Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects Python deleting runtime scripts, compiled modules, screenshots, and credential archives from temporary or profile paths. This rule specifically looks for file deletion or creation events where the target file matches common Python script/module extensions (.py, .pyc, .pyd, .so) or archive/image extensions (.zip, .7z, .png, .jpg) within temporary or user profile directories, and the process responsible is identified as Python.
Udm Ghost Dynamic Js
YARA-L
Targets JavaScript containing atob decoding, dynamic appendChild, and one-time localStorage keys. The UDM rule retains principal and target context for correlation.
Detects a small Go-based scanner, identified by its renamed executable 'go.exe', when launched with command-line arguments indicative of broad network scanning activities such as CIDR range specifications (/16, /24), service discovery, or exploit module usage. This behavior is often associated with initial access or reconnaissance phases by adversaries.
This rule detects processes generating network connections to multiple known malicious ports (4444, 7211, 8000, 8001, 8002, 10000) within a 30-minute window. This behavior is indicative of command and control (C2) beaconing, where a compromised system periodically communicates with a C2 server. The rule is designed to identify a pattern of C2 activity that might be used across different threat campaigns, leveraging ports commonly associated with various C2 frameworks or custom C2 implementations.
Detects curl commands transmitting harvested GitHub tokens (ghp_ prefix) in the request body, representing the final exfiltration stage of gh-token-monitor.
Detects vLLM spawning download utilities like curl or wget to pull secondary payloads post-exploitation, potentially indicating a compromise related to CVE-2026-22778.
Detects Linux execution environments where processes manually manipulate their argv[0] to masquerade as kernel threads ([khubd]) or legitimate daemons (smbd -D). The rule specifically looks for process command lines matching 'khubd', 'smbd -D', or 'kauditd -sh' where the actual executable filename is not 'smbd', 'kauditd', or 'khubd'.
Hunts for the creation of hidden keylogger output files formatted with MD5 hashes (s<MD5> or c<MD5>) within the deceptive /usr/share/man9/ph/ directory, as observed in Velvet Ant activity.
Detects suspicious execution of command-line tools like curl, wget, or PowerShell to query OAuth/token-related endpoints (e.g., /token, oauth, access_token). The rule filters out expected parent processes (e.g., shells, IDEs, common build tools) to identify potentially malicious attempts to steal application access tokens.
Detects rclone remote configuration or config file creation when the binary is running from a portable user writable location, such as Downloads, Temp, AppData, Desktop, /tmp/, or /var/tmp/. This activity can indicate an attempt to exfiltrate data to cloud storage services.
This rule monitors system logs for attempts to disable or stop the Linux Audit daemon (auditd) or modify its configuration via auditctl or system management commands (systemctl, service). Disabling the audit system is a common technique used by adversaries to hide malicious activity from security monitoring.
Detects CI/CD runner agents calling 'aws configure list-profiles' and connecting to a known malicious IP address (216.126.225.129), as prescribed by the Megalodon CI/CD malware.
Detects suspicious cron utility activity, including modifications or executions, with specific indicators associated with the MYRA malware family. This rule identifies attempts to establish persistence or execute malicious code via scheduled tasks on Linux systems.
Detects the execution of curl commands that involve base64 decoding, often used by adversaries to download and execute obfuscated scripts or payloads. The rule specifically looks for common shell utilities (curl, zsh, bash, sh) executing commands containing 'base64 --decode' and 'curl', along with specific suspicious domains or a generic base64 encoded string pattern.
This rule monitors system logs for attempts to disable or stop the Linux Audit daemon (auditd) or modify its configuration via auditctl or system management commands (systemctl, service). Disabling the audit system is a common technique used by adversaries to hide malicious activity from security monitoring.
This rule identifies newly created PHP files within specific WordPress plugin folders ("woocommerce-subscription" or "woocommerce-notification") that have a rare SHA256 hash count (less than 5 occurrences in the enterprise). This behavior is indicative of web shells or backdoored plugin files, potentially introduced via a supply chain compromise.
Correlates a non-browser headless runtime (Node/Bun) querying the GitHub API for the specific commit 'OhNoWhatsGoingOnWithGitHub'. This could indicate a supply chain attack where malicious code within a Node.js or Bun.js application attempts to communicate with a GitHub dead drop for command and control or data exfiltration.
This rule detects the execution of JavaScript files named 'bw_setup.js' or 'execution.js' using the 'bun' runtime, immediately followed by an outbound network connection to the command and control (C2) domain 't.m-kosche.com'. The detection logic correlates process execution events with network connection events within a 10-minute window, indicating potential malicious activity associated with supply chain attacks.
This query detects the creation of local user accounts on Linux systems using the 'useradd' or 'adduser' commands. Monitoring for local account creation is crucial as adversaries may create accounts for persistence, privilege escalation, or to facilitate lateral movement.
Detects interaction with the WordPress Theme Editor utility immediately followed by a file modification to functions.php, indicative of the ErrTraffic deployment phase. This activity can be a sign of web shell deployment or other malicious code injection.
Detects the use of `wget` or `curl` to specifically target a GitHub API endpoint with a suspicious string, indicating an attempt to download initial stage malware or tools from a dead drop. This pattern is associated with supply chain attacks where GitHub is used as a temporary hosting for malicious components.
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