As threat actors operationalize AI to accelerate attacks, they are also leveraging the wider global interest around AI itself as a social engineering lure. In recent months, Microsoft Threat Intelligence has observed a growing number of campaigns that impersonate the branding of popular AI platforms such as ChatGPT, Microsoft Copilot, DeepSeek, and Anthropic’s Claude as lures. These campaigns, which don’t represent compromise of services, span phishing, malvertising, and search engine optimization (SEO)-driven attacks that ultimately lead to credential theft, financial fraud, or malware infection.

Threat actors are quick to capitalize on highly anticipated launches or emerging trends, leveraging trusted branding and exploiting user curiosity to improve the success rates of their campaigns. Despite the AI-themed lures, however, these campaigns combine longstanding tactics, such as urgency-driven messaging, abuse of trusted services, and multi-stage redirection chains that require user interaction to evade detection.

While traditional lures like invoices, payment notifications, or delivery alerts remain effective and continue to be widely used, AI-themed lures reflect a shift in social engineering that is likely to persist as a long-term tactic used by threat actors, from cybercriminal groups to nation states. Notably, Microsoft Threat Intelligence has observed the initial access broker Storm-3075 employing AI-themed malvertising to deliver payloads, including malware signed by the malware-signing-as-a-service (MSaaS) offering attributed to the financially motivated threat actor Fox Tempest, on behalf of multiple downstream actors.

This blog details several of the campaigns observed by Microsoft Threat Intelligence in the past few months that used AI brands and references as lures, and provides guidance to help users and organizations detect, mitigate, and respond to these threats. Importantly, Microsoft believes that the activity noted in this blog is purely abuse of AI brand names as lures, not reflecting a compromise of any referenced vendor. As threat actors scale their operations with AI, organizations should leverage AI-powered security capabilities to enhance visibility, automate detection, and accelerate response across email, identity, and endpoint surfaces.

ChatGPT-themed lure leads to phishing kit collecting credit card data

On May 5, 2026, Microsoft detected a ChatGPT-themed phishing attack that delivered malicious URLs leading to phishing pages that collected credit card and personal information such as names and addresses. This phishing activity, which consisted of 4,500 emails sent to targets in South Africa (97%), was part of a broader campaign using similar themes and infrastructure. We also observed this campaign delivering as much as 100,000 emails on a single day to targets in Switzerland, Austria, and South Africa affecting a broad range of industries, including higher education and professional services.

The emails used the sender display name ChatGPT and the subject “To ensure your ChatGPT Plus continues to work – please update your payment method”. The emails posed as an urgent request to update the ChatGPT Plus subscription payment method. They warned the recipient that if a new payment method was not provided within seven days, the account would be downgraded to a free plan. A ChatGPT logo was prominently displayed at the top of the email body.

The phishing email contained a clickable Update payment method button, which did not directly send users to the attacker-controlled site. Instead, users were redirected through a series of legitimate and abused redirector hops. This is a common technique used by threat actors to exploit the reputation of trusted domains and bypass email filters, evade detection, and track victim engagement.

Targets were first directed to grupoconstat[.]bitrix24[.]com[.]br (a legitimate customer relationship management (CRM) service), which redirected to awstrack[.]me (an Amazon domain used for tracking email opens and clicks), which in turn redirected to a Rebrandly URL (a legitimate but often abused URL shortener service). Targets were finally sent to a likely legitimate but compromised domain legendarytrendsbay[.]shop where the threat actor had placed the phishing page in the /ChatGPT/ folder.

The landing page did not immediately display the phishing content. It first required visitors to pass a custom CAPTCHA, which was a simple Update payment button. If they clicked this button, users were sent to the next page where personal information, including first name, last name, and address was collected. The final page then collected the name, credit card number, expiration date, and card verification code.

Claude-themed phishing campaign collected credentials and access tokens

From April 20 to 22, 2026, Microsoft observed a phishing campaign impersonating Anthropic-branded services to target users with account-related lures tied to the Claude AI platform. The campaign sent phishing emails to targets across more than 2,000 organizations, primarily in the United States (62%), the United Kingdom (18%), and India (9%). While this campaign impacted a broad range of industries, it was most notably focused on information technology (56%), other business entities (21%), and financial services (8%).

The campaign used enforcement-themed messaging claiming that the recipient’s account was in violation of acceptable use policies and required immediate action. The emails impersonated Anthropic’s popular AI service Claude using the display names Anthropic Teams and Anthropic PBC, masquerading as legitimate account-related communications. Subject lines followed a consistent structure of “Claude Appeal Request” combined with date elements.

The email body was delivered as HTML and included Anthropic and Claude branding. The message informed recipients that their account was violating “AUP (Account Usage Policy)” and that Anthropic had “initiated an appeal procedure”. The message instructed recipients to review the attached material to access their appeal and indicated that Claude features would be limited pending review.

The email attachment was a PDF named Fill and Sign Claude Appeal Form.pdf, which was designed to resemble an official process tied to Claude account enforcement. The document presented an appeal workflow, prompting users to copy an appeal ID and click the “Claude Appeal” link, which initiated the credential harvesting process.

When clicked, the link embedded in the PDF directed users to an attacker-controlled domain, dash.awaydouble[.]org. The initial landing page displayed a Cloudflare verification prompt, presented as confirming the user was arriving from a “legitimate session”. This step likely served as a gating mechanism to impede automated analysis and sandbox detonation.

Users who completed the verification were redirected to another Claude-themed landing page hosted on servicing.pureplantcravings[.]com. This page was named “Account Appeal Notice” and contained “Account Security & Compliance” message informing users that their account had been flagged for repeated violations of usage policies. The page provided a reference date and a one-time access code, prompting users to copy the code and continue.

Clicking “Continue” redirected users to the final page, which was not available at the time of analysis. Source code revealed conditional redirect logic that routed users to one of two final landing pages, depending on whether the site was accessed through mobile device or a desktop system.

While the final redirect destination was no longer active at the time of analysis, infrastructure overlap, including shared intermediate domains and consistent redirect logic, strongly suggested that users were ultimately presented with a Microsoft sign-in experience. This final stage is consistent with adversary-in-the-middle (AiTM) tactics designed to intercept authentication tokens and facilitate account compromise.

“Awesome AI Windows Plugin” malvertising deploys Vidar stealer

Since at least early 2026, Microsoft Threat Intelligence has observed malvertising campaigns that use AI-themed terms such as “Awesome AI Windows Plugin” and “Flux Pro AI” in social engineering lures in malicious popups, in malware executable names, and GitHub repository and folder names throughout the attack chain. These campaigns are notable for their scale and velocity, moving from launch to mass impact within hours and infecting tens to hundreds of thousands of endpoints. The malware delivered in these campaigns is frequently code-signed, lending an additional layer of perceived trust to both the operating system and the user.

Microsoft attributes this malvertising activity to an initial access broker and malware distributor tracked as Storm-3075. We assess that Storm-3075 delivers final payloads on behalf of multiple downstream actors. While the example campaign described in this section delivered Vidar Stealer, we have also observed this campaign distributing Lumma Stealer, Hijack Loader, and Oyster.

On March 13, 2026, a single campaign run targeted over 66,000 devices. Microsoft has revoked the related signing certificate and GitHub has taken down the associated repository, helping to prevent tens of thousands of additional infections. Given the nature of the attack source, majority of impacted devices were likely consumer rather than enterprise endpoints. Telemetry showed global distribution, with the top affected countries being Japan, South Africa, the United States, and France.

Analysis of the redirection chain determined that the attack likely originated from free movie streaming sites. Infections on such sites typically begin when users interact with embedded movie players or click popups. Malvertising embedded in such sites can redirect users to a range of unwanted content, including malware. In this campaign, users were redirected to a page advertising a download for an “Awesome AI Windows plugin”, a fictitious product name. The plugin purported to help users watch free, high-quality videos, a lure aligned with the context of users already streaming free or pirated content.

Clicking the download button retrieved an executable named ProFluxeFlowAi-win-Setup.exe, which the user then had to manually launch. The file name mimicked a legitimate product with a similar name, Flux Pro AI, which supports text, image, and video creation. This lure reinforced the perceived legitimacy of the executable within the streaming of free movies context. The executable itself was hosted on GitHub in a repository named shippingtechnologymovie under a folder named AI-techVideos, both tailored to the AI video helper narrative.

The malware executable was signed with a fraudulently obtained Microsoft-issued code-signing certificate obtained through Artifact Signing (certificate thumbprint: 4f5c5b3ef45cfff7721754487a86aeff9a2e6e32). Microsoft attributes the signing service used by the threat actor to Fox Tempest, a financially motivated threat actor operating a malware-signing-as-a-service (MSaaS) offering used by other threat actors. Microsoft has revoked over one thousand code signing certificates attributed to Fox Tempest. In May 2026, Microsoft’s Digital Crimes Unit (DCU), in partnership with Resecurity, facilitated a disruption of Fox Tempest infrastructure and access model.   

Signing malware through such a service is expensive; however, for a threat actor targeting tens or hundreds of thousands of infections, the cost can be justified by the additional level of trust signed binaries imply to both the operating system and the user. Signed malware also tends to exhibit lower detection rates early in the infection lifecycle, extending the window of effective distribution.

Another notable feature of the malware is that, immediately after launch, it displays a window with a “Continue” checkmark and does not proceed until the box is clicked. This extra user interaction step is uncommon. We assess that this technique is intended to hide the malicious functionality from sandboxes and automated analysis environments that cannot dynamically perform the click. Until the user clicks “Continue,” the malware performs no suspicious activity on the operating system. This technique is functionally analogous to the CAPTCHAs frequently seen in phishing attacks.

Once the user clicks “Continue”, the executable drops and runs a malicious Python-based downloader. Both the Python interpreter and the downloader script are saved in the \AppData\Local\ folder as pythonw.exe and LICENSE.txt, respectively. The malicious script runs shellcode that loads the next-stage malware from the command-and-control (C2) domain brokeapt[.]com. The final payload observed in this campaign was Vidar infostealer.

Fake DeepSeek V4 installers on GitHub delivered Vidar Stealer

In April 2026, Microsoft identified a social engineering campaignsocial-engineering campaign that leveraged interest in the newly released DeepSeek V4 by impersonating it through a fraudulent GitHub repository and organization. The campaign abused GitHub’s release-asset infrastructure to deliver information-stealing malware such as Vidar stealer. Search engines increased the exposure of the malicious repository, exacerbated by the fact that DeepSeek did not publish an official V4 repository on GitHub.

Our investigation shows the DeepSeek lure is one identity in a broader rotating brand-abuse ecosystem that recycles whichever AI tool is trending into a fresh malware download experience. After discovering this activity, Microsoft shared the details with GitHub, and GitHub has since taken down the malicious organization, repository, and operator account.

On April 24, 2026, within hours of DeepSeek officially previewing its new V4 frontier model, a threat actor initiated the attack chain that can be summarized as:

1. Resource development on GitHub, all within roughly 45 minutes: A new GitHub organization (DeepSeek-V4), a single repository (deepseek-V4), and a release tag (deepseek-V4). The repository was decorated with stolen DeepSeek branding, real benchmark data, and SEO-optimized topics.
2. Search-driven discovery: Users found the repository through GitHub repository search, search engines, social sharing, and AI-assisted search results pointing to the lure page. The repository’s llms.txt and topic taxonomy were designed to be discovered by both classical search engines and large-language-model-powered search; observed top-rank results on search engines are consistent with that design, though we did not observe paid advertising and therefore do not assess this as malvertising.
3. Archive download from GitHub’s release-asset CDN: The release page hosted two archives, deepseek-v4-pro_x64.7z and deepseek-v4-flash_x64.7z.
4. User extraction: Users needed to extract the executable from the archive using common Windows archive tools.
5. Payload execution: The archives contained a heavyweight Win32 PE that masqueraded as the DeepSeek installer. At least one confirmed victim endpoint revealed the extracted payload landed at: C:\Users\<user>\Downloads\Programs\IA DeepSeek-V4\deepseek-v4-flash_x64.exe.
6. Active payload rotation: The threat actor actively rotated archive content while preserving file names and the release page. We observed at least three distinct archive hash generations in three days.

Microsoft Defender telemetry observed the first victim download approximately four hours later. The threat actor’s operational tempo on April 24, 2026, is consistent with a prepared, rehearsed workflow. The repository was designed to be convincing at a glance. It accumulated 91 stars and 27 forks within four days, though the proportion of organic versus inflated engagement is not independently confirmed. The attacker invested in several credibility-building elements:

• Stolen branding: The repository’s README and assets folder embedded the legitimate DeepSeek whale logo, copied from the real deepseek-ai/DeepSeek-V2 repository.
• Real benchmark data as lure: The release notes displayed authentic DeepSeek V4 benchmark scores against Claude Opus 4.6, GPT-5.4, and Gemini 3.1 Pro, copied from the official release announcement.
• Action-oriented SEO topics: The repository was tagged with deepseek-v4, deepseek-v4-download, deepseek-v4-downloader, deepseek-v4-install, and deepseek-v4-installer, which are queries users are expected to use when intent-shopping for an installer.
• LLM-aware discoverability: A top-level llms.txt file repeated the same SEO copy in a format aimed at AI-assisted search engines.

On closer inspection, the staging gives the operation away: the repository contained only a README, LICENSE, llms.txt, and stub assets/ and inference/ directories with no real model code; all nine commits were made in a single burst on April 24, 2026 by a single author; the README claimed an MIT license while repository metadata specified Apache 2.0.

Once the lure was live, search engines increased the exposure of the malicious repository. We tested the queries an interested user would naturally try when looking for DeepSeek V4 on GitHub or the open web. In a snapshot captured on April 28, 2026, the results were as follows (search results are volatile and may differ at the time of reading):

The 7z archives hosted on GitHub contained a loader executable such as SHA-256: 5455341ed1bbe75a664fca2dd0794c508e1874f75360253a7ff5bc119bc92d80. The loader was observed downloading and installing Vidar stealer and potentially additional malware.

