Marble - the real time decision engine for fraud and AML
A free and open platform for detecting and preventing email attacks like BEC, malware, and credential phishing. Gain visibility and control, hunt for advanced threats, collaborate with the community, and write detections-as-code.
The Threat Hunting In Rapid Iterations (THIRI) Jupyter notebook is designed as a research aide to let you rapidly prototype threat hunting rules.
The Web Exploit Detector is a Node.js application used to detect possible infections, malicious code and suspicious files in web hosting environments
Hunting Queries for Defender ATP
CVE proof-of-concept labs, exploit scripts, and detection/prevention rules (Nginx, Apache, Snort, YARA) for high-severity CVEs. Authorized security testing & research only.
Sigma detection rules for hunting with the threathunting-keywords project
Microsoft Sentinel, Defender for Endpoint - KQL Detection Packs
Microsoft Sentinel SIEM Log Source Analyzer
Curated Linux LPE corpus — 28 modules from 2016 to 2026, with detection rules. One command, safest-first root: skeletonkey --auto --i-know
Check Sigma rules for easy-to-bypass whitelists to make them more robust (https://github.com/SigmaHQ/sigma)
32 production-quality KQL detection rules for Microsