Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
40,063 detections
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Detects rapid, multi-category reconnaissance activity initiated by AI-agent binaries (e.g., Claude, Cursor, ChatGPT). The rule identifies sessions that perform four or more distinct discovery operations—spanning account, network service, system information, and network configuration discovery—within a short time window, indicating potentially malicious autonomous exploration by an AI agent. Covers T1046, T1087, T1083, T1016
Detects rapid, machine-speed, sequential attack-path adaptation by suspected AI agent binaries. The rule monitors for a correlation of four stages occurring within a tight 20-minute window: 1) Failed service connections across three or more distinct protocols (SMB, SSH, HTTP, RDP, WinRM), 2) Credential access attempts (Logon events or execution of known credential-dumping tools), and 3) A lateral movement pivot to a new, previously un-targeted internal destination. The rule specifically keys on the InitiatingProcessId and InitiatingProcessCreationTime to ensure the sequence is attributed to a single process instance, distinguishing it from human manual penetration testing activity. Covers T1190, T1210, T1078
Detects anomalous multi-agent chaining where one AI-enabled agent instance initiates a connection to an AI API and subsequently hands off information to a second, distinct agent instance, which then performs an suspicious downstream action such as spawning a shell or initiating an unauthorized external network connection. This behavior is intended to identify potential abuse of AI-coding assistant tools for automated execution chains.
Detects the presence or execution of files associated with the 'MacSync' malware family, based on a list of known MD5 file hashes.
Detects the presence or execution of files associated with the 'MacSync' malware family, based on a list of known MD5 file hashes.
Detects the presence or execution of files associated with the 'MacSync' malware family, based on a list of known MD5 file hashes.
This rule detects modifications or creation of Git hooks ('pre-commit', 'post-checkout') within local repository directories. Attackers can leverage these hooks as an execution trigger for arbitrary code whenever standard Git actions occur, facilitating persistence or privilege escalation on compromised developer machines.
Detects outbound network connections to domains, URLs, and IP:Port combinations identified as malicious in the ThreatFox OSINT feed. This rule covers various commodity malware C2 and payload delivery infrastructure.
Detects the loading of radcui.dll from the non-standard %LOCALAPPDATA%\Microsoft\RemoteApp\Gateway\ directory. This behavior is associated with DLL sideloading chains where signed Microsoft binaries (such as wkspbroker.exe) are abused to load malicious payloads, often seen in the PREY-0058/Aur0ra Teams vishing campaigns.
Detects instances where a Node.js process spawns another Node.js process to execute a JavaScript file located within the node_modules directory. This pattern is commonly observed when malware or malicious scripts attempt to execute payloads from within project dependencies, potentially hiding malicious activity within seemingly legitimate library paths.
This rule detects potentially malicious activity involving Node.js modules. It monitors for the deletion of specific 'sharedLoad.min.js' or 'extended' files within 'node_modules' directories, the execution of Node.js processes attempting file deletion operations (like 'unlink' or 'rm') within 'node_modules', and the creation or modification of JavaScript files within 'node_modules' that contain 'btree' references. This activity may indicate an attempt to tamper with application dependencies, inject malicious code, or remove artifacts.
Detects execution of Node.js processes loading specifically named JavaScript files ('sharedLoad.min.js') within the 'node_modules/indexed-btree' directory, or file modifications involving these specific paths, which may indicate a malicious loader or supply chain compromise attempt.
This rule detects instances where a Node.js process spawns a child process, also running as node.exe, that attempts to execute a specific JavaScript file path (sharedLoad.min.js or its extended version). This behavior is characteristic of certain Node.js-based applications or potentially malicious scripts using shared loaders for modular execution.
Detects the execution of the AnyDesk remote support application when initiated from a web browser (msedge.exe) or the Windows file explorer (explorer.exe). This pattern is often indicative of user-driven execution, potentially as part of a tech support scam or unauthorized remote access attempt.
Detects a Node.js process deleting specific core application files, such as 'index.js' or 'sharedLoad.min.js', located within 'node_modules' directories. This activity may indicate malicious tampering, package integrity compromise, or an adversary attempting to disrupt application functionality.
Detects the SCKit Go-based credential-stealing implant found in compromised npm and PyPI packages. The detection logic focuses on unique build-info module paths, specific C2 encryption protocol headers, and embedded campaign identifiers related to 'memos-cloud-openclaw-plugin' and 'MemoryOS' supply chain compromises.
This rule monitors application, build system, and dependency scanning logs for references to known-malicious versions of the @memtensor/memos-cloud-openclaw-plugin (npm) and MemoryOS (PyPI) packages. These versions contain the sckit Go worm and are associated with automated supply chain attacks involving the reuse of stolen credentials, indicated by the 'exact-ref-one-use-NPM_TOKEN' marker.
Detects npm package publish events that lack 'gitHead' provenance metadata. The absence of this field indicates that the package was likely published from a developer's local machine rather than through an authorized CI/CD pipeline, a technique used in supply chain attacks to bypass CI-gated controls.
Detects execution of 'clspack.exe' from within the user's AppData directory. This location is frequently used by adversaries to stage and execute malicious binaries to evade detection, as it is outside of typical system directories like System32 or SysWOW64 where trusted system binaries are expected.
Detects the execution of rundll32.exe with the '/sta' command line argument followed by a CLSID. This behavior leverages the IShellRunDll COM interface to execute registered objects, bypassing the standard requirement of providing a DLL path and exported function name. This method is often used by adversaries to execute malicious code while blending in with legitimate system processes.
This rule detects potentially malicious file execution by monitoring for the usage of .pif files, often disguised as image files or documents, which subsequently launch suspicious child processes such as msiexec, wscript, cscript, or rundll32. The detection logic matches on specific parent processes (e.g., browsers, email clients, file explorers) triggering the file, followed by suspicious command line arguments within a 10-minute window.
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