Lastly, Microsoft observed that the DeepSeek-themed payloads share infrastructure with a much larger rotating fake-AI / fake-tool ecosystem. The same shared loader hash (SHA-256 5455341…) appeared under file names impersonating GPT-5.5, Claude Code, Kimi, Seedance, Gemma, GrokCLI, Manus AI, FraudGPT, and others (see table below). Public research from Trend Micro, Zscaler ThreatLabz, and Huntress describe the same broader ecosystem, with TradeAI.exe, OpenClaw_x64.7z, WormGPT_x64.7z, and DeepSeekAI_agent_x64.7z appearing as sibling lures and the downstream payload set documented as Vidar plus GhostSocks.

Mitigation and protection guidance

To defend against social engineering campaigns that leverage AI brands as lures, 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 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: 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.

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 Threat Intelligence podcast.

The post AI brands as bait: How threat actors are using the AI hype in social engineering appeared first on Microsoft Security Blog.

Ransomware that combines robust encryption with rapid lateral movement significantly increases the risk and impact of an attack. The Gentlemen ransomware is a ransomware-as-a-service (RaaS) threat that is distinguished by its ability to pair its strong per-file encryption with an aggressive self-propagation capability designed to enable broad network compromise. In addition to using per-file ephemeral Curve25519 keys with XChaCha20 stream cipher, The Gentlemen ransomware attempts to spread across an environment using series of simultaneous, distinct lateral movement methods, increasing the likelihood of widespread impact once initial access is achieved.

Microsoft Threat Intelligence tracks the operators behind the ransomware as Storm-2697, a financially motivated threat actor that manages the RaaS platform known as “The Gentlemen” while affiliates carry out attacks. Emerging around mid-2025, The Gentlemen initially started as a closed ransomware group then began offering its RaaS to affiliates in September 2025. More recently, The Gentlemen operators established an official partnership with BreachForums, a popular cybercriminal marketplace, to recruit affiliates including penetration testers and initial access brokers. Given that The Gentlemen is already a widely adopted RaaS platform, this partnership may lead to increased activity as the program becomes accessible to a broader pool of threat actors.

The operators behind the ransomware use double extortion tactics, encrypting data while also exfiltrating sensitive information to pressure victims through the threat of public release if the ransom is not paid. The ransomware is written in Go and obfuscated with Garble to target the Windows environment. Microsoft has observed The Gentlemen ransomware impacting organizations across education, transportation, healthcare, and financial industries in North America, South America, Europe, Africa, and Asia.

In this blog, we present a detailed analysis of the Gentlemen ransomware encryptor, including its execution flow, defense evasion behaviors, encryption design, and lateral movement techniques. This research is intended to provide defenders, incident responders, and the broader security community with a better understanding of how the threat operates, from initial argument parsing and defense evasion, through its file encryption internals, to the full lateral movement that enables it to propagate across the network. We also provide mitigation guidance, Microsoft Defender detections, hunting queries, and indicators of compromise (IOCs) to help organizations defend against this threat and similar ransomware activity.

Pre-encryption

Command-line argument processing

The ransomware operator can control The Gentlemen encryptor through command-line arguments. A password is required for execution, and optional arguments allow the operator to specify encryption scope, speed, lateral movement, and post-encryption behaviors.

The binary accepts the following arguments:

The --full command-line argument appears to be the intended mode of operation for comprehensive file encryption on the infected device. When this argument is provided, the malware spawns two child processes of itself: one appended with the argument --system to encrypt local volumes under a SYSTEM-privileged scheduled task, and one appended with the argument --shares to encrypt network shares. This separation ensures that the malware can reach both local drives (which might require SYSTEM privileges) and mapped network shares (which are only visible in the user’s session).

The speed arguments (--fast, --superfast, --ultrafast) are mutually exclusive and control how much of each large file is encrypted. When no speed flag is specified, the default per-chunk percentage is 9%. These flags only affect files that are larger than 1 MB, and small files are fully encrypted regardless of the speed setting.

Usage prompt

When the encryptor is executed with no command-line argument, the malware prints a branded usage banner to the console.

It first executes the following PowerShell commands to render a console header:

This is followed by a detailed usage prompt provided by the malware author that documents all available flags with descriptions and examples:

It is worth noting that the file size percentages listed in the usage prompt refer to the total file encryption amount. Internally, the malware encrypts three separate chunks, and the per-chunk percentage used in the code is: fast=3%, superfast=1%, ultrafast=0.3%, default=9%.

Password check

Before executing its primary functionality, the malware validates the --password argument against a hardcoded value embedded within the binary. For the sample analyzed in this blog, the expected password is “9VoAvR7G”. If the provided password does not match, the malware outputs bad args and terminates execution.

This password check is a simple operator authentication mechanism, with each build containing a unique embedded password. Its purpose is to restrict execution to authorized operators and reduce the risk of accidental or unauthorized detonation if the binary is recovered or intercepted. However, because this validation relies on a static comparison, it can be easily identified and bypassed through static analysis techniques.

System encryption: Privilege escalation

When the --system argument is provided (either directly or via the --full argument), the malware creates a scheduled task to re-execute itself as SYSTEM. If a delay value is also specified through the --T argument, the scheduled execution time is adjusted accordingly.

To relaunch itself as SYSTEM, it issues the following sequence of commands:

The malware can only perform this task if it’s executed from an account with administrator privilege. It first deletes any existing task named gentlemen_system to avoid conflicts, creates a new one-time task that runs its binary under the SYSTEM account, and finally triggers that task.

This sequence ensures a clean state by first removing any existing task with the same name (gentlemen_system), creating a new scheduled task that executes the ransomware binary with SYSTEM-level privileges before finally triggering its immediate execution.

When running within this scheduled task context, the malware sets the environment variable LOCKER_BACKGROUND=1. This variable functions as an internal execution flag, indicating that the process is operating as a background encryption worker with elevated privileges, rather than as the original operator-invoked instance.

Defense evasion

Before starting file encryption, the malware executes a sequence of commands to disable defensive controls and remove potential forensic artifacts.

Disable Microsoft Defender

The PowerShell commands disable Microsoft Defender real-time monitoring to remove active protection on the infected device. The malware then adds its own executable to the Defender exclusion list to avoid detection. Finally, it excludes the entire C:\ volume from scanning, reducing the likelihood of subsequent detection during file encryption.

Delete shadow copies and event logs

To further impede recovery efforts, the malware deletes all Volume Shadow Copies using both vssadmin and wmic (Windows Management Instrumentation command-line utility). It then clears the System, Application, and Security event logs using wevtutil to remove key audit trails.

Delete forensics artifacts

These commands remove a variety of forensic artifacts, including prefetch files that track program execution, Defender diagnostic and support logs, and Remote Desktop Protocol (RDP) logs.

Additionally, the malware manually deletes PowerShell command history across all user profiles by removing the following file:

This action eliminates evidence of previously executed PowerShell commands, further reducing the visibility of execution history and threat actor activity.

Process and service termination

Process termination

The malware stops a list of running processes using the command:

The table below summarizes the different categories and processes being targeted:

Service termination

In addition to terminating processes, the malware disables and stops a list of Windows services using the commands:

The table below summarizes the different categories and services being targeted:

Terminating these processes and services serves two primary objectives:

• File access and encryption reliability: Many targeted processes/services, such as databases, Office applications, and backup agents, maintain active file locks. By forcibly terminating these processes, the ransomware ensures that locked files become accessible for encryption.
• Defense and recovery disruption: By stopping backup services, endpoint protection agents, and remote access tools, the malware reduces the likelihood of real-time detection and data restoration from backups.

Collectively, these behaviors maximize encryption coverage while hindering the environment’s ability to detect, respond to, or recover from the attack.

Persistence

The encryptor can establish persistence for itself through two mechanisms: scheduled tasks and registry keys.

Scheduled tasks persistence

For establishing persistence with scheduled tasks, the malware executes the following sequence of commands:

These commands first remove any pre-existing tasks with the same names, then create two persistence mechanisms that execute automatically at system startup. The UpdateSystem task launches the payload in the SYSTEM security context, while the UpdateUser task launches it in the currently signed-in user’s context. This design increases the likelihood that the ransomware will run after reboot regardless of privilege level or sign-in state.

Registry keys persistence

For establishing persistence with the registry, the malware executes the following sequence of commands:

The GupdateS value under HKEY_LOCAL_MACHINE (HKLM) provides device-wide persistence that allows the malware to run at startup for all users, while the GupdateU value under HKEY_CURRENT_USER (HKCU) provides user-scoped persistence within the current profile. By writing to both registry hives, the malware establishes redundant autorun paths across both system-level and user-level execution contexts.

Together, the scheduled tasks and Run key modifications create layered persistence, ensuring that the encryptor is re-executed after a reboot in both privileged and user-context scenarios.

Network share traversal

When the command-line argument --shares is provided, the malware initiates network share discovery and enumeration. It begins by probing all drive letters A through Z to identify mapped network drives using the following commands:

This sequence discovers any drives that are already mapped in the current user’s session, which are then added to the encryption target list.

To further enhance visibility into the network environment, the malware enables multiple Windows network discovery services and their associated firewall rules using the following commands:

The services enabled as part of this process include:

• Function Discovery Resource Publication (fdrespub): Publishes the host’s resources to the network, allowing other systems to detect it.
• Function Discovery Provider Host (fdPHost): Hosts provider components responsible for discovering network resources.
• Simple Service Discovery Protocol (SSDP) Discovery (SSDPSRV): Enables discovery of Universal Plug and Play (UPnP) devices.
• UPnP Device Host (upnphost): Supports the hosting and management of UPnP devices.

Finally, the malware reinforces this configuration by enabling the Network Discovery firewall rule group. This redundancy ensures that firewall restrictions do not limit its network visibility, further maximizing the number of reachable targets for encryption and propagation.

Volume and directory traversal

To enumerate all available volumes on the system, the malware executes the following PowerShell command sequence:

This command queries Windows Management Instrumentation (WMI) for all mounted volumes with drive letter paths and attempts to enumerate Cluster Shared Volumes (CSVs).

Additionally, the malware performs a secondary enumeration routine by iterating through drive letters A through Z while verifying their existence on disk. This brute-force method ensures broader coverage by identifying volumes that might not be retrieved through WMI queries to maximize visibility into all potential encryption targets.

Directory exclusion list

To maintain system stability and avoid disrupting critical operating system components, the malware excludes a predefined set of directories from traversal and encryption. These directories include core Windows system paths, application directories, and locations commonly associated with security and system management:

Extension exclusion list

The ransomware also excludes a set of file extensions associated with system-critical binaries, configuration files, and executable content:

By avoiding executable files, libraries, scripts, and other system-relevant formats, the malware preserves the integrity of the operating environment. This selective encryption model is a common ransomware design pattern, ensuring that the system remains operational enough for the victim to receive instructions and facilitate ransom payment.

File name exclusion list

The specific file names below are also excluded:

The inclusion of README-GENTLEMEN.txt, the ransomware’s ransom note, prevents it from being encrypted during execution. This ensures that the ransom instructions remain accessible to the victim, which is critical for the operator’s monetization workflow.

Ransom note

During directory traversal, the malware drops a ransom note named README-GENTLEMEN.txt in each scanned directory to provide victim-facing instructions.

The note contains identifiers assigned to the victim, communication channels, and guidance on how to initiate contact with the operators.

File encryption

File ownership

Before encrypting a file, the ransomware modifies the file ownership and access control settings to ensure it has unrestricted write access to the target. This is achieved through the following sequence of commands:

The takeown command recursively transfers ownership of the specified file or directory to the executing user, overriding existing ownership constraints. The icacls command then grants full control permissions to the Everyone security identifier (SID S-1-1-0), applying inheritance flags to propagate these permissions to all child objects. Finally, the attrib command removes the read-only attributes.

Cryptographic scheme

The Gentlemen ransomware implements a hybrid cryptographic design that combines Curve25519 elliptic-curve cryptography with the XChaCha20 stream cipher to achieve efficient and secure per-file encryption.

For each file, the malware performs the following sequence of operations:

1. Generates a unique ephemeral Curve25519 key pair, consisting of a randomly generated private key and its corresponding public key
2. Computes the Elliptic-curve Diffie–Hellman (ECDH) shared secret between the ephemeral private key and the operator’s embedded public key
3. Uses the resulting shared secret as the XChaCha20 key, and derives the nonce from the first 24 bytes of the ephemeral public key
4. Encrypts the file contents using XChaCha20 with this key and nonce combination
5. Appends the Base64-encoded ephemeral public key to the file footer to enable subsequent key reconstruction during decryption

In this sample, the operator’s public key is hard-coded within the binary as a Base64-encoded value:

This design ensures that each file is encrypted with a distinct key and nonce derived from a per-file ephemeral key exchange, eliminating any possibility of key or nonce reuse across files.

During decryption, the decryptor can use the operator’s Curve25519 private key together with the stored ephemeral public key to reconstruct the ECDH shared secret and recover the XChaCha20 key. The nonce is deterministically reconstructed by extracting the first 24 bytes of the recovered ephemeral public key, making separate nonce storage unnecessary.

Overall, this approach provides strong cryptographic isolation between encrypted files while maintaining operational simplicity and efficiency for the threat actor during both encryption and decryption.

Size-based encryption

The malware uses different encryption strategies based on file size:

Small files that are less than 1MB in size are fully encrypted. This ensures that documents, configuration files, and other small but critical data are completely corrupted. For larger files such as databases, virtual disk images, archives, full encryption would be time-consuming. Instead, the malware encrypts three data chunks distributed across the file, which is sufficient to corrupt the file structure while dramatically reducing encryption time.

After encryption, each affected file is renamed with the appended extension .umc16h. This extension serves as a quick indicator of files already encrypted by the ransomware.

Large file chunking logic

For files larger than 1 MB, the malware performs partial encryption by dividing the file into three non-contiguous chunks distributed across its contents:

The first chunk begins at the start of the file, the second is positioned near the midpoint, and the third is located toward the end. This distribution ensures that even limited encryption is sufficient to corrupt the file structure while minimizing processing time.

Each chunk is encrypted in 64 KB (0x10000) blocks using XChaCha20. To maintain cryptographic separation between chunks, the malware modifies the nonce on a per-chunk basis. Specifically, the last byte of the 24-byte XChaCha20 nonce is XOR-ed with the chunk index (0, 1, or 2), and a new cipher instance is initialized for each chunk using the modified nonce. As a result, chunk 0 uses the original nonce, while subsequent chunks use deterministically altered variants.

Although all chunks for a given file share the same derived encryption key, this nonce mutation ensures that each chunk is processed under a unique keystream, preventing keystream reuse across different regions of the file.

The encryption percentage for each file is determined by the provided speed command-line arguments:

File footer

After encrypting each file, the malware appends a structured footer containing metadata required for identification and decryption. The footer format differs slightly depending on whether the file was fully or partially encrypted.

Small file encryption (files ≤ 1 MB):

Large file encryption (files > 1 MB):

The footer serves three primary functions:

1. Key and nonce reconstruction: The Base64-encoded ephemeral public key, located after --eph--, allows the decryptor to recompute both the XChaCha20 key (using ECDH shared secret) and the nonce (first 24 bytes of the ephemeral public key).
2. Identification: The GENTLEMEN marker, located after --marker--, serves as a unique identifier, allowing encryptors/decryptors to quickly determine that the file has been encrypted by The Gentlemen ransomware.
3. Decryption mode: The optional speed flag marker (only present on large files) tells the decryptor which chunking percentage was used.

Notably, the speed marker is only present for large-file encryption. Files that are ≤ 1 MB do not include a speed marker, and its absence signals that the file was fully encrypted. This implicit encoding in the footer allows the decryptor to distinguish between full and partial encryption modes without requiring additional metadata fields.

Post-encryption

Wallpaper setup

If the --silent argument is not provided, the malware drops the following bitmap image file to %TEMP%\gentlemen.bmp and sets it as the system’s desktop wallpaper.

This behavior serves as an immediate visual indicator of compromise, signaling to the victim that encryption has completed.

Self-propagation

The self-propagation module is the more distinctive component of The Gentlemen ransomware. When enabled with the --spread argument, it turns the malware from a single-host encryptor into a self-propagating worm that attempts to deploy its encryptor to every reachable system on the network.

The --spread argument accepts either explicit credentials in domain/user:password format for authenticated lateral movement, or an empty string to reuse the current session’s authentication token.

Placeholder legend

The executed commands in this section use the following placeholders:

Phase 1: Local staging setup

The malware prepares the infected host to act as a distribution point for its binary by executing the following command sequence:

The commands copy the malware executable into C:\Temp, creates a hidden Server Message Block (SMB) share named share$ pointing to that directory, and modifies registry settings to allow anonymous access. With this setup, other systems on the network can retrieve the payload from \\<self>\share$, even when valid credentials are not available.

Phase 2: PsExec drop

The malware binary carries an embedded copy of PsExec and drops it to C:\Temp\psexec.exe on the infected device.

If the embedded PsExec payload cannot be extracted successfully, the malware falls back to downloading PsExec directly from Microsoft’s Sysinternals Live service using the following PowerShell command:

Phase 3: Network enumeration

After dropping PsExec, the malware attempts to enumerate and discover remote systems on the network, including workstations, servers, and domain controllers. Each discovered host becomes a candidate target for propagation.

Phase 4: PowerShell defense evasion blob

Before attempting to run the payload on a remote system, the malware executes the following PowerShell command on the remote target to weaken local defenses and make payload execution more reliable:

This command disables Microsoft Defender real-time monitoring, adds broad Defender exclusions, turns off Windows Firewall across all profiles, shares local drives, grants permissive New Technology File System (NTFS) access, enables SMB1, and loosens anonymous-access restrictions through Local Security Authority (LSA) registry settings. Together, these changes make the remote system significantly more exposed and ready for the payload deployment step.

Phase 5: Payload deployment

For each discovered remote host, the malware attempts a series of independent lateral movement techniques to execute its payload. Notably, these techniques are executed without dependency on prior success, and each method is attempted regardless of whether earlier attempts fail. This execution model of The Gentlemen’s propagation logic can significantly increase the likelihood that at least one execution path succeeds even in secured environments.

5.1: Remote file copy

The malware first stages its payload on the remote system by copying the encryptor binary over the administrative C$ share:

This operation ensures a local copy of the payload is available on the target host, allowing subsequent execution methods to reference a path that does not depend on network shares.

5.2: PsExec-based execution

If PsExec is successfully dropped or downloaded, the malware leverages it to perform a multi-stage execution sequence on the remote host.

First, the malware executes the PowerShell defense evasion payload to weaken host protections:

After a delay to allow defenses to be disabled, the malware executes the payload from the locally staged path C:\Temp under SYSTEM privileges:

After another sleep period, the malware executes the final command to run the payload with the –h flag for elevated token and –c -f to copy and force execution:

5.3: WMIC process creation

The malware uses WMI via wmic.exe to create remote processes:

The first command executes the defense evasion blob, the second runs the payload from the infected host’s SMB share, and the third runs the pre-staged copy from the target’s local C:\Temp directory.

5.4: Scheduled tasks (user)

The malware creates three scheduled tasks under the target user’s context, each running two minutes after the time when they are created:

The scheduled task DefU is set to run the defense evasion blob, UpdateGU executes the payload from the infected host’s SMB share, and UpdateGU2runs the pre-staged copy from the target’s local C:\Temp directory.

5.5: Scheduled tasks (system)

The same three tasks are repeated, running under the SYSTEM account:

By attempting both user-context and SYSTEM-context task creation, the ransomware can improve its chance of propagation across environments with different permission boundaries.

5.6: Service-based execution

The malware executes the following command sequence to create three Windows services on the target host:

Similar to the scheduled tasks, the service DefSvc is set to run the defense evasion blob, UpdateSvc executes the payload from the infected host’s SMB share, and UpdateSvc2 runs the pre-staged copy from the target’s local C:\Temp directory. These services run as SYSTEM by default, which provides another high-privilege execution path for the ransomware payload on the remote system.

5.7: Payload deployment: PowerShell remoting

Using PowerShell remoting, the malware executes commands directly on the target using Invoke-Command:

This method leverages Windows Remote Management (WinRM), providing an alternative execution channel when PsExec or WMIC are unavailable or blocked.

5.8: PowerShell WMI execution

Finally, the malware uses the PowerShell WMI class interface directly to create remote processes with the following command sequence.

This provides functionality equivalent to wmic.exe, but through a different execution path. As a result, it might succeed in environments where the WMIC binary is restricted but WMI access remains available.

Self-propagation summary

Across all techniques, the malware attempts 21 remote execution operations per target host, spanning multiple APIs, privilege levels, and execution contexts. Each method attempts to launch the payload from:

• The infected host’s SMB share: \\<self>\share$\<payload_name>
• The target host’s locally staged path: C:\Temp\<payload_name>

This redundancy is central to The Gentlemen’s propagation strategy. In secured environments where most lateral movement techniques are mitigated, a single successful execution on a single additional host is sufficient to continue the propagation.

Free space wipe

If the --wipe argument is provided, The Gentlemen ransomware performs an additional post-encryption routine to eliminate recoverable artifacts from disk.

The malware first enumerates all available volume paths on the system. For each volume, it creates a temporary file named wipefile.tmp at the root directory and determines the amount of available free space. It then writes random data to this file in 64 MB blocks until the volume is completely filled. Once the disk space has been exhausted, the temporary file is deleted.

This process effectively overwrites all unallocated disk space with random data, preventing forensic tools from recovering remnants of previously deleted files. This includes cached or temporary versions of original unencrypted data that might still reside on disk. When combined with earlier actions such as Volume Shadow Copy deletion, this behavior reduces the likelihood of data recovery without access to the threat actor’s decryption key.

Self-delete

If the --keep flag is not provided, the malware attempts to remove its executable from disk after completing encryption.

Since a running process cannot directly delete its own binary, the ransomware generates and executes a temporary batch script at <malware_path>.batwith the following contents:

The batch script introduces a short delay by sending three Internet Control Message Protocol (ICMP) echo requests to the local host, pausing execution long enough for the main malware process to terminate. After this delay, the script deletes the original ransomware executable before removing itself. This mechanism helps reduce on-disk artifacts and hinders post-incident forensic analysis by eliminating the ransomware binary from the compromised system.

Defending against The Gentlemen ransomware

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

• Read the human-operated ransomware threat overview for advice on developing a holistic security posture to prevent ransomware, including credential hygiene and hardening recommendations. 
• Turn on cloud-delivered protection in Microsoft Defender Antivirus or the equivalent for your antivirus product to cover rapidly evolving threat actor tools and techniques. Cloud-based machine learning protections block a huge majority of new and unknown variants. 
• Turn on tamper protection features to prevent threat actors from stopping security services. In addition to tamper protection, you can also enable and configure Microsoft Defender Antivirus always-on protection in Group Policy. 
• Enable controlled folder access. Controlled folder access helps protect your valuable data from malicious apps and threats, such as ransomware. Controlled folder access works by only allowing trusted apps to access protected folders. Protected folders are specified when controlled folder access is configured. Apps that aren’t included in the trusted apps list are prevented from making any changes to files inside protected folders. 
• 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. 
• Configure investigation and remediation in full automated mode to let Microsoft Defender for Endpoint take immediate action on alerts to resolve breaches, significantly reducing alert volume. 
• 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 several of the infection vectors of this threat. These rules, which can be configured by any user, offer significant hardening against targeted attacks. In observed attacks, Microsoft customers who had the following rules turned on could mitigate the attack in the initial stages and prevent hands-on-keyboard activity:  
  • Block executable files from running unless they meet a prevalence, age, or trusted list criterion 
  • Block process creations originating from PSExec and WMI commands if you’re managing your devices with Intune or another MDM solution. This rule is incompatible with management through Microsoft Endpoint Configuration Manager. 
  • Use advanced protection against ransomware

Microsoft Defender detections 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 Defender Antivirus

Microsoft Defender Antivirus detects threat components as the following malware:

• Ransom:Win64/Gentlemen

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.

• Ransomware-linked threat actor detected
• Ransomware behavior detected in the file system
• Possible ransomware activity
• File backups were deleted
• Potential human-operated malicious activity
• Possible data exfiltration
• Suspicious wallpaper change

The following alerts might indicate threat activity associated with The Gentlemen ransomware if Defender for Endpoint is set to block mode.

• ‘Gentlemen’ ransomware was detected
• ‘Gentlemen’ ransomware was prevented

Microsoft Defender for Cloud Apps

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

• Ransomware activity

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

• Tool profile: Gentlemen ransomware
• Threat overview profile: Human-operated ransomware

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:

Known The Gentlemen ransomware files

Search for the file hashes associated with The Gentlemen ransomware activity identified in this report. 

let fileHashes = dynamic(["22b38dad7da097ea03aa28d0614164cd25fafeb1383dbc15047e34c8050f6f67"]);
union
(
   DeviceFileEvents
   | where SHA256 in (fileHashes)
   | project Timestamp, DeviceId, DeviceName, FileName, InitiatingProcessFileName, FileHash = SHA256, SourceTable = "DeviceFileEvents"
),
(
   DeviceEvents
   | where SHA256 in (fileHashes)
   | project Timestamp, DeviceId, DeviceName, FileName, InitiatingProcessFileName, FileHash = 
SHA256, SourceTable = "DeviceEvents"
),
(
   DeviceImageLoadEvents
   | where SHA256 in (fileHashes)
   | project Timestamp, DeviceId, DeviceName, FileName, InitiatingProcessFileName, FileHash = SHA256, SourceTable = "DeviceImageLoadEvents"
),
(
   DeviceProcessEvents
   | where SHA256 in (fileHashes)
   | project Timestamp, DeviceId, DeviceName, FileName, InitiatingProcessFileName, FileHash = SHA256, SourceTable = "DeviceProcessEvents"
)
| order by Timestamp desc

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 web sessions IP and file hash indicators of compromise using Advanced Security Information Model (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(["22b38dad7da097ea03aa28d0614164cd25fafeb1383dbc15047e34c8050f6f67"]);
_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 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(["22b38dad7da097ea03aa28d0614164cd25fafeb1383dbc15047e34c8050f6f67"]);
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

Acknowledgements

• License to Encrypt: The “Gentlemen” Make Their Move. Cybereason (accessed 2026-02-06)
• Unmasking The Gentlemen Ransomware: Tactics, Techniques, and Procedures Revealed. TrendMicro (accessed 2026-02-06)

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 The Gentlemen ransomware: Dissecting a self-propagating Go encryptor appeared first on Microsoft Security Blog.

Fox Tempest is a financially motivated threat actor that operates a malware-signing-as-a-service (MSaaS)  used by other cybercriminals to more effectively distribute malicious code, including ransomware. The threat actor abuses Microsoft Artifact Signing to generate short-lived, fraudulent code-signing certificates to appear legitimately signed, allowing malware to evade security controls.

Fox Tempest has created over a thousand certificates and established hundreds of Azure tenants and subscriptions to support its operations. Microsoft has revoked over one thousand code signing certificates attributed to Fox Tempest. In May 2026, Microsoft’s Digital Crimes Unit (DCU), with support from industry partner Resecurity, disrupted Fox Tempest’s MSaaS offering, targeting the infrastructure and access model that enables its broader criminal use.

Microsoft Threat Intelligence observed Fox Tempest’s operations enabling the deployment of Rhysida ransomware by threat actors such as Vanilla Tempest, as well as the distribution of other malware families including Oyster, Lumma Stealer, and Vidar. The consistency, scale, and downstream impact of the resulting attack activity demonstrate that Fox Tempest is a vital operator within the broader cybercrime ecosystem.

In this blog, we examine how Fox Tempest’s MSaaS operation functioned and how it enabled the delivery of trusted, signed malware across the cybercrime ecosystem. We also provide Microsoft Defender detections, indicators of compromise (IOCs), and mitigation recommendations to help organizations identify and disrupt similar activity.

Fox Tempest’s role and impact

Fox Tempest doesn’t directly target victims but instead provides supporting services that enable ransomware operations by other threat actors. Microsoft Threat Intelligence has tracked Fox Tempest since September 2025. Microsoft Threat Intelligence has linked the actor to various ransomware groups including Vanilla Tempest, Storm-0501, Storm-2561, and Storm-0249, who have all leveraged Fox Tempest-signed malware in active intrusions. Malware delivery in these attacks have included use of legitimate purchased advertisements, malvertising, and SEO poisoning.

