Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
7,138 detections
Filters
Last updated
All Time
Detection languages
3,224
1,086
498
476
469
Contributors
1,824
1,607
872
505
300
Categories
2,976
2,470
1,061
1,024
908
Platforms
39,790
7,138
6,515
3,861
3,597
Products / Services
1,325
1,067
970
655
490
MITRE Techniques
2,227
1,319
1,319
874
873
CVEs
66
65
33
32
28
IDS Classtypes
81
79
56
27
10
IDS Protocols
149
98
6
5
4
Detects unauthorized creation or modification of AI agent system prompts, guardrails, or policy configuration files. This rule monitors for changes made by processes or users other than those identified as authorized CI/CD deployment agents or service accounts, helping to prevent unauthorized tampering with AI agent behavior or safety policies.
Identifies suspicious processes performing beacon-like network communications with rare external destinations. The rule detects consistent hourly activity intervals and high connection counts to endpoints rarely contacted by other devices in the organization, serving as a heuristic for automated C2 beaconing.
Detects when an AI agent's code execution sandbox (e.g., Python, Node.js, or Shell interpreters) initiates suspicious child processes. This includes the execution of network utilities for potential C2 (e.g., curl, nc, socat), the creation of interactive reverse shells, or the execution of credential harvesting tools (e.g., mimikatz, secretsdump), which suggests the AI agent's sandbox environment has been compromised or abused.
Detects unauthorized processes attempting to read sensitive wallet extension storage files or desktop application wallet data folders, a behavior characteristic of the Psychedelic Stealer malware designed to harvest cryptocurrency credentials prior to exfiltration.
Detects instances where a Python process spawns a command-line shell (cmd.exe, powershell.exe, or bash) within 15 seconds of starting, while executing common reconnaissance or utility commands. This behavior is indicative of malicious code executing at import-time, a technique often associated with supply chain compromises in Python packages.
This rule detects potential persistence via Python environment variable manipulation (PYTHONPATH) followed by suspicious network activity from a child process of python.exe. It specifically looks for the modification of the PYTHONPATH environment variable using PowerShell on Windows or shell configuration files on Unix-like systems, followed by a python.exe-initiated network connection (like curl) to external domains, which may indicate the execution of a malicious sitecustomize.py hook.
Detects attempts to redirect Python package resolution away from the default PyPI index. This is achieved by monitoring pip CLI arguments (--index-url, --extra-index-url), environment variables (PIP_INDEX_URL, PIP_EXTRA_INDEX_URL, PIP_CONFIG_FILE), or the creation/modification of pip configuration files (pip.conf, pip.ini). Such activity is often associated with software supply chain attacks where an adversary attempts to force the installation of malicious packages from a controlled repository.
This rule monitors the software inventory for vulnerable versions of OpenSSL and WolfSSL libraries. Specifically, it flags instances of WolfSSL prior to version 5.9.4, which are susceptible to peer-authentication bypass vulnerabilities. The rule is intended for patch management and asset exposure tracking rather than detecting active exploitation.
This rule detects a node.exe process initiating a network connection to a specific remote IP (69.48.229.140) on port 8080, followed by the termination of that same process within 45 seconds of the connection. This behavior is indicative of a short-lived beaconing process or an ephemeral network task associated with command-and-control activity.
Detects network activity associated with a malicious NPM package (typosquatting) beaconing to a known C2 server (69.48.229.140) and performing command and control operations, including command polling and data exfiltration, specifically from a Node.js environment.
Detects the execution of known Python scripts (CES_Enroll.py, ntlm_ces_relay.py, ces_negotiate_ntlm.py) often associated with NTLM relay attacks or forced authentication techniques. These scripts leverage Python to interact with authentication protocols or relay requests.
Detects the creation or modification of scheduled tasks (crontab entries) initiated by processes commonly associated with Citrix NetScaler ADC/Gateway appliances (nsppe, httpd, nscollect). This behavior is often indicative of persistence mechanisms used by attackers following an initial exploit on an edge network device.
Detects suspicious child processes such as shell interpreters, download utilities, and base64-decoded commands spawned from core Citrix NetScaler processes (nsppe, httpd, aoacli, nscli). This pattern is often indicative of post-exploitation command execution following an exploitation of remote code execution (RCE) vulnerabilities.
This rule detects potential anti-forensic activity on Citrix ADC/NetScaler devices by monitoring for two primary indicators of log tampering: an unexpected drop in syslog volume to zero following a period of activity, or the execution of explicit commands intended to clear audit logs and configuration files.
Detects the creation, modification, or renaming of common JSP web shell filenames (x.jsp, u.jsp, u2.jsp) within known web application directories (e.g., webapps, Peoplesoft, WebLogic). This pattern is indicative of an adversary attempting to establish a web shell for persistent access or command execution on a vulnerable web server.
Detects an suspicious progression of activities originating from identified AI assistant/agent processes. The rule monitors for a chain of behaviors occurring within a 15-minute window: execution of an AI agent/tool, followed by host discovery (network/system enumeration), access to sensitive local credential files, archival of data, and outbound network communication to common file-sharing/exfiltration platforms.
This rule detects the execution or presence of specific Go or Terraform modules known to be malicious or associated with suspicious dependency retrieval. It monitors command-line activity from terraform.exe/go.exe attempting to download/run from these paths, as well as file system events involving these specific folder paths and filenames.
This rule monitors package installation logs for indicators of packages potentially generated or suggested by AI tools (e.g., Copilot, code assistants) being installed in a target environment. It specifically looks for a low volume of installations (<=3) for packages that have been published within the last 14 days, which is a pattern often associated with the 'Publish Hallucinated Entities' technique in AI systems, where malicious or hallucinated code packages are introduced into the supply chain.
Detects a sequential pattern where a browser process (Chrome, Edge, or Safari) accesses an AI chat platform's conversation API, followed within 5 minutes by a network connection to a known unauthorized exfiltration destination (api.pbapi.xyz). This pattern suggests the potential use of a browser-based tool or extension (e.g., Poper Blocker or similar) to intercept and exfiltrate AI chat history.
Detects DNS lookups and outbound network connections to known command and control (C2) and staging domains associated with the STAC4924 campaign. The rule performs strict matching on domain names to ensure that subdomains are identified while avoiding false positives from partial string matches within URLs.
High-fidelity correlation of OS-DET-LNX-005 and OS-DET-LNX-006: a system shell copied to a
non-standard/writable path, followed within 15 minutes on the same host by execution of a
shell with the privilege-preserving -p flag from a non-standard path. The two events
together are a near-certain SUID-root shell misconfiguration abuse (bash -p to root) and a
lower-FP signal than either component alone. Detection logic adapted from Elastic Security Labs.
non-standard/writable path, followed within 15 minutes on the same host by execution of a
shell with the privilege-preserving -p flag from a non-standard path. The two events
together are a near-certain SUID-root shell misconfiguration abuse (bash -p to root) and a
lower-FP signal than either component alone. Detection logic adapted from Elastic Security Labs.
Page 21 of 340