Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects the creation or modification of registry entries within the 'HKCU\...\Run' hive that point to executables located in suspicious or atypical directories such as 'ProgramData', 'Users\All Users', or specific non-standard application paths often used by malware for persistence.
Detects the execution of binaries masquerading as legitimate software (such as KeePass, Adobe Flash, or specialized medical document viewers) from user-writable and non-standard execution paths (e.g., Downloads, Temp). This behavior is characteristic of the CHOSEN BRICK malware's lure-execution stage, where users are socially engineered into running a decoy installer.
Detects the use of built-in Windows utilities and commands to disable system recovery features, delete volume shadow copies, clear backup catalogs, or perform mass file deletion. This behavior is highly indicative of wiper malware preparing for a destructive attack by preventing system recovery.
Detects outbound network traffic, including DNS lookups, TLS connections, and HTTP requests, directed towards IPRoyal or LightningProxies. These services are commonly used as residential or datacenter proxies and may be leveraged by adversaries for command-and-control (C2) communication, including traffic tunneling for services like Telegram.
Flags individual authentication events against services WaterPlum/North Korean IT worker operations are known to touch (laptop-farm remote-access tooling, freelance/crowdsourcing platforms, job-application and recruitment portals). This rule matches on a SINGLE qualifying event and does not itself prove IP reuse across contexts -- this Sigma dialect has no native cross-event correlation construct, so confirming that the SAME source IP appears across two or more of these categories (the actual WaterPlum indicator reported by investigators) requires a downstream correlation search, SOAR playbook, or UEBA rule that groups these flagged events by SourceIp over a rolling window.
No description available.
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.
No description available.
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.
Detects the execution of PowerShell with encoded commands originating from scripting engines wscript.exe or cscript.exe. The command line contains indicators of malicious activity such as references to external domains, archive expansion, or specific executable payloads.
Detects the Microsoft Edge browser executable running from an anomalous path (C:\ProgramData\Microsoft\Windows\Telemetry\) or exhibiting suspicious network behavior (to a known malicious domain 'deadhub.org' or IP address '193.23.118.155'). This behavior is indicative of a masquerading attempt to hide malicious activity by mimicking a trusted browser binary.
Detects modifications to HKEY_CURRENT_USER Run keys associated with the HEAVYGRAM backdoor, which uses specific filenames and patterns to establish persistence via autorun registry entries.
Detects unauthorized usage of the Android Accessibility Service to navigate system settings, specifically targeting the toggling of developer options and the extraction of 6-digit ADB pairing codes, as observed in the RatHat Android malware.
Detects instances where AI-based coding or agent-driven tools (e.g., Cursor, Claude Code, AutoGPT) perform suspicious file archiving/packaging activities followed by network egress to unauthorized or known exfiltration-prone services. This helps identify potential data exfiltration by AI agents or compromised development environments.
Detects instances where AI-based coding or agent-driven tools (e.g., Cursor, Claude Code, AutoGPT) perform suspicious file archiving/packaging activities followed by network egress to unauthorized or known exfiltration-prone services. This helps identify potential data exfiltration by AI agents or compromised development environments.
Detects AI coding assistants and LLM agent frameworks attempting to access, read, or export sensitive credential files, registry hives, or application secrets. The rule monitors both file system operations on known secret locations and process execution patterns indicative of credential dumping or API token retrieval by these tools.
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