Cryptocurrency analysis associated with Fox Tempest has identified clear links tying the actor to ransomware affiliates responsible for delivering several prominent ransomware families, including INC, Qilin, Akira, and others, with observed proceeds in the millions. Based on the scale of the MSaaS offering, Microsoft Threat Intelligence assesses that Fox Tempest is a well-resourced group handling infrastructure creation, customer relations, and financial transactions.

The downstream impact of these operations has resulted in attacks against a broad range of industry sectors, including healthcare, education, government, and financial services, impacting organizations globally including, but not limited to the United States, France, India, and China.

Fox Tempest’s malware signing as a service infrastructure

Fox Tempest’s MSaaS capability was available through the website signspace[.]cloud, a now defunct service that was disrupted by DCU, which enabled other threat actors to fraudulently obtain short-lived Microsoft-issued certificates that were valid for only 72 hours, obtained through Artifact Signing (previously named Azure Trusted Signing). This use of short-life certificates from a trusted source allowed malware and ransomware to masquerade as legitimate software (like AnyDesk, Teams, Putty, and Webex) to bypass security controls, significantly increasing the likelihood of execution and successful delivery. Fox Tempest offered this MSaaS capability to the ransomware ecosystem since at least May 2025.

To obtain legitimate signed certificates through Artifact Signing, the requestor must pass detailed identify validation processes in keeping with industry standard verifiable credentials (VC), which suggests the threat actor very likely used stolen identities based in the United States and Canada to masquerade as a legitimate entity and obtain the necessary digital credentials for signing. The SignSpace website was built on Artifact Signing and enabled secure file signing through an admin panel and user page, leveraging Azure subscriptions, certificates, and a structured database for managing users and files. A GitHub repository, called code‑signing‑service, included configuration files and technical details that directly linked it to the infrastructure behind signspace[.]cloud.

The signspace[.]cloud service has two unique modeling groupings: the admin and the customers. The admin is responsible for maintaining the tooling, account creation, and infrastructure, while the customers provide files to be fraudulently code signed. Customers who accessed the service could upload malicious files to be signed using Fox Tempest-controlled certificates.

Below are examples of the signspace[.]cloud portal as seen by Fox Tempest’s customers:

In February 2026, Microsoft Threat Intelligence observed a notable shift in Fox Tempest’s operational infrastructure. Fox Tempest transitioned to providing customers with pre-configured virtual machines (VMs) hosted on US-based virtual private server provider Cloudzy’s infrastructure, allowing threat actors to upload their malicious files directly to Fox Tempest‑controlled environments and receive signed binaries in return. This infrastructure evolution reduced friction for customers, improved operational security for Fox Tempest, and further streamlined the delivery of malicious but trusted, signed malware at scale. Microsoft’s Digital Crimes Unit (DCU) disrupted this infrastructure and continues to partner with Cloudzy to identify and disrupt related infrastructure.

Below is an example of the Fox Tempest-provided VM environment as seen by customers:

Inside the VM, Fox Tempest provided files that are used to sign code:

• The first file, metadata.json, was a configuration file that pointed to an Azure‑hosted endpoint which also included the signing account and certificate profile.
• The second file, test.js, is an example of a file provided by Fox Tempest that had been digitally signed to demonstrate their signing capabilities to customers.
• The third file, PS code sample.txt, contains the PowerShell script they used to sign customer‑submitted files using certificates under Fox Tempest control.

Threat actors using Fox Tempest’s MSaaS offering paid thousands of dollars to get their malicious code signed, as shown below with the Google Form detailing the service’s pricing model. Actors filled out the form before being added to a queue to submit payment and gain access to a VM. The form (written in both English and Russian) asks the user to choose a selected plan from a price list of $5000 USD, $7500 USD, or $9000 USD, with a mention that higher paying plans receive priority in the queue sequence.

Fox Tempest engaged directly with customers using a Telegram channel, EV Certs for Sale by SamCodeSign under the user account arbadakarba2000. All signing activity occurred using a Fox Tempest-provided email address associated with a very small number of IP addresses.

Case study: Fox Tempest enables Vanilla Tempest attacks

Vanilla Tempest began using Fox Tempest’s MSaaS service as early as June 2025. Through this service, Vanilla Tempest uploaded malicious payloads such as trojanized Microsoft Teams installers, which Fox Tempest would fraudulently signed to appear legitimate. Vanilla Tempest would then distribute these signed binaries through legitimately purchased advertisements that redirected users searching for Microsoft Teams to attacker‑controlled advertisements and fraudulent download pages.

Victims were presented with a malicious MSTeamsSetup.exe in place of the legitimate client, reflecting a broader pattern of Vanilla Tempest frequently abusing trusted software brands to lure victims and establish initial access. Execution of the counterfeit installer resulted in the deployment of the Oyster backdoor (also known as Broomstick), a modular, multistage implant that establishes persistent remote access, initiates command‑and‑control (C2) communications, collects host‑level information, and enables the delivery of additional payloads. By masquerading as a widely deployed enterprise collaboration tool hiding behind a fraudulently signed binary, Vanilla Tempest’s Oyster payload was likely able to evade casual detection and blend into normal enterprise activity. In some observed cases, Vanilla Tempest also deployed Rhysida ransomware within victim environments using the same process.

Defending against Fox Tempest-enabled attacks

To defend against Fox Tempest tactics, techniques, and procedures (TTPs) and similar activity, Microsoft recommends the following mitigation measures:

• Read the human-operated ransomware threat overview for advice on developing a holistic security posture to prevent ransomware, including credential hygiene and hardening recommendations.
• 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.
• Turn on Safe Links and Safe Attachments in Microsoft Defender for Office 365.
• 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 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.
• Microsoft Defender XDR customers can turn on attack surface reduction rules to prevent several of the infection vectors of this threat. These rules, which can be configured by any user, offer significant hardening against targeted attacks. In observed attacks, Microsoft customers who had the following rules turned on could mitigate the attack in the initial stages and prevent hands-on-keyboard activity:
  • 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.

Microsoft Defender XDR threat analytics

• Actor profile: Fox Tempest
• Actor profile: Vanilla Tempest
• Threat Overview profile: Human-operated ransomware
• Activity profile: Vanilla Tempest leverages fake Microsoft Teams setup to deliver Oyster backdoor

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.

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 Threat Intelligence podcast.

The post Exposing Fox Tempest: A malware-signing service operation 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.

Microsoft Incident Response – Detection and Response Team (DART) researchers observed an emerging, financially motivated threat actor that Microsoft tracks as Storm-2755 conducting payroll pirate attacks targeting Canadian users. In this campaign, Storm-2755 compromised user accounts to gain unauthorized access to employee profiles and divert salary payments to attacker-controlled accounts, resulting in direct financial loss for affected individuals and organizations. 

While similar payroll pirate attacks have been observed in other malicious campaigns, Storm-2755’s campaign is distinct in both its delivery and targeting. Rather than focusing on a specific industry or organization, the actor relied exclusively on geographic targeting of Canadian users and used malvertising and search engine optimization (SEO) poisoning on industry agnostic search terms to identify victims. The campaign also leveraged adversary‑in‑the‑middle (AiTM) techniques to hijack authenticated sessions, allowing the threat actor to bypass multifactor authentication (MFA) and blend into legitimate user activity.

Microsoft has been actively engaged with affected organizations and taken multiple disruption efforts to help prevent further compromise, including tenant takedown. Microsoft continues to engage affected customers, providing visibility by sharing observed tactics, techniques, and procedures (TTPs) while supporting mitigation efforts.

In this blog, we present our analysis of Storm-2755’s recent campaign and the TTPs employed across each stage of the attack chain. To support proactive mitigations against this campaign and similar activity, we also provide comprehensive guidance for investigation and remediation, including recommendations such as implementing phishing-resistant MFA to help block these attacks and protect user accounts.

Storm-2755’s attack chain

Analysis of this activity reveals a financially motivated campaign built around session hijacking and abuse of legitimate enterprise workflows. Storm-2755 combined initial credential and token theft with session persistence and targeted discovery to identify payroll and human resources (HR) processes within affected Canadian organizations. By operating through authenticated user sessions and blending into normal business activity, the threat actor was able to minimize detection while pursuing direct financial gain.

The sections below examine each stage of the attack chain—from initial access through impact—detailing the techniques observed.

Initial access

In the observed campaign, Storm-2755 likely gained initial access through SEO poisoning or malvertising that positioned the actor-controlled domain, bluegraintours[.]com, at the top of search results for generic queries like “Office 365” or common misspellings like “Office 265”. Based on data received by DART, unsuspecting users who clicked these links were directed to a malicious Microsoft 365 sign-in page designed to mimic the legitimate experience, resulting in token and credential theft when users entered their credentials.

Once a user entered their credentials into the malicious page, sign-in logs reveal that the victim recorded a 50199 sign-in interrupt error immediately before Storm-2755 successfully compromised the account. When the session shifts from legitimate user activity to threat actor control, the user-agent for the session changes to Axios; typically, version 1.7.9, however the session ID will remain consistent, indicating that the token has been replayed.

This activity aligns with an AiTM attack—an evolution of traditional credential phishing techniques—in which threat actors insert malicious infrastructure between the victim and a legitimate authentication service. Rather than harvesting only usernames and passwords, AiTM frameworks proxy the entire authentication flow in real time, enabling the capture session cookies and OAuth access tokens issued upon successful authentication. Due to these tokens representing a fully authenticated session, threat actors can reuse them to gain access to Microsoft services without being prompted for credentials or MFA, effectively bypassing legacy MFA protections not designed to be phishing-resistant; phishing-resistant methods such as FIDO2/WebAuthN are designed to mitigate this risk.

While Axios is not a malicious tool, this attack path seems to take advantage of known vulnerabilities of the open-source software, namely CVE-2025-27152, which can lead to server-side request forgeries.

Persistence

Storm-2755 leveraged version 1.7.9 of the Axios HTTP client to relay authentication tokens to the customer infrastructure which effectively bypassed non-phishing resistant MFA and preserved access without requiring repeated sign ins. This replay flow allowed Storm-2755 to maintain these active sessions and proxy legitimate user actions, effectively executing an AiTM attack.

Microsoft consistently observed non-interactive sign ins to the OfficeHome application associated with the Axios user-agent occurring approximately every 30 minutes until remediation actions revoked active session tokens, which allowed Storm-2755 to maintain these active sessions and proxy legitimate user actions without detection.

After around 30 days, we observed that the stolen tokens would then become inactive when Storm-2755 did not continue maintaining persistence within the environment. The refresh token became unusable due to expiration, rotation, or policy enforcement, preventing the issuance of new access tokens after the session token had expired. The compromised sessions primarily featured non-interactive sign ins to OfficeHome and recorded sign ins to Microsoft Outlook, My Sign-Ins, and My Profile. For a more limited set of identities, password and MFA changes were observed to maintain more durable persistence within the environment after the token had expired.

Discovery

Once user accounts have been successfully comprised, discovery actions begin to identify internal processes and mailboxes associated with payroll and HR. Specific intranet searches during compromised sessions focused on keywords such as “payroll”, “HR”, “human”, “resources”, ”support”, “info”, “finance”, ”account”, and “admin” across several customer environments.

Email subject lines were also consistent across all compromised users; “Question about direct deposit”, with the goal of socially engineering HR or finance staff members into performing manual changes to payroll instructions on behalf of Storm-2755, removing the need for further hands-on-keyboard activity.

While similar recent campaigns have observed email content being tailored to the institution and incorporating elements to reference senior leadership contacts, Storm-2755’s attack seems to be focused on compromising employees in Canada more broadly. 

Where Storm-2755 was unable to successfully achieve changes to payroll information through user impersonation and social engineering of HR personnel, we observed a pivot to direct interaction and manual manipulation of HR software-as-a-service (SaaS) programs such as Workday. While the example below illustrates the attack flow as observed in Workday environments, it’s important to note that similar techniques could be leveraged against any payroll provider or SaaS platform.

Defense evasion

Following discovery activities, but prior to email impersonation, Storm-2755 created email inbox rules to move emails containing the keywords “direct deposit” or “bank” to the compromised user’s conversation history and prevent further rule processing. This rule ensured that the victim would not see the email correspondence from their HR team regarding the malicious request for bank account changes as this correspondence was immediately moved to a hidden folder.

This technique was highly effective in disguising the account compromise to the end user, allowing the threat actor to discreetly continue actions to redirect payments to an actor-controlled bank account undisturbed.

To further avoid potential detection by the account owner, Storm-2755 renewed the stolen session around 5:00 AM in the user’s time zone, operating outside normal business hours to reduce the chance of a legitimate reauthentication that would invalidate their access.

Impact

The compromise led to a direct financial loss for one user. In this case, Storm-2755 was able to gain access to the user’s account and created inbox rules to prevent emails that contained “direct deposit” or “bank”, effectively suppressing alerts from HR. Using the stolen session, the threat actor would email HR to request changes to direct deposit details, HR would then send back the instructions on how to change it. This led Storm-2755 to manually sign in to Workday as the victim to update banking information, resulting in a payroll check being redirected to an attacker-controlled bank account.

Defending against Storm-2755 and AiTM campaigns

Organizations should mitigate AiTM attacks by revoking compromised tokens and sessions immediately, removing malicious inbox rules, and resetting credentials and MFA methods for affected accounts.

To harden defenses, enforce device compliance enforcement through Conditional Access policies, implement phishing-resistant MFA, and block legacy authentication protocols. Organizations storing data in a security information and event management (SIEM) solution enable Defenders to quickly establish a clearer baseline of regular and irregular activity to distinguish compromised sessions from legitimate activity.

Enable Microsoft Defender to automatically disrupt attacks, revoke tokens in real time, monitor for anomalous user-agents like Axios, and audit OAuth applications to prevent persistence. Finally, run phishing simulation campaigns to improve user awareness and reduce susceptibility to credential theft.

