Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
7,139 detections
Filters
Last updated
All Time
Detection languages
3,217
1,086
504
478
469
Contributors
1,824
1,607
872
505
300
Categories
2,971
2,471
1,060
1,026
908
Platforms
39,762
7,139
6,517
3,851
3,599
Products / Services
1,324
1,067
970
657
487
MITRE Techniques
2,228
1,317
1,314
873
871
CVEs
66
65
33
32
28
IDS Classtypes
81
80
56
27
10
IDS Protocols
149
98
6
5
4
Detects use of Discord webhooks for covert C2 or data exfiltration
This rule detects the download of a standalone Python build for Apple Darwin from astral-sh/python-build-standalone on GitHub using 'curl', followed by its extraction using 'tar'. This activity could indicate a developer setting up a specific Python environment or potentially a malicious actor introducing a custom Python interpreter.
Detects unauthorized access, creation, or modification of sensitive credential and token files (e.g., OAuth tokens, AWS credentials, gcloud tokens) in common user directories like AppData or .config by processes other than established browsers or legitimate cloud CLI tools. This behavior is indicative of credential theft or SaaS pivot attacks.
Detects unauthorized or external access attempts to exposed Ollama API endpoints (port 11434) for generating or chatting, which could be indicative of LLMjacking. The rule identifies requests from known attacker IPs or any external IP, especially if the request count is high.
Correlates processes executing commands containing 'megalodon' with outbound network connections to a specific C2 IP address (216.126.225.129). This rule aims to detect data exfiltration or command and control communication associated with the Megalodon malware.
This rule detects the loading of a machine learning model (e.g., Pickle, PyTorch, or Hugging Face model files) via Python, immediately followed by the creation of a Windows Executable (PE) or Shared Object (.so) file on disk by the same initiating process. This behavior is indicative of an embedded stage-2 loader within a malicious model file, often seen in backdoored Large Language Models (LLMs). The time correlation between the model loading and the file drop is set to 45 seconds to identify immediate post-load execution.
This rule detects a classic malicious model attack chain where a Python process reads a .pkl, .pt, or .bin model file, and immediately spawns an anomalous system shell or execution utility. This indicates potential Remote Code Execution (RCE) via deserialization vulnerabilities in machine learning models.
Identifies web server processes initiating network connections to the credential-stealing generate.2faplugin.org domain. This activity is indicative of a supply chain compromise targeting ShapedPlugin, where backdoored pro plugins are distributed via official channels, leading to data exfiltration.
Correlates the execution of the initial dropper script (setup.cjs) to the hardcoded C2 IPs, indicating potential compromise by the Mastra NPM malware.
Detects MYRA Linux RAT establishing cron-based persistence by scheduling /usr/local/lib/.cache-update.sh to execute every 13 minutes with a fileless fallback chain using memfd_loader and agent_launcher. Indicative of the apintergrationpost npm supply chain attack by threat actor kimijohn01.
Detects MYRA RAT fileless execution where memfd_loader or memfd_exec loads the Node.js binary and JavaScript agent bundle into anonymous memory file descriptors via memfd_create and executes via fexecve. Resulting processes show /proc/PID/exe pointing to '/memfd:.node (deleted)' or '/memfd:.bundle' with no files on disk.
This rule identifies potential ransomware activity by detecting a process performing a high volume of file rename or modification operations within a short time window. It specifically targets files with known ransomware extensions or those using randomized 6-8 character alphanumeric extensions, while excluding common administrative, backup, and temporary file operations performed by trusted software.
Detects the execution of commands used to parse /etc/hosts for PeopleSoft-related node names (WEB, APP, csprd) for lateral movement targeting. Threat actors (e.g., ShinyHunters) use this to discover internal application and web servers.
Detects the execution of commands used to parse /etc/hosts for PeopleSoft-related node names (WEB, APP, csprd) for lateral movement targeting. Threat actors (e.g., ShinyHunters) use this to discover internal application and web servers.
Identifies the execution of MeshCentral for remote command execution.
This rule identifies the execution of MeshCentral for remote command execution, specifically looking for command-line arguments containing 'meshctrl.js' and 'RunCommand'. This activity has been observed in attacks such as those by ShinyHunters to stage payloads on compromised Oracle PeopleSoft servers.
This rule identifies the execution of MeshCentral for remote command execution by looking for specific command-line arguments. It specifically targets instances where 'meshctrl.js' and 'RunCommand' are present in process command lines or syslog messages. This activity has been associated with threat actors like ShinyHunters.
Detects instances where FFmpeg media processing tools spawn interactive shell processes. This behavior is highly indicative of successful remote code execution (RCE) via CVE-2026-8461 (PixelSmash), where an attacker hijacks the AVBuffer struct to call libc's system() function.
Detects the creation of common ransomware note file names with suspicious extensions.
Detects suspicious chmod commands used to hide or protect malware
Detects repeated SSH authentication failures indicating brute force
Page 245 of 340