Arnold Chan
@slazTrusted contributorCompletionist
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7,555 detections
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This rule detects potentially malicious child processes spawned by Node.js. It specifically monitors for scenarios where a Node.js process executes a detached child process using standard library options ('detached', 'stdio', 'windowsHide', 'ignore'), which is a common technique used by malware to run background tasks while remaining hidden from the parent process terminal. The rule excludes common benign development, build, and process management tools to reduce false positives.
This rule detects potentially malicious child processes spawned by Node.js. It specifically monitors for scenarios where a Node.js process executes a detached child process using standard library options ('detached', 'stdio', 'windowsHide', 'ignore'), which is a common technique used by malware to run background tasks while remaining hidden from the parent process terminal. The rule excludes common benign development, build, and process management tools to reduce false positives.
This rule detects instances where a Node.js process spawns a child Node.js process from a 'node_modules' directory using configuration flags typically associated with hidden, detached background tasks (e.g., 'detached', 'stdio', 'windowsHide', 'ignore'). It explicitly excludes common Node.js process managers and build tools to reduce false positives associated with legitimate development activities.
Detects anomalous patterns associated with potential WordPress comment moderation bypass. The rule identifies suspicious rapid sequences of comment submissions, use of unapproved comment preview endpoints with moderation hashes, or reuse of approved-commenter cookies. These behaviors can be indicative of an attacker attempting to preview or force-render stored XSS payloads to administrators or visitors before the comment has been officially approved.
Detects anomalous patterns associated with potential WordPress comment moderation bypass. The rule identifies suspicious rapid sequences of comment submissions, use of unapproved comment preview endpoints with moderation hashes, or reuse of approved-commenter cookies. These behaviors can be indicative of an attacker attempting to preview or force-render stored XSS payloads to administrators or visitors before the comment has been officially approved.
Detects anomalous patterns associated with potential WordPress comment moderation bypass. The rule identifies suspicious rapid sequences of comment submissions, use of unapproved comment preview endpoints with moderation hashes, or reuse of approved-commenter cookies. These behaviors can be indicative of an attacker attempting to preview or force-render stored XSS payloads to administrators or visitors before the comment has been officially approved.
Detects anomalous patterns associated with potential WordPress comment moderation bypass. The rule identifies suspicious rapid sequences of comment submissions, use of unapproved comment preview endpoints with moderation hashes, or reuse of approved-commenter cookies. These behaviors can be indicative of an attacker attempting to preview or force-render stored XSS payloads to administrators or visitors before the comment has been officially approved.
Detects potential zero-click administrator session hijacking by correlating a logged-in administrator accessing a page containing user-generated content (e.g., comments) followed immediately by a sensitive administrative action (e.g., plugin installation, user creation) within a 5-second window, suggesting automated script execution via an autofocus/onfocus handler triggered by the admin's browser.
Detects AI agent tooling (e.g., LangChain, Copilot, Claude Code) performing read operations on databases containing sensitive data patterns, or performing suspicious bulk data enumeration. The rule monitors Azure SQL Database security audit events for suspicious application name signatures and non-schema introspective queries.
Detects AI agent tooling (e.g., LangChain, Copilot, Claude Code) performing read operations on databases containing sensitive data patterns, or performing suspicious bulk data enumeration. The rule monitors Azure SQL Database security audit events for suspicious application name signatures and non-schema introspective queries.
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