To proactively protect against this attack pattern and similar patterns of compromise Microsoft recommends:

1. Implement phishing resistant MFA where possible: Traditional MFA methods such as SMS codes, email-based one-time passwords (OTPs), and push notifications are becoming less effective against today’s attackers. Sophisticated phishing campaigns have demonstrated that second factors can be intercepted or spoofed.
2. Use Conditional Access Policies to configure adaptive session lifetime policies: Session lifetime and persistence can be managed in several different ways based on organizational needs. These policies are designed to restrict extended session lifetime by prompting the user for reauthentication. This reauthentication might involve only one first factor, such as password, FIDO2 security keys, or passwordless Microsoft Authenticator, or it might require MFA.
3. Leverage continuous access evaluation (CAE): For supporting applications to ensure access tokens are re-evaluated in near real time when risk conditions change. CAE reduces the effectiveness of stolen access and fresh tokens by allowing access to be promptly revoked following user risk changes, credential resets, or policy enforcement events limiting attacker persistence.
   1. Consider Global Secure Access (GSA) as a complementary network control path: Microsoft’s Global Secure Access (Entra Internet Access + Entra Private Access) extends Zero Trust enforcement to the network layer, providing an identity-aware secure network edge that strengthens CAE signal fidelity, enables Compliant Network Conditional Access conditions, and ensures consistent policy enforcement across identity, device, and network—forming a complete third managed path alongside identity and device controls.
4. Create alerting of suspicious inbox-rule creation: This alerting is essential to quickly identify and triage evidence of business email compromise (BEC) and phishing campaigns. This playbook helps defenders investigate any incident related to suspicious inbox manipulation rules configured by threat actors and take recommended actions to remediate the attack and protect networks.
5. Secure organizational resources through Microsoft Intune compliance policies: When integrated with Microsoft Entra Conditional Access policies, Intune offers an added layer of protection based on a devices current compliance status to help ensure that only devices that are compliant are permitted to access corporate resources.

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. 

Microsoft Defender XDR threat analytics

• Activity Profile: Storm-2755 “payroll pirate attacks” targeting Canadian employees
• Activity Profile: Targeted “payroll pirate” attacks affecting US universities
• Actor Profile: Storm-2657

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 queries to find related activity in their networks:

Review inbox rules created to hide or delete incoming emails from Workday

Results of the following query may indicate an attacker is trying to delete evidence of Workday activity.

CloudAppEvents 
| where Timestamp >= ago(1d)
| where Application == "Microsoft Exchange Online" and ActionType in ("New-InboxRule", "Set-InboxRule")  
| extend Parameters = RawEventData.Parameters // extract inbox rule parameters
| where Parameters has "From" and Parameters has "@myworkday.com" // filter for inbox rule with From field and @MyWorkday.com in the parameters
| where Parameters has "DeleteMessage" or Parameters has ("MoveToFolder") // email deletion or move to folder (hiding)
| mv-apply Parameters on (where Parameters.Name == "From"
| extend RuleFrom = tostring(Parameters.Value))
| mv-apply Parameters on (where Parameters.Name == "Name" 
| extend RuleName = tostring(Parameters.Value))

Review updates to payment election or bank account information in Workday

The following query surfaces changes to payment accounts in Workday.

CloudAppEvents 
| where Timestamp >= ago(1d)
| where Application == "Workday"
| where ActionType == "Change My Account" or ActionType == "Manage Payment Elections"
| extend Descriptor = tostring(RawEventData.target.descriptor)

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.

Malicious inbox rule

The query includes filters specific to inbox rule creation, operations for messages with DeleteMessage, and suspicious keywords.

let Keywords = dynamic(["direct deposit", “hr”, “bank”]);
OfficeActivity
| where OfficeWorkload =~ "Exchange" 
| where Operation =~ "New-InboxRule" and (ResultStatus =~ "True" or ResultStatus =~ "Succeeded")
| where Parameters has "Deleted Items" or Parameters has "Junk Email"  or Parameters has "DeleteMessage"
| extend Events=todynamic(Parameters)
| parse Events  with * "SubjectContainsWords" SubjectContainsWords '}'*
| parse Events  with * "BodyContainsWords" BodyContainsWords '}'*
| parse Events  with * "SubjectOrBodyContainsWords" SubjectOrBodyContainsWords '}'*
| where SubjectContainsWords has_any (Keywords)
 or BodyContainsWords has_any (Keywords)
 or SubjectOrBodyContainsWords has_any (Keywords)
| extend ClientIPAddress = case( ClientIP has ".", tostring(split(ClientIP,":")[0]), ClientIP has "[", tostring(trim_start(@'[[]',tostring(split(ClientIP,"]")[0]))), ClientIP )
| extend Keyword = iff(isnotempty(SubjectContainsWords), SubjectContainsWords, (iff(isnotempty(BodyContainsWords),BodyContainsWords,SubjectOrBodyContainsWords )))
| extend RuleDetail = case(OfficeObjectId contains '/' , tostring(split(OfficeObjectId, '/')[-1]) , tostring(split(OfficeObjectId, '\\')[-1]))
| summarize count(), StartTimeUtc = min(TimeGenerated), EndTimeUtc = max(TimeGenerated) by  Operation, UserId, ClientIPAddress, ResultStatus, Keyword, OriginatingServer, OfficeObjectId, RuleDetail
| extend AccountName = tostring(split(UserId, "@")[0]), AccountUPNSuffix = tostring(split(UserId, "@")[1])
| extend OriginatingServerName = tostring(split(OriginatingServer, " ")[0])

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_domains = dynamic(["http://bluegraintours.com"]);
_Im_NetworkSession(starttime=todatetime(ago(lookback)), endtime=now())
| where DstDomain has_any (ioc_domains)
| summarize imNWS_mintime=min(TimeGenerated), imNWS_maxtime=max(TimeGenerated),
  EventCount=count() by SrcIpAddr, DstIpAddr, DstDomain, 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(["http://bluegraintours.com"]);
_Im_WebSession (url_has_any = ioc_domains)

Indicators of compromise

In observed compromises associated with hxxp://bluegraintours[.]com, sign-in logs consistently showed a distinctive authentication pattern. This pattern included multiple failed sign‑in attempts with various causes followed by a failure citing Microsoft Entra error code 50199, immediately preceding a successful authentication. Upon successful sign in, the user-agent shifted to Axios, while the session ID remained unchanged—an indication that an authenticated session token had been replayed rather than a new session established. This combination of error sequencing, user‑agent transition, and session continuity is characteristic of AiTM activity and should be evaluated together when assessing potential compromise tied to this domain

Acknowledgments

• https://pushsecurity.com/blog/phishing-with-active-directory-federation-services/ – Push Security offers a deep technical analysis of an Active Directory Federation Services (ADFS)‑enabled phishing attack, demonstrating how the bluegraintours[.]com ADFS deployment was exploited to intercept authentication tokens.

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 Investigating Storm-2755: “Payroll pirate” attacks targeting Canadian employees 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.

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 Storm-1175 focuses gaze on vulnerable web-facing assets in high-tempo Medusa ransomware operations 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

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

In a campaign observed in the first half of 2025, we identified the actor specifically targeting Workday profiles. However, it’s important to note that any SaaS systems storing HR or payment and bank account information could be easily targeted with the same technique. These attacks don’t represent any vulnerability in the Workday platform or products, but rather financially motivated threat actors using sophisticated social engineering tactics and taking advantage of the complete lack of multifactor authentication (MFA) or lack of phishing-resistant MFA to compromise accounts. Workday has published guidance for their customers in their community, and we thank Workday for their partnership and support in helping to raise awareness on how to mitigate this threat.

Microsoft has identified and reached out to some of the affected customers to share tactics, techniques, and procedures (TTPs) and assist with mitigation efforts. In this blog, we present our analysis of Storm-2657’s recent campaign and the TTPs employed in attacks. We offer comprehensive guidance for investigation and remediation, including implementing phishing-resistant MFA to help block these attacks and protect user accounts. Additionally, we provide comprehensive detections and hunting queries to enable organizations to defend against this attack and disrupt threat actor activity.

Analysis of the campaign

In the observed campaign, the threat actor gained initial access through phishing emails crafted to steal MFA codes using adversary-in-the-middle (AITM) phishing links. After obtaining MFA codes, the threat actor was able to gain unauthorized access to the victims’ Exchange Online and later hijacked and modified their Workday profiles.

After gaining access to compromised employee accounts, the threat actor created inbox rules to delete incoming warning notification emails from Workday, hiding the actor’s changes to the HR profiles. Storm-2657 then stealthily moved on to modify the employee’s salary payment configuration in their HR profile, thereby redirecting future salary payments to accounts under the actor’s control, causing financial harm to their victims. While the following example illustrates the attack flow as observed in Workday environments, it’s important to note that similar techniques could be leveraged against any payroll provider or SaaS platform.

Initial access

The threat actor used realistic phishing emails, targeting accounts at multiple universities, to harvest credentials. Since March 2025, we’ve observed 11 successfully compromised accounts at three universities that were used to send phishing emails to nearly 6,000 email accounts across 25 universities.

Some phishing emails contained Google Docs links, making detection challenging, as these are common in academic environments. In multiple instances, compromised accounts did not have MFA enabled. In other cases, users were tricked into disclosing MFA codes via AiTM phishing links distributed through email. Following the compromise of email accounts and the payroll modifications in Workday, the threat actor leveraged newly accessed accounts to distribute further phishing emails, both within the organization and externally to other universities.

The threat actor used several themes in their phishing emails. One common theme involved messages about illnesses or outbreaks on campus, suggesting that recipients might have been exposed. These emails included a link to a Google Docs page that then redirected to an attacker-controlled domain.

Some examples of the email subject lines are:

• COVID-Like Case Reported — Check Your Contact Status
• Confirmed Case of Communicable Illness
• Confirmed Illness

In one instance, a phishing email was sent to 500 individuals within a single organization, encouraging targets to check their illness exposure status. Approximately 10% of recipients reported the email as a suspected phishing attempt.

The second theme involved reports of misconduct or actions by individuals within the faculty, with the goal of tricking recipients into checking the link to determine if they are mentioned in the report.

Some examples of the subject lines are:

• Faculty Compliance Notice – Classroom Misconduct Report
• Review Acknowledgment Requested – Faculty Misconduct Mention

The most recently identified theme involved phishing emails impersonating a legitimate university or an entity associated with a university. To make their messages appear convincing, Storm-2657 tailored the content based on the recipient’s institution. Examples included messages that appear to be official communications from the university president, information about compensation and benefits, or documents shared by HR with recipients. Most of the time the subject line contained either the university name or the university’s president name, further enhancing the email’s legitimacy and appeal to the intended target.

Some examples of the subject lines are:

• Please find the document forwarded by the HR Department for your review
• [UNIVERSITY NAME] 2025 Compensation and Benefits Update
• A document authored by [UNIVERSITY PRESIDENT NAME] has been shared for your examination.

Defense evasion

Following account compromise, the threat actor created a generic inbox rule to hide or delete any incoming warning notification emails from the organization’s Workday email service. This rule ensured that the victim would not see the notification emails from Workday about the payroll changes made by the threat actor, thereby minimizing the likelihood of detection by the victim. In some cases, the threat actor might have attempted to stay under the radar and hide their traces from potential reviews by creating rule names solely using special characters or non-alphabetic symbols like “….” or “\’\’\’\’”.

Persistence

In observed cases, the threat actor established persistence by enrolling their own phone numbers as MFA devices for victim accounts, either through Workday profiles or Duo MFA settings. By doing so, they bypassed the need for further MFA approval from the legitimate user, enabling continued access without detection.

Impact

The threat actor subsequently accessed Workday through single sign-on (SSO) and changed the victim’s payroll/bank account information.

With the Workday connector enabled in Microsoft Defender for Cloud Apps, analysts can efficiently investigate and identify attack traces by examining Workday logs and Defender-recorded actions. There are multiple indicators available to help pinpoint these changes. For example, one indicator from the Workday logs generated by such threat actor changes is an event called “Change My Account” or “Manage Payment Elections”, depending on the type of modifications performed in the Workday application audit logs:

These payroll modifications are frequently accompanied by notification emails informing users that payroll or bank details have been changed or updated. As previously discussed, threat actors might attempt to eliminate these messages either through manual deletion or by establishing inbox rules. These deletions can be identified by monitoring Exchange Online events such as SoftDelete, HardDelete, and MoveToDeletedItems. The subjects of these emails typically contain the following terms:

• “Payment Elections”
• “Payment Election”
• “Direct Deposit”

Microsoft Defender for Cloud Apps correlates signals from both Microsoft Exchange Online (first-party SaaS application) and Workday (third-party SaaS application), enabling thorough detection of suspicious activities that span multiple systems, as seen in the image below. Only by correlating first party and third-party signals is it possible to detect this activity spawning across multiple systems.

Mitigation and protection guidance

Mitigating threats from actors like Storm-2657 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 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. Below 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.

Microsoft Defender XDR detections

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.

Hunting queries

Microsoft Defender XDR

The Microsoft Defender for Cloud Apps connector for Workday includes write events such as Workday account updates, payroll configuration changes, etc. These are available in the Defender XDR CloudAppEvents hunting tables for further investigation. Important events related to this attack include but are not limited:

• Add iOS Device
• Add Android Device
• Change My Account
• Manage Payment Elections

Install the Microsoft Defender for Cloud Apps connector for Workday to take advantage of these logging, investigation, and detection capabilities.

Review inbox rules created to hide or delete incoming emails from Workday

Results of the following query may indicate an attacker is trying to delete evidence of Workday activity.

CloudAppEvents 
| where Timestamp >= ago(1d)
| where Application == "Microsoft Exchange Online" and ActionType in ("New-InboxRule", "Set-InboxRule")  
| extend Parameters = RawEventData.Parameters // extract inbox rule parameters
| where Parameters has "From" and Parameters has "@myworkday.com" // filter for inbox rule with From field and @MyWorkday.com in the parameters
| where Parameters has "DeleteMessage" or Parameters has ("MoveToFolder") // email deletion or move to folder (hiding)
| mv-apply Parameters on (where Parameters.Name == "From"
| extend RuleFrom = tostring(Parameters.Value))
| mv-apply Parameters on (where Parameters.Name == "Name" 
| extend RuleName = tostring(Parameters.Value))

Review updates to payment election or bank account information in Workday

The following query surfaces changes to payment accounts in Workday.

