Arnold Chan
@slazTrusted contributorCompletionist
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7,555 detections
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This rule detects potential malicious activity by matching endpoint file events against a known list of malicious file hashes (SHA256, SHA1, MD5) and monitoring for connections to known malicious domains or URLs.
Sweeps DeviceFileEvents, DeviceProcessEvents, and DeviceNetworkEvents over a rolling 30-day window for known RevStealer indicators: exact SHA-256 matches against all 13 published file hashes, and exact-host matches (via parsed URL host, not substring) against the confirmed C2 domain meta7.archscreen68.one. An empty, extensible IP list is included for when a malicious IP is published.
Detects malicious AI assistant links delivered via spearphishing emails that contain pre-populated prompt injection query parameters. The rule correlates the clicking of a high-signal URL (containing parameters like prompt, system, or lengthy search queries with malicious keywords) originating from an email with a subsequent active session to the same AI service within 5 minutes, confirming potential weaponized AI assistant session manipulation. Covers T1566.002, T1204.001
Detects malicious AI assistant links delivered via spearphishing emails that contain pre-populated prompt injection query parameters. The rule correlates the clicking of a high-signal URL (containing parameters like prompt, system, or lengthy search queries with malicious keywords) originating from an email with a subsequent active session to the same AI service within 5 minutes, confirming potential weaponized AI assistant session manipulation. Covers T1566.002, T1204.001
Detects a multi-stage attack pattern against publicly exposed AI service endpoints. The detection correlates: (1) Enumeration of sensitive AI/MCP-related API endpoints (minimum 3 distinct hits) in a 10-minute window; (2) Subsequent POST requests to AI service endpoints within 15 minutes of the enumeration; and (3) A spike of 5 or more server errors (HTTP 5xx) within 10 minutes following the POST activity. This pattern suggests automated reconnaissance followed by attempted exploitation of exposed AI model interfaces or orchestration services. Covers T1595.002, T1190
Detects rapid, multi-category reconnaissance activity initiated by AI-agent binaries (e.g., Claude, Cursor, ChatGPT). The rule identifies sessions that perform four or more distinct discovery operations—spanning account, network service, system information, and network configuration discovery—within a short time window, indicating potentially malicious autonomous exploration by an AI agent. Covers T1046, T1087, T1083, T1016
Detects potential multimodal prompt injection attacks where an AI agent process ingests a file (PDF, image, etc.) from a browser or mail client and subsequently performs suspicious downstream activity, such as spawning a shell with execution primitives or making network connections to rare, non-reputable external domains. Covers T1204, T1059, T1105
Detects a multi-stage attack chain where an AI-agent's configuration file (e.g., mcp.json) is modified, followed immediately by the execution of a tool process (node/python) spawned by the agent, the subsequent spawning of a shell process, and finally an outbound network connection to a rare, non-standard domain. This sequence is indicative of AI agent tool poisoning, where malicious tool definitions are introduced to execute arbitrary commands and exfiltrate data. Coverts T1195.002, T1565.001, T1059
Detects a multi-stage attack chain where an AI-agent's configuration file (e.g., mcp.json) is modified, followed immediately by the execution of a tool process (node/python) spawned by the agent, the subsequent spawning of a shell process, and finally an outbound network connection to a rare, non-standard domain. This sequence is indicative of AI agent tool poisoning, where malicious tool definitions are introduced to execute arbitrary commands and exfiltrate data. Coverts T1195.002, T1565.001, T1059
Detects a multi-stage attack chain where an AI-agent's configuration file (e.g., mcp.json) is modified, followed immediately by the execution of a tool process (node/python) spawned by the agent, the subsequent spawning of a shell process, and finally an outbound network connection to a rare, non-standard domain. This sequence is indicative of AI agent tool poisoning, where malicious tool definitions are introduced to execute arbitrary commands and exfiltrate data. Coverts T1195.002, T1565.001, T1059
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