Ibrahim Saud
@tektrixIndiaCompletionist
2 followers18,457 downloads7,048 copies47 likes38,331 views
11,679 detections
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Detects instances of rundll32.exe or regsvr32.exe executing from suspicious locations or with suspicious command-line arguments (e.g., URLs, JavaScript, or script file extensions) initiated by an unsigned process. This is a common technique used to proxy malicious code execution while evading security monitoring.
This rule detects common Cobalt Strike malleable profile named pipe creation events as well as network connections initiated by common LOLBins (Living Off the Land Binaries) that are unsigned, which is a common indicator of beaconing activity.
Detects execution patterns associated with known Water Hydra exploit chains, specifically targeting CVE-2023-38831 (WinRAR self-extracting archive exploitation) and CVE-2024-21412 (Mark-of-the-Web/SmartScreen bypass via nested internet shortcuts). The rule monitors process lineage for WinRAR spawning command interpreters from temporary extraction directories and command line anomalies associated with rundll32.exe triggered from internet shortcut chains.
Detects instances where common AI agent orchestration runtimes (e.g., LangChain, AutoGPT, CrewAI) spawn command-line or scripting interpreters as child processes. This behavior is highly suspicious and often indicative of malicious command execution triggered by prompt injection attacks, where an adversary manipulates the agent into executing arbitrary system commands.
This rule detects the installation of common AI agent and orchestration frameworks (e.g., LangChain, AutoGen, CrewAI) using command-line package managers (pip, npm, conda) that point to non-standard or unverified package indexes. This behavior is a common indicator of a potential software supply-chain compromise, where an adversary attempts to inject malicious code by forcing the installation of packages from an attacker-controlled source.
This rule monitors Azure Active Directory service principal sign-in logs to identify authentication attempts from countries or Autonomous System Numbers (ASNs) that have not been observed in the entity's 14-day historical baseline. Such anomalous login behavior may indicate potential account compromise, token theft, or unauthorized use of service principal credentials.
This rule detects automated browser-based processes (such as chromedriver, msedgedriver, geckodriver, playwright, or node/python scripts leveraging browser automation frameworks) initiating network connections to domains or URLs identified in active threat intelligence as malicious. This behavior is indicative of an AI agent or automated script being steered toward attacker-controlled infrastructure, potentially for drive-by compromise or exploitation.
Detects DNS query activity from processes commonly used as AI agent runtimes (e.g., python.exe, node.exe) toward domains characterized by DGA-like patterns, such as long alphanumeric strings or high-consonant density, which may indicate command-and-control communication.
Detects a burst of file delete or overwrite operations initiated by a configured AI agent service identity. This behavior, if deviating from established baselines, may indicate a compromised agent performing malicious destructive activities such as mass data deletion or ransomware-style file destruction.
Detects anomalous use of an LLM provider API key by identifying successful API requests originating from multiple distinct countries within a one-hour time window. This activity often indicates the potential theft and concurrent unauthorized use of an API token.
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