Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
7,143 detections
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Detects AI coding agents (such as Claude Code, Cursor, Copilot CLI, etc.) spawning shell interpreters (bash, cmd, powershell) to execute installation or configuration scripts from within git-cloned repository directories. This activity is indicative of indirect prompt injection attacks where an adversary manipulates the agent into autonomously running malicious setup code.
Detects unauthorized modifications to SSH 'authorized_keys' files or the '/etc/ssh/sshd_config' configuration file on Linux systems. These actions can be used for persistent access (key injection) or to weaken SSH security controls (e.g., enabling root login) and are typical indicators of account manipulation or compromise.
Detects processes attempting to connect to the Cloud Instance Metadata Service (IMDS) IP address (169.254.169.254) or referencing it in the command line. This behavior is often associated with credential theft or reconnaissance on cloud instances.
This rule detects suspicious activity related to GitHub Actions workflows, including the creation or modification of workflow configuration files, the placement of suspicious JavaScript files in the repository's .github directory, the execution of the 'Bun' runtime within an Actions runner environment, and cloud-based events indicating workflow modification containing 'Run Copilot' strings. These patterns are often associated with CI/CD pipeline compromise, malicious automation, or unauthorized code execution within build environments.
Detects the execution of the libpwn_cve_2026_55200_server.py Python script, which is identified as a malicious SSH scaffold targeting CVE-2026-55200. This script facilitates exploitation of libssh2 clients by binding to a specific port and delivering malformed packets during the pre-authentication phase.
Detects the execution of Python interpreters spawned by code editors or runtime environments (e.g., VS Code, Cursor, Node.js) with specific command-line arguments involving 'init'. This behavior may indicate an adversary attempting to leverage development tools to execute custom scripts, potentially for automated deployment, persistence, or malicious payload initialization.
This rule detects the execution of python.exe or python3.exe using the '-m init' command line flag while attempting to establish a network connection over specific, often non-standard, ports (4444, 1337, 9001, 9002, 5555, 6666, 7777, 8888). This pattern is commonly associated with reverse shells or C2 agent check-ins initiated via Python scripts.
Detects when the node.js runtime process accesses Docker configuration files, which may contain sensitive authentication credentials or registry settings. This behavior is atypical for standard node.js applications and could indicate credential theft or unauthorized container environment interaction.
Detects a fileless execution technique used by the MYRA Linux RAT where a payload is executed from memory using memfd_create and fexecve, effectively bypassing disk-based detection. The rule identifies processes originating from Node.js or npm installation scripts that exhibit anonymous, memory-backed execution paths typical of this malware's lifecycle.
Detects node.exe processes or file operations involving suspicious strings like 'piterpan', 'pmtrader', or 'DEFAULT_USERNAME_TAG', which are associated with malicious activity or unauthorized staging of scripts within the node environment.
Detects Node.js runtime instances interacting with multiple sensitive developer configuration and credential files (e.g., .gitconfig, GitHub CLI host tokens, Claude configuration, git-credentials) in a single session. This pattern is consistent with infostealer malware (such as Miasma/MYRA) attempting to harvest developer credentials for downstream exploitation.
This rule detects persistence mechanisms and fileless execution patterns commonly associated with the MYRA malware family on Linux systems. It specifically monitors for malicious cron job creation, LD_PRELOAD library manipulation, unauthorized shell profile modifications, and memfd-based execution spawned from Node.js or npm processes.
Detects instances of a Node.js process accessing sensitive browser credential and cookie storage files, which is a common behavior associated with credential theft malware or malicious scripts.
Detects nmap processes performing IPv6 scans (using flags such as -6) that result in abnormal process termination or the spawning of unexpected child processes (e.g., cmd.exe, sh, bash). This behavior is indicative of exploitation attempts targeting the nmap IPv6 extension header length integer wrap vulnerability, including the execution of associated PoC harness binaries.
Detects high volumes of file operations (creation, rename, or modification) where files are given extensions typically associated with ransomware (e.g., .locked, .encrypted). The rule aggregates activity by process and endpoint and triggers an alert when the number of such operations exceeds a defined threshold, while excluding known legitimate backup and security software.
Detects multiple processes accessing sensitive browser data files like 'Local State' and 'Login Data', commonly associated with credential theft activities from web browsers.
Detects the execution of the 'fortigatesniffer' binary, which is often associated with packet capture and network reconnaissance activities on a host.
Detects instances where language-related processes (amazonq-language-server, node) or common tools (bash, sh, curl, aws) execute commands containing AWS access credentials or perform potential data exfiltration via curl POST requests.
Detects execution patterns associated with CVE-2026-46331 (pedit COW exploit), which uses a user namespace unshare operation, followed by tc pedit action abuse to perform page cache poisoning on /bin/su to achieve root privilege escalation. The rule monitors for the exploit binary, unshare namespace creation, tc command interaction, unauthorized root shell spawning by su/sudo, and attempts to clear page caches.
Detects execution and compilation activities associated with the DirtyPipe (CVE-2022-0847) vulnerability, which allows an unprivileged user to overwrite data in read-only files, leading to privilege escalation to root. The rule tracks common exploit filenames, compilation patterns, and specific commands used for privilege escalation via unshare or su.
This rule detects network communication (connections, DNS queries, or proxy logs) between endpoints and a list of known malicious domains and IP addresses associated with Mistic and Woodgnat/KongTuke threat families. It identifies these activities across network event logs, DNS queries, and security logs.
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