CloudAppEvents 
| where Timestamp >= ago(1d)
| where Application == "Workday"
| where ActionType == "Change My Account" or ActionType == "Manage Payment Elections"
| extend Descriptor = tostring(RawEventData.target.descriptor)

Review device additions in Workday

The following query looks for recent device additions in Workday. If the device is unknown, it may indicate an attacker joined their own device for persistence and MFA evasion.

CloudAppEvents 
| where Timestamp >= ago(1d)
| where Application == "Workday"
| where ActionType has "Add iOS Device" or ActionType has "Add Android Device"
| extend Descriptor = tostring(RawEventData.target.descriptor) // will contain information of the device

Hunt for bulk suspicious emails from .edu sender

The following query identifies email from .edu senders sent to a high number of users.

EmailEvents
| where Timestamp >= ago(7d)
| where SenderFromDomain has "edu" or SenderMailFromDomain has "edu"
| where EmailDirection == "Inbound"
| summarize dcount(RecipientEmailAddress), dcount(InternetMessageId), make_set(InternetMessageId), dcount(Subject), dcount(NetworkMessageId), take_any(NetworkMessageId) by bin(Timestamp,1d), SenderFromAddress
| where dcount_RecipientEmailAddress > 100 // number can be adjusted, usually the sender will send emails to around 100-600 recipients per day

Hunt for phishing URL from identified .edu phish sender

If a suspicious .edu sender has been identified, use the following query to surface email events from this sender address.

EmailEvents
| where Timestamp >= ago(1d)
| where SenderFromAddress == ""
| where EmailDirection == "Inbound"
| project NetworkMessageId, Subject, InternetMessageId
| join EmailUrlInfo on NetworkMessageId
| where Timestamp >= ago(1d)
| project Url, NetworkMessageId, Subject, InternetMessageId

Hunt for user clicks to suspicious URL from the identified .edu phish sender (previous query)

If a suspicious .edu sender has been identified, use the below query to surface user clicks that may indicate a malicious link was accessed.

EmailEvents
| where Timestamp >= ago(1d)
| where SenderFromAddress == ""
| where EmailDirection == "Inbound"
| project NetworkMessageId, Subject, InternetMessageId
| join UrlClickEvents on NetworkMessageId
| where Timestamp >= ago(1d)
| project AccountUpn, Subject, InternetMessageId, DetectionMethods, ThreatTypes, IsClickedThrough // these users very likely fall into the phishing attack

Microsoft Sentinel

Install the Workday connector for Microsoft Sentinel. Microsoft Sentinel has a range of detection and threat hunting content that customers can use to detect the post exploitation activity detailed in this blog.

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.

Malicious inbox rule

The query includes filters specific to inbox rule creation, operations for messages with ‘DeleteMessage’, and suspicious keywords.

let Keywords = dynamic(["helpdesk", " alert", " suspicious", "fake", "malicious", "phishing", "spam", "do not click", "do not open", "hijacked", "Fatal"]);
OfficeActivity
| where OfficeWorkload =~ "Exchange" 
| where Operation =~ "New-InboxRule" and (ResultStatus =~ "True" or ResultStatus =~ "Succeeded")
| where Parameters has "Deleted Items" or Parameters has "Junk Email"  or Parameters has "DeleteMessage"
| extend Events=todynamic(Parameters)
| parse Events  with * "SubjectContainsWords" SubjectContainsWords '}'*
| parse Events  with * "BodyContainsWords" BodyContainsWords '}'*
| parse Events  with * "SubjectOrBodyContainsWords" SubjectOrBodyContainsWords '}'*
| where SubjectContainsWords has_any (Keywords)
 or BodyContainsWords has_any (Keywords)
 or SubjectOrBodyContainsWords has_any (Keywords)
| extend ClientIPAddress = case( ClientIP has ".", tostring(split(ClientIP,":")[0]), ClientIP has "[", tostring(trim_start(@'[[]',tostring(split(ClientIP,"]")[0]))), ClientIP )
| extend Keyword = iff(isnotempty(SubjectContainsWords), SubjectContainsWords, (iff(isnotempty(BodyContainsWords),BodyContainsWords,SubjectOrBodyContainsWords )))
| extend RuleDetail = case(OfficeObjectId contains '/' , tostring(split(OfficeObjectId, '/')[-1]) , tostring(split(OfficeObjectId, '\\')[-1]))
| summarize count(), StartTimeUtc = min(TimeGenerated), EndTimeUtc = max(TimeGenerated) by  Operation, UserId, ClientIPAddress, ResultStatus, Keyword, OriginatingServer, OfficeObjectId, RuleDetail
| extend AccountName = tostring(split(UserId, "@")[0]), AccountUPNSuffix = tostring(split(UserId, "@")[1])
| extend OriginatingServerName = tostring(split(OriginatingServer, " ")[0])

Risky sign-in with new MFA method

This query identifies scenarios of risky sign-ins tied to new MFA methods being added.

let mfaMethodAdded=CloudAppEvents
    | where ActionType =~ "Update user." 
    | where RawEventData has "StrongAuthenticationPhoneAppDetail"
    | where isnotempty(RawEventData.ObjectId) and isnotempty(RawEventData.Target[1].ID)
    | extend AccountUpn = tostring(RawEventData.ObjectId)
    | extend AccountObjectId = tostring(RawEventData.Target[1].ID)
    | project MfaAddedTimestamp=Timestamp,AccountUpn,AccountObjectId;
    let usersWithNewMFAMethod=mfaMethodAdded
    | distinct AccountObjectId;
    let hasusersWithNewMFAMethod = isnotempty(toscalar(usersWithNewMFAMethod));
    let riskySignins=AADSignInEventsBeta
    | where hasusersWithNewMFAMethod
    | where AccountObjectId in (usersWithNewMFAMethod)
    | where RiskLevelDuringSignIn in ("50","100") //Medium and High sign-in risk level.
    | where Application in ("Office 365 Exchange Online", "OfficeHome")
    | where isnotempty(SessionId)
    | project SignInTimestamp=Timestamp, Application, SessionId, AccountObjectId, IPAddress,RiskLevelDuringSignIn
    | summarize SignInTimestamp=argmin(SignInTimestamp,*) by Application,SessionId, AccountObjectId, IPAddress,RiskLevelDuringSignIn;
    mfaMethodAdded
    | join riskySignins on AccountObjectId
    | where MfaAddedTimestamp - SignInTimestamp < 6h //Time delta between risky sign-in and device registration less than 6h
    | project-away AccountObjectId1

Microsoft Security Copilot

Security Copilot customers can use the standalone experience to create their own prompts or run the following prebuilt promptbooks to automate incident response or investigation tasks related to this threat:

• Incident investigation
• Microsoft User analysis
• Threat actor profile
• Threat Intelligence 360 report based on MDTI article
• Vulnerability impact assessment

Note that some promptbooks require access to plugins for Microsoft products such as Microsoft Defender XDR or Microsoft Sentinel.

Acknowledgments

We would like to thank Workday for their collaboration and assistance in responding to this threat.

Workday customers can refer to the guidance published by Workday on their community: https://community.workday.com/alerts/customer/1229867.

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 Investigating targeted “payroll pirate” attacks affecting US universities appeared first on Microsoft Security Blog.

North Korea has deployed thousands of remote IT workers to assume jobs in software and web development as part of a revenue generation scheme for the North Korean government. These highly skilled workers are most often located in North Korea, China, and Russia, and use tools such as virtual private networks (VPNs) and remote monitoring and management (RMM) tools together with witting accomplices to conceal their locations and identities.

Historically, North Korea’s fraudulent remote worker scheme has focused on targeting United States (US) companies in the technology, critical manufacturing, and transportation sectors. However, we’ve observed North Korean remote workers evolving to broaden their scope to target various industries globally that offer technology-related roles. Since 2020, the US government and cybersecurity community have identified thousands of North Korean workers infiltrating companies across various industries.

Organizations can protect themselves from this threat by implementing stricter pre-employment vetting measures and creating policies to block unapproved IT management tools. For example, when evaluating potential employees, employers and recruiters should ensure that the candidates’ social media and professional accounts are unique and verify their contact information and digital footprint. Organizations should also be particularly cautious with staffing company employees, check for consistency in resumes, and use video calls to confirm a worker’s identity.

Microsoft Threat Intelligence tracks North Korean IT remote worker activity as Jasper Sleet (formerly known as Storm-0287). We also track several other North Korean activity clusters that pursue fraudulent employment using similar techniques and tools, including Storm-1877 and Moonstone Sleet. To disrupt this activity and protect our customers, we’ve suspended 3,000 known Microsoft consumer accounts (Outlook/Hotmail) created by North Korean IT workers. We have also implemented several detections to alert our customers of this activity through Microsoft Entra ID Protection and Microsoft Defender XDR as noted at the end of this blog. As with any observed nation-state threat actor activity, Microsoft has directly notified targeted or compromised customers, providing them with important information needed to secure their environments. As we continue to observe more attempts by threat actors to leverage AI, not only do we report on them, but we also have principles in place to take action against them.

This blog provides additional information on the North Korean remote IT worker operations we published previously, including Jasper Sleet’s usual TTPs to secure employment, such as using fraudulent identities and facilitators. We also provide recent observations regarding their use of AI tools. Finally, we share detailed guidance on how to investigate, monitor, and remediate possible North Korean remote IT worker activity, as well as detections and hunting capabilities to surface this threat.

From North Korea to the world: The remote IT workforce

Since at least early 2020, Microsoft has tracked a global operation conducted by North Korea in which skilled IT workers apply for remote job opportunities to generate revenue and support state interests. These workers present themselves as foreign (non-North Korean) or domestic-based teleworkers and use a variety of fraudulent means to bypass employment verification controls.

North Korea’s fraudulent remote worker scheme has since evolved, establishing itself as a well-developed operation that has allowed North Korean remote workers to infiltrate technology-related roles across various industries. In some cases, victim organizations have even reported that remote IT workers were some of their most talented employees. Historically, this operation has focused on applying for IT, software development, and administrator positions in the technology sector. Such positions provide North Korean threat actors access to highly sensitive information to conduct information theft and extortion, among other operations.

North Korean IT workers are a multifaceted threat because not only do they generate revenue for the North Korean regime, which violates international sanctions, they also use their access to steal sensitive intellectual property, source code, or trade secrets. In some cases, these North Korean workers even extort their employer into paying them in exchange for not publicly disclosing the company’s data.

Between 2020 and 2022, the US government found that over 300 US companies in multiple industries, including several Fortune 500 companies, had unknowingly employed these workers, indicating the magnitude of this threat. The workers also attempted to gain access to information at two government agencies. Since then, the cybersecurity community has continued to detect thousands of North Korean workers. On January 3, 2025, the Justice Department released an indictment identifying two North Korean nationals and three facilitators responsible for conducting fraudulent work between 2018 and 2024. The indicted individuals generated a revenue of at least US$866,255 from only ten of the at least 64 infiltrated US companies.

North Korean threat actors are evolving across the threat landscape to incorporate more sophisticated tactics and tools to conduct malicious employment-related activity, including the use of custom and AI-enabled software.

Tactics and techniques

The tactics and techniques employed by North Korean remote IT workers involve a sophisticated ecosystem of crafting fake personas, performing remote work, and securing payments. North Korean IT workers apply for remote roles, in various sectors, at organizations across the globe.

They create, rent, or procure stolen identities that match the geo-location of their target organizations (for example, they would establish a US-based identity to apply for roles at US-based companies), create email accounts and social media profiles, and establish legitimacy through fake portfolios and profiles on developer platforms like GitHub and LinkedIn. Additionally, they leverage AI tools to enhance their operations, including image creation and voice-changing software. Facilitators play a crucial role in validating fraudulent identities and managing logistics, such as forwarding company hardware and creating accounts on freelance job websites. To evade detection, these workers use VPNs, virtual private servers (VPSs), and proxy services as well as RMM tools to connect to a device housed at a facilitator’s laptop farm located in the country of the job.

Crafting fake personas and profiles

The North Korean remote IT worker fraud scheme begins with the procurement of identities for the workers. These identities, which can be stolen or “rented” from witting individuals, include names, national identification numbers, and dates of birth. The workers might also leverage services that generate fraudulent identities, complete with seemingly legitimate documentation, to fabricate their personas. They then create email accounts and social media pages they use to apply for jobs, often indirectly through staffing or contracting companies. They also apply for freelance opportunities through freelancer sites as an additional avenue for revenue generation. Notably, they often use the same names/profiles repeatedly rather than creating unique personas for each successful infiltration.

Additionally, the North Korean IT workers have used fake profiles on LinkedIn to communicate with recruiters and apply for jobs.

The workers tailor their fake resumes and profiles to match the requirements for specific remote IT positions, thus increasing their chances of getting selected. Over time, we’ve observed these fake resumes and employee documents noticeably improving in quality, now appearing more polished and lacking grammatical errors facilitated by AI.

Establishing digital footprint

After creating their fake personas, the North Korean IT workers then attempt to establish legitimacy by creating digital footprints for these fake personas. They typically leverage communication, networking, and developer platforms, (for example, GitHub) to showcase their supposed portfolio of previous work samples:

Using AI to improve operations

Microsoft Threat intelligence has observed North Korean remote IT workers leveraging AI to improve the quantity and quality of their operations. For example, in October 2024, we found a public repository containing actual and AI-enhanced images of suspected North Korean IT workers:

The repository also contained the resumes and email accounts used by the said workers, along with the following tools and resources they can use to secure employment and to do their work:

• VPS and VPN accounts, along with specific VPS IP addresses
• Playbooks on conducting identity theft and creating and bidding jobs on freelancer websites
• Wallet information and suspected payments made to facilitators
• LinkedIn, GitHub, Upwork, TeamViewer, Telegram, and Skype accounts
• Tracking sheet of work performed, and payments received by the IT workers

Image creation

Based on our review of the repository mentioned previously, North Korean IT workers appear to conduct identity theft and then use AI tools like Faceswap to move their pictures over to the stolen employment and identity documents. The attackers also use these AI tools to take pictures of the workers and move them to more professional looking settings. The workers then use these AI-generated pictures on one or more resumes or profiles when applying for jobs.

Communications

Microsoft Threat Intelligence has observed that North Korean IT workers are also experimenting with other AI technologies such as voice-changing software. While we haven’t observed threat actors using combined AI voice and video products as a tactic first hand, we do recognize that combining these technologies could allow future threat actor campaigns to trick interviewers into thinking they aren’t communicating with a North Korean IT worker. If successful, this tactic could allow the North Korean IT workers to do interviews directly and no longer rely on facilitators standing in for them on interviews or selling them account access.

Facilitators for initial access

North Korean remote IT workers require assistance from a witting facilitator to help find jobs, pass the employment verification process, and once hired, successfully work remotely. We’ve observed Jasper Sleet advertising job opportunities for facilitator roles under the guise of partnering with a remote job candidate to help secure an IT role in a competitive market:

The IT workers may have the facilitators assist in creating accounts on remote and freelance job websites. They might also ask the facilitator to perform the following tasks as their relationship builds:

• Create a bank account for the North Korean IT worker, or lend their (the facilitator’s) own account to the worker
• Purchase mobile phone numbers or SIM cards

During the employment verification process, the witting accomplice helps the North Korean IT workers validate the latter’s fraudulent identities using online background check service providers. The documents submitted by the workers include fake or stolen drivers’ licenses, social security cards, passports, and permanent resident identification cards. Workers train using interview scripts, which include a justification for why the employee must work remotely.

Once hired, the remote workers direct company laptops and hardware to be sent to the address of the accomplice. The accomplice then either runs a laptop farm that provides the laptops with an internet connection at the geo-location of the role or forwards the items internationally. For hardware that remain in the country of the role, the accomplice signs into the computers and installs software that enables the workers to connect remotely. Remote IT workers might also access devices remotely using IP-based KVM devices, like PiKVM or TinyPilot.

Defense evasion and persistence

To conceal their physical location as well as maintain persistence and blend into the target organization’s environment, the workers typically use VPNs (particularly Astrill VPN), VPSs, proxy services, and RMM tools. Microsoft Threat Intelligence has observed the persistent use of JumpConnect, TinyPilot, Rust Desk, TeamViewer, AnyViewer, and Anydesk. When an in-person presence or face-to-face meeting is required, for example to confirm banking information or attend a meeting, the workers have been known to pay accomplices to stand in for them. When possible, however, the workers eliminate all face-to-face contact, offering fraudulent excuses for why they are not on camera during video teleconferencing calls or speaking.

Attribution

Microsoft Threat Intelligence uses the name Jasper Sleet (formerly known as Storm-0287) to represent activity associated with North Korean’s remote IT worker program. These workers are primarily focused on revenue generation, use remote access tools, and likely fall under a particular leadership structure in North Korea. We also track several other North Korean activity clusters that pursue fraudulent employment using similar techniques and tools, including Storm-1877 and Moonstone Sleet.

How Microsoft disrupts North Korean remote IT worker operations with machine learning

Microsoft has successfully scaled analyst tradecraft to accelerate the identification and disruption of North Korean IT workers in customer environments by developing a custom machine learning solution. This has been achieved by leveraging Microsoft’s existing threat intelligence and weak signals generated by monitoring for many of the red flags listed in this blog, among others. For example, this solution uses impossible time travel risk detections, most commonly between a Western nation and China or Russia. The machine learning workflow uses these features to surface suspect accounts most likely to be North Korean IT workers for assessment by Microsoft Threat Intelligence analysts.

Once Microsoft Threat Intelligence reviews and confirms that an account is indeed associated with a North Korean IT worker, customers are then notified with a Microsoft Entra ID Protection risk detection warning of a risky sign-in based on Microsoft’s threat intelligence. Microsoft Defender XDR customers also receive the alert Sign-in activity by a suspected North Korean entity in the Microsoft Defender portal.

Defending against North Korean remote IT worker infiltration

Defending against the threats from North Korean remote IT workers involves a threefold strategy:

• Ensuring a proper vetting approach is in place for freelance workers and vendors
• Monitoring for anomalous user activity
• Responding to suspected Jasper Sleet signals in close coordination with your insider risk team

Investigate

How can you identify a North Korean remote IT worker in the hiring process?

To protect your organization against a potential North Korean insider threat, it is important for your organization to prioritize a process for verifying employees to identify potential risks. The following can be used to assess potential employees:

• Confirm the potential employee has a digital footprint and look for signs of authenticity. This includes a real phone number (not VoIP), a residential address, and social media accounts. Ensure the potential employee’s social media/professional accounts are not highly similar to the accounts of other individuals. In addition, check that the contact phone number listed on the potential employee’s account is unique and not also used by other accounts.
• Scrutinize resumes and background checks for consistency of names, addresses, and dates. Consider contacting references by phone or video-teleconference rather than email only.
• Exercise greater scrutiny for employees of staffing companies, since this is the easiest avenue for North Korean workers to infiltrate target companies.
• Search whether a potential employee is employed at multiple companies using the same persona.
• Ensure the potential employee is seen on camera during multiple video telecommunication sessions. If the potential employee reports video and/or microphone issues that prohibit participation, this should be considered a red flag.
• During video verification, request individuals to physically hold driver’s licenses, passports, or identity documents up to camera.
• Keep records, including recordings of video interviews, of all interactions with potential employees.
• Require notarized proof of identity.

Monitor

How can your organization prevent falling victim to the North Korean remote IT worker technique?

To prevent the risks associated with North Korean insider threats, it’s vital to monitor for activity typically associated with this fraudulent scheme.

Monitor for identifiable characteristics of North Korean remote workers

Microsoft has identified the following characteristics of a North Korean remote worker. Note that not all the criteria are necessarily required, and further, a positive identification of a remote worker doesn’t guarantee that the worker is North Korean.

• The employee lists a Chinese phone number on social media accounts that is used by other accounts.
• The worker’s work-issued laptop authenticates from an IP address of a known North Korean IT worker laptop farm, or from foreign—most commonly Chinese or Russian—IP addresses even though the worker is supposed to have a different work location.
• The worker is employed at multiple companies using the same persona. Employees of staffing companies require heightened scrutiny, given this is the easiest way for North Korean workers to infiltrate target companies.
• Once a laptop is issued to the worker, RMM software is immediately downloaded onto it and used in combination with a VPN.
• The worker has never been seen on camera during a video telecommunication session or is only seen a few times. The worker may also report video and/or microphone issues that prohibit participation from the start.
• The worker’s online activity doesn’t align with routine co-worker hours, with limited engagement across approved communication platforms.

Monitor for activity associated with Jasper Sleet access

• If RMM tools are used in your environment, enforce security settings where possible, to implement MFA:
  • Use Windows Defender Application Control or AppLocker to create policies to block unapproved IT management tools. Consider hunting for unapproved RMM software installations and creating custom detections (Investigation & response > Hunting > Advanced hunting > Manage rules > Create custom detection) for any advanced hunting queries that are useful indicators of anomalous or unapproved activity in your environment.
  • If an unapproved installation is discovered, 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.
• Monitor for impossible travel—for example, a supposedly US-based employee signing in from China or Russia.
• Monitor for use of public VPNs such as Astrill. For example, IP addresses associated with VPNs known to be used by Jasper Sleet can be added to Sentinel watchlists. Or, Microsoft Defender for Identity can integrate with your VPN solution to provide more information about user activity, such as extra detection for abnormal VPN connections.
• Monitor for signals of insider threats in your environment. Microsoft Purview Insider Risk Management can help identify potentially malicious or inadvertent insider risks.
• Monitor for consistent user activity outside of typical working hours.

Remediate

What are the next steps if you positively identify a North Korean remote IT worker employed at your company?

Because Jasper Sleet activity follows legitimate job offers and authorized access, Microsoft recommends approaching confirmed or suspected Jasper Sleet intrusions with an insider risk approach using your organization’s insider risk response plan or incident response provider like Microsoft Incident Response. Some steps might include:

• Restrict response efforts to a small, trusted insider risk working group, trained in operational security (OPSEC) to avoid tipping off subjects and potential collaborators.
• Rapidly evaluate the subject’s proximity to critical assets, such as:
  • Leadership or sensitive teams
  • Direct reports or vendor staff the subject has influence over
  • Suppliers or vendors
  • People/non-people accounts, production/pre-production environments, shared accounts, security groups, third-party accounts, security groups, distribution groups, data clusters, and more
• Conduct preliminary link analysis to:
  • Detect relationships with potential collaborators, supporters, or other potential aliases operated by the same actor
  • Identify shared indicators (for example, shared IP addresses, behavioral overlap)
  • Avoid premature action that might alert other Jasper Sleet operators
• Conduct a risk-based prioritization of efforts, informed by:
  • Placement and access to critical assets (not necessarily where you identified them)Stakeholder insight from potentially impacted business units
  • Business impact considerations of containment (which might support additional collection/analysis) or mitigation (for example, eviction)
• Conduct open-source intelligence (OSINT) collection and analysis to:
  • Determine if the identity associated with the threat actor is associated with a real person. For example, North Korean IT workers have leveraged stolen identities of real US persons to facilitate their fraud. Conduct OSINT on all available personally identifiable information (PII) provided by the actor (name, date of birth, SSN, home of record, phone number, emergency contact, and others) and determine if these items are linked to additional North Korean actors, and/or real persons’ identities.
  • Gather all known external accounts operated by the alias/persona (for example, LinkedIn, GitHub, freelance working sites, bug bounty programs).
  • 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.
• Engage counterintelligence or insider risk/threat teams to:
  • Understand tradecraft and likely next steps
  • Gain national-level threat context, if applicable
• Make incremental, risk-based investigative and response decisions with the support of your insider threat working group and your insider threat stakeholder group; one providing tactical feedback and the other providing risk tolerance feedback.
• Preserve evidence and document findings.
• Share lessons learned and increase awareness.
• Educate employees on the risks associated with insider threats and provide regular security training for employees to recognize and respond to threats, including a section on the unique threat posed by North Korean IT workers.

After an insider risk response to Jasper Sleet, it might be necessary to also conduct a thorough forensic investigation of all systems that the employee had access to for indicators of persistence, such as RMM tools or system/resource modifications.

For additional resources, refer to CISA’s Insider Threat Mitigation Guide. If you suspect your organization is being targeted by nation-state cyber activity, report it to the appropriate national authority. For US-based organizations, the Federal Bureau of Investigation (FBI) recommends reporting North Korean remote IT worker activity to the Internet Crime Complaint Center (IC3).

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, 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 Defender XDR

Alerts with the following title in the security center can indicate threat activity on your network:

• Sign-in activity by a suspected North Korean entity

Microsoft Defender for Endpoint

Alerts with the following titles in the security center can indicate Jasper Sleet RMM activity on your network. These alerts, however, can be triggered by unrelated threat activity.

• Suspicious usage of remote management software
• Suspicious connection to remote access software

Microsoft Defender for Identity

Alerts with the following titles in the security center can indicate atypical identity access on your network. These alerts, however, can be triggered by unrelated threat activity.

• Atypical travel
• Suspicious behavior: Impossible travel activity

Microsoft Entra ID Protection

Microsoft Entra ID Protection risk detections inform Entra ID user risk events and can indicate associated threat activity, including unusual user activity consistent with known patterns identified by Microsoft Threat Intelligence research. Note, however, that these alerts can be also triggered by unrelated threat activity.

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

Microsoft Defender for Cloud Apps

Alerts with the following titles in the security center can indicate atypical identity access on your network. These alerts, however, can be triggered by unrelated threat activity.

• Impossible travel activity

Microsoft Security Copilot

Security Copilot customers can use the standalone experience to create their own prompts or run the following prebuilt promptbooks to automate incident response or investigation tasks related to this threat:

• Incident investigation
• Microsoft User analysis
• Threat actor profile

Note that some promptbooks require access to plugins for Microsoft products such as Microsoft Defender XDR or Microsoft Sentinel.

Hunting queries

Microsoft Defender XDR

Because organizations might have legitimate and frequent uses for RMM software, we recommend using the Microsoft Defender XDR advanced hunting queries available on GitHub to locate RMM software that hasn’t been endorsed by your organization for further investigation. In some cases, these results might include benign activity from legitimate users. Regardless of use case, all newly installed RMM instances should be scrutinized and investigated.

If any queries have high fidelity for discovering unsanctioned RMM instances in your environment, and don’t detect benign activity, you can create a custom detection rule from the advanced hunting query in the Microsoft Defender portal. 

Microsoft Sentinel

The alert Insider Risk Sensitive Data Access Outside Organizational Geo-locationjoins Azure Information Protection logs (InformationProtectionLogs_CL) with Microsoft Entra ID sign-in logs (SigninLogs) to provide a correlation of sensitive data access by geo-location. Results include:

• User principal name
• Label name
• Activity
• City
• State
• Country/Region
• Time generated

The recommended configuration is to include (or exclude) sign-in geo-locations (city, state, country and/or region) for trusted organizational locations. There is an option for configuration of correlations against Microsoft Sentinel watchlists. Accessing sensitive data from a new or unauthorized geo-location warrants further review.

References

• https://www.justice.gov/opa/pr/two-north-korean-nationals-and-three-facilitators-indicted-multi-year-fraudulent-remote
• https://www.justice.gov/usao-dc/media/1352191/dl
• https://www.reuters.com/technology/north-koreans-use-fake-names-scripts-land-remote-it-work-cash-2023-11-21/
• https://github.com/jischell-msft/RemoteManagementMonitoringTools

Acknowledgments

For more information on North Korean remote IT worker operations, we recommend reviewing DTEX’s in-depth analysis in the report Exposing DPRK’s Cyber Syndicate and IT Workforce.

Learn more

Meet the experts behind Microsoft Threat Intelligence, Incident Response, and the Microsoft Security Response Center at our VIP Mixer at Black Hat 2025. Discover how our end-to-end platform can help you strengthen resilience and elevate your security posture.

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 Jasper Sleet: North Korean remote IT workers’ evolving tactics to infiltrate organizations appeared first on Microsoft Security Blog.

One of the primary challenges in reverse engineering malware developed with Rust lies in its layers of abstraction added through features such as memory safety and concurrency handling, making it more challenging to identify the behavior and intent of the malware. Compared to traditional languages, Rust binaries are often larger and more complex due to the incorporation of extensive library code. Consequently, reverse engineers must undertake the demanding task of distinguishing attacker-written code from standard library code, necessitating advanced expertise and specialized tools.

To address these pressing challenges, Microsoft Threat Intelligence Center has developed RIFT. RIFT underscores the growing need for specialized tools as cyber threat actors continue to leverage Rust’s features to evade detection and complicate analysis. The adoption of Rust by threat actors is a stark reminder of the ever-changing tactics employed in the cyber domain, and the increasing sophistication required to combat these threats effectively. In this blog post, we explore how threat actors are increasingly adopting Rust for malware development due to its versatility and how RIFT can be used to combat this threat by enhancing the efficiency and accuracy of Rust-based malware analysis.

Threat actors continue adopting Rust

As Rust gains popularity as a rapidly growing programming language, its use by malware authors is becoming more noticeable. Over the past five years, Microsoft Threat Intelligence Center and the broader security industry have observed financially motivated and state-supported groups increasingly using Rust for malware development.

In 2021, the group behind the notorious BlackCat ransomware was among the first significant entities in the ransomware field to write their malicious programs in Rust. Following the appearance of the first malware families written in Rust, reverse engineers indicated that such malware presents a unique challenge for analysis.

Subsequently, several other groups began developing or rewriting their tools in the programming language. Nation-state threat actors have also selectively developed their malware in Rust.

Rust as a popular language for malware development

Rust is a versatile language known for its performance, type safety, concurrency, and memory safety. While these features benefit legitimate development, they also complicate static analysis of malicious files. The community has extensively addressed many of these challenges. One of the core issues in analyzing Rust binaries is differentiating between library code and code written by malware authors.

To illustrate the significance of this problem, Microsoft Threat Intelligence Center conducted a simple experiment. A small PE EXE file that downloads data from a website and saves it on disk as sample_data.txt is generated with Microsoft 365 Copilot. The program is first compiled in C++ and then in Rust. The C++ program is compiled using Microsoft Visual C++ (MSVC) with Visual Studio 2022, in release mode for the 64-bit architecture and dynamically linked, using default settings. The Rust binary is compiled using compiler version rustc 1.89.0-nightly (16d2276fa 2025-05-16), also in release mode and with default settings.

Next, both programs are loaded into IDA Pro, and a simple complexity analysis is performed by counting and comparing the number of disassembled and identified functions. Additionally, functions are categorized as annotated or not annotated. An annotated function is one that is automatically detected by IDA’s built-in signatures or algorithms. It should be noted that IDA has capabilities to enhance library recognition, but these were not used for this experiment.

While both programs implement similar functionalities, the total number of disassembled functions in the C++ program is lower than 100, while the Rust programs pack almost 10,000 functions. Furthermore, the size of the C++ program is lower than 20 KB, while the Rust program is larger than 3 MB.

Programs written in Rust are typically statically linked, embedding all dependencies directly into the executable. As a result, binaries are larger with a high volume of functions, requiring analysts to distinguish first between third-party library code and attacker-authored logic.

To address this key problem, Microsoft Threat Intelligence Center is releasing an internally developed tool: RIFT.

This open-source project is designed to help reverse engineers and analysts more efficiently identify attacker-authored logic within Rust-based malware.

From source code to binary

Before delving into the inner workings of RIFT, it is essential to have a fundamental understanding of how Rust binaries are compiled. As illustrated in the diagram above, Rust developers typically engage with three primary components and two endpoints:

• cargo – The package manager
• rustc – The Rust compiler
• rustup – The Rust update manager
• static.rust-lang.org – S3 bucket that hosts pre-compiled compilers and toolchains
• crates.io – Rust community’s crate registry

Once a developer has conceptualized what they intend to develop, a typical workflow may proceed as follows:

1. Using the cargo tool, the developer initializes a new projected named “test”.
2. They opt not to use the latest Rust compiler but a specific version. They execute rustup install 1.84.0-x86_64-pc-windows-msvc to install the desired compiler version and configure the project to use the installed compiler.
3. They determine that their project should communicate via HTTP and incorporate a third-party dependency. They run cargo add request to install the latest version of the third-party library, request.

Following these steps will result in a fully configured project. Upon completion, the developer may run cargo build to finalize the binary, compiling the project.

Static artifacts and where to find them

Reverse engineers are usually handed the final development product of the malware author, oftentimes without information such as the compiler used or third-party dependencies. While it is highly likely that malware authors use the same tools as reverse engineers for development, no insights into the exact environment are available.

However, understanding the development toolchain can assist in quickly distinguishing library code from author written logic. Fortunately, various indicators can be extracted that provide insights.

Rust compiler version

Rust binaries typically include metadata from the compiler that identifies the Rust version used to compile the binary. A config.toml file is provided alongside pre-compiled Rust compilers and toolchains. This configuration file contains the commit hash and the corresponding Rust compiler version of the pre-compiled product. By extracting the commit hash from the final binary output, it is possible to map the Git commit hash back to the appropriate Rust compiler version by parsing all available config.toml files from the official release channels.

Rust crates

As mentioned above, cargo is used to add dependencies to a project. Next to the Git commit hash, metadata extracted from Rust binaries also include the statically linked dependencies and their versions.

The above image shows how filtering for certain strings can display which dependencies were likely statically linked into RALord ransomware.

Introducing RIFT

RIFT is an open-source tool consisting of a set of IDA Pro (supporting versions >=9.0) plugins and Python scripts that aim to assist reverse engineers and other software analysts in annotating library code in Rust malware. It essentially consists of three components:

RIFT Static Analyzer: IDA Pro plugin to extract the Rust compiler commit hash and embedded dependencies from a binary.

RIFT Generator: A Python program to automate the process of Rust compiler identification, FLIRT signature generation of used Rust compiler and dependencies, as well as automation of binary diffing.

RIFT Diff Applier: IDA Pro plugin to consume binary diffing information generated by RIFT Generator.

Extracting static information with RIFT Static Analyzer

In the previous section, we listed which indicators can be extracted from Rust binaries that give insights into which Rust compiler and dependencies were used. RIFT Static Analyzer automates the extraction process and stores the information in a JSON file for further processing. Furthermore, the plugin also extracts the architecture the binary was compiled for and the target operating system. In the below image, the target operating system is labeled as target_triple.

RIFT Generator: Automating FLIRT signature generation and auto diffing

Information gathered and stored by RIFT Static Analyzer can then be further processed by RIFT Generator.

The Python program automates the process of compilation, data collection, FLIRT signature generation, and binary comparison.

It is essentially a wrapper around the following tools:

• Cargo (Rust package manager) to manage the downloading and compiling of dependencies
• Hexray’s FLAIR tools, specifically sigmake.exe and pcf.exe, to generate FLIRT signatures
• Hexray’s text interface version of IDA, idat.exe, to automate binary analysis and disassembly
• The open-source tool Diaphora to facilitate binary diffing

The above image provides an overview of the phases RIFT Generator processes through. RIFT Generator reads the JSON file produced by RIFT Static Analyzer and downloads the corresponding Rust compiler, as well as the dependencies.

It is worth noting that upon completion of phase 1, both the code of the downloaded compiler and compiled crates are compressed as COFF files into RLIB files. RLIB is essentially a Rust-specific archive format similar to TAR. Once decompressed in phase 2, the COFF files are extracted and further processed.

FLIRT signatures and binary diffing

To provide information necessary for annotating library code in Rust binaries accurately, RIFT uses two known techniques for pattern matching: FLIRT signatures and binary diffing.

FLIRT stands for Fast Library Identification and Recognition Technology and enables IDA to identify standard library functions produced by its supported compilers. A characteristic of this technology is that library recognition is very precise. Therefore, functions that have a high similarity may not be flagged by FLIRT signatures due to their strict criteria.

Additionally, RIFT automates the process of binary diffing the collected COFF files against the target binary by leveraging IDA’s command line utility (idat.exe) and the Diaphora plugin.

In general, both approaches have their own advantages and disadvantages, which are listed below.

Consuming binary diffing information

If the binary diffing approach is applied, a second IDA plugin called RIFT Diff Applier can be used to apply the diffing results. In contrast to FLIRT signatures, the RIFT Diff Applier offers analysts an interactive, semi-manual method for identifying library code. It operates in two modes:

1. Interactive mode
2. Auto rename mode

By default, symbol names in COFF files are mangled. Consequently, if RIFT Generator generates the binary diffing information and stores it in the JSON format, the symbol names are also mangled. To address this issue, enabling Name Demangling can assist in attempting to demangle these names. We are continuously improving the tool, and currently, rust-demangler is being used for this purpose.

For both modes, a minimum similarity ratio can be specified. Functions will only be displayed or renamed if they meet or exceed the specified similarity threshold. Once the user clicks “OK”, a new window will appear in IDA with the title RIFT. Users can now right click on a function name and display the top three matching functions with the highest similarity determined through binary diffing or use the CTRL+X shortcut.

Applying RIFT on RALord ransomware

Having introduced the functionalities of RIFT, we will now examine its practical application in analyzing RALord ransomware and how RIFT’s FLIRT signature generation can be used to immensely reduce time identifying library functions in RALord.

First, RIFT Static Analyzer is used to dump the extractable dependencies, Git commit hash of the Rust compiler, target architecture, and target operating system. Next, the information is fed into RIFT Generator.

Once RIFT Generator has finished generating FLIRT signatures, they can either be loaded one by one manually or by using our script shared in the RIFT GitHub repository named “ida_apply_flirt_from_folder.py”.

The image below compares parts of the main function before and after application of RIFT. After applying the FLIRT signatures generated from the extracted dependencies and Rust compiler, the majority of library and compiler code is identified in the main function. As a result, reverse engineers can focus solely on the threat actor code instead of spending time weeding out the library code.

Applying RIFT on SPICA

In some use cases, FLIRT signature application might not be enough, for example when conducting a deep dive. RIFT’s binary diffing approach can provide additional information to improve library code recognition in addition to FLIRT signatures.

Having demonstrated the effectiveness of RIFT in applying FLIRT signatures to streamline the analysis of RALord ransomware, we now turn our focus to applying the binary diffing approach on SPICA, a backdoor written in Rust. This transition highlights scenarios where FLIRT signatures alone might be insufficient, necessitating a deeper, complementary analysis.

Similar to before, RIFT Static Analyzer is used first and the extracted information is fed into RIFT Generator. However, this time, we apply FLIRT signature generation and binary diffing.

To use the binary diffing approach, Diaphora must be used first to generate the corresponding SQLite file. It is worth noting that depending on the size of the binary and extracted dependencies, the binary diffing procedure can take multiple hours.

Once done, RIFT Diff Applier can be used to load the binary diffing output file.

A benefit of this approach is that for certain functions where FLIRT signatures failed to properly label the library function due to its strictness, RIFT Diff Applier can provide useful and reliable information where the similarity is high. Furthermore, thinking about detection engineering, the approach can also help identify or filter out potential library functions, especially when writing signatures on code segments.

Afterwords: Open sourcing RIFT

Rust’s strong performance, safety-focused design, cross-compilation support, and concurrency features have led to its increased adoption by threat actors for developing complex malware. This growing shift towards Rust represents a yet another evolution in the threat landscape, enabling attackers to create malware that is not more resistant to detection and analysis.

For malware analysts, this trend introduces a daunting set of challenges. Rust’s innovative features often result in binaries that are harder to decompile and analyze, making reverse engineering a time-intensive process. Analysts are frequently left grappling with unfamiliar patterns and library-heavy outputs, which further complicate their efforts to dissect malware and develop detection methods.

To address these challenges, we are proud to announce the open sourcing of RIFT. Designed to help accelerate Rust malware analysis by assisting reverse engineers to recognize library code in Rust malware through FLIRT signatures and binary diffing, RIFT further reinforces global efforts to equip security professionals with proper tools to defend against threats. By making RIFT freely available to the cybersecurity community, we aim to foster collaboration and innovation in combating the rise of Rust-based malware. We would like to extend a special thanks to the author of the Diaphora project for their invaluable contribution to the reverse engineering community.

Microsoft’s ongoing research and development efforts, including the creation of tools like RIFT, underscore our commitment to protecting customers and securing the cyber landscape. By enhancing the efficiency and accuracy of malware analysis, we aim to keep pace with evolving threats and ensure the safety of users worldwide. This research highlights the critical need for advanced security measures to safeguard against such increasingly sophisticated cyber threats.

References

• https://github.com/microsoft/RIFT
• https://www.security.com/threat-intelligence/noberus-blackcat-alphv-rust-ransomware
• http://approjects.co.za/?big=en-us/security/blog/2022/07/05/hive-ransomware-gets-upgrades-in-rust/#:~:text=Hive%20isn’t%20the%20first,data%20type%2C%20and%20thread%20safety
• https://www.trendmicro.com/en_us/research/23/e/rust-based-info-stealers-abuse-github-codespaces.html
• https://www.gdatasoftware.com/blog/2025/05/38207-asyncrat-rust
• https://www.sonicwall.com/blog/nova-raas-the-ransomware-that-spares-schools-and-nonprofits-for-now
• https://research.checkpoint.com/2023/rust-binary-analysis-feature-by-feature/
• https://doc.rust-lang.org/cargo/
• https://docs.hex-rays.com/user-guide/helper-tools
• https://github.com/joxeankoret/diaphora
• https://www.ti.com/lit/an/spraao8/spraao8.pdf?ts=1749128710998
• https://pypi.org/project/rust-demangler/
• https://blog.google/threat-analysis-group/google-tag-coldriver-russian-phishing-malware/

Acknowledgments

• https://www.sentinelone.com/press/sentinelone-and-intezer-team-to-simplify-reverse-engineering-of-rust-malware/
• https://www.youtube.com/watch?v=cMIhIARmNfU

Learn more

Meet the experts behind Microsoft Threat Intelligence, Incident Response, and the Microsoft Security Response Center at our VIP Mixer at Black Hat 2025. Discover how our end-to-end platform can help you strengthen resilience and elevate your security posture.

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 latest changes in the broader threat landscape, listen to the Microsoft Threat Intelligence podcast. 

The post Unveiling RIFT: Enhancing Rust malware analysis through pattern matching appeared first on Microsoft Security Blog.