Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects uncommon or suspicious child processes spawning from a WSL process. This could indicate an attempt to evade parent/child relationship detections or persistence attempts via cron using WSL.
Detects uncommon or suspicious child processes spawning from a WSL process. This could indicate an attempt to evade parent/child relationship detections or persistence attempts via cron using WSL.
Detects uncommon or suspicious child processes spawning from a WSL process. This could indicate an attempt to evade parent/child relationship detections or persistence attempts via cron using WSL.
Detects uncommon or suspicious child processes spawning from a WSL process. This could indicate an attempt to evade parent/child relationship detections or persistence attempts via cron using WSL.
Detects uncommon or suspicious child processes spawning from a WSL process. This could indicate an attempt to evade parent/child relationship detections or persistence attempts via cron using WSL.
Detects uncommon or suspicious child processes spawning from a WSL process. This could indicate an attempt to evade parent/child relationship detections or persistence attempts via cron using WSL.
Detects uncommon or suspicious child processes spawning from a WSL process. This could indicate an attempt to evade parent/child relationship detections or persistence attempts via cron using WSL.
Detects artifacts of the winAgent v2.0 Windows implant line, including mod_* modules, WUEngine persistence binaries, and COM/CLSID hijack strings used by AI-assisted implant development
Detects artifacts of the winAgent v2.0 Windows implant line, including mod_* modules, WUEngine persistence binaries, and COM/CLSID hijack strings used by AI-assisted implant development
Detects potential device-code phishing abuse where a successful device code authentication is followed by scripted API activity using common automation user agents within a short time window (10 minutes). This behavior is indicative of an attacker who has successfully phished a user's device code and is immediately leveraging the stolen token to interact with Microsoft Graph, Azure, or Intune services.
Detects potential device-code phishing abuse where a successful device code authentication is followed by scripted API activity using common automation user agents within a short time window (10 minutes). This behavior is indicative of an attacker who has successfully phished a user's device code and is immediately leveraging the stolen token to interact with Microsoft Graph, Azure, or Intune services.
Detects potential device-code phishing abuse where a successful device code authentication is followed by scripted API activity using common automation user agents within a short time window (10 minutes). This behavior is indicative of an attacker who has successfully phished a user's device code and is immediately leveraging the stolen token to interact with Microsoft Graph, Azure, or Intune services.
This rule detects suspicious process execution originating from web server applications (e.g., php-fpm, apache2, nginx). It looks for common shell interpreters or command-line utilities (e.g., bash, curl, python) triggered by these web server processes when they contain command execution function strings in their command lines (e.g., system, shell_exec, passthru), which is a common indicator of web shell activity or post-exploitation command execution.
Detects anomalous child process execution originating from PaperCut application processes (pc-app.exe) or associated Java processes. This is indicative of post-exploitation activity following an RCE vulnerability where the application server is leveraged to spawn command interpreters, discovery utilities, or ingress tools.
This rule detects potentially malicious activity originating from Microsoft Word (WINWORD.EXE). It monitors for two specific patterns: the creation of script files (.bat, .vbs, .cmd) with GUID-based filenames in non-temp directories, and the creation or execution of files matching known malicious hashes associated with the Hookedge malware family.
Detects execution or file presence associated with HOOKEDGE/HEADLACE malware. This rule uses a dual-approach: matching known malicious file hashes (SHA256) and monitoring for specific script files (bat, vbs, cmd) following a GUID-formatted naming convention typically used by the HOOKEDGE installer chain.
This rule detects potentially malicious activity associated with removable media (USB drives) by identifying two distinct patterns: first, the creation of an 'autorun.inf' file on a removable drive followed by the execution of a script or executable from that same drive shortly after. Second, it identifies executables appearing on removable media that are launched across multiple distinct hosts within a one-hour window, which may indicate worm-like spreading or mass-malware distribution via portable storage.
This rule detects activity associated with the exploitation of PaperCut vulnerabilities. It looks for connections to known malicious IP addresses, the presence of specific credential harvesting tools, reconnaissance commands (whoami, tasklist) executed by the PaperCut application (pc-app.exe), suspicious PowerShell downloads of AnyDesk, and unauthorized access to PaperCut configuration files or log files containing known exploit strings.
This rule detects potentially unauthorized process executions (such as shells, network utilities, or enumeration tools) originating from TeamCity server processes (java.exe, javaw.exe). It filters out known TeamCity build agent or maintenance activities to highlight deviations from standard server behavior.
Detects a sequence of events where a user visits a Cloudflare Pages URL (*.pages.dev) and shortly after, a suspicious command (mshta, powershell, or curl) is executed. This pattern is consistent with the UNC5142 threat actor's TTP of using social engineering lures hosted on Cloudflare Pages to trick users into running malicious commands.
This rule monitors for a multi-stage attack pattern involving two potential indicators: first, it identifies phishing emails containing a 'Google Docs' link combined with an attachment named 'API Logic Flaw'. Second, it detects browser activity involving the paste of JavaScript code or suspicious browser clipboard activity, which may indicate an attacker attempting to execute malicious scripts directly in the user's browser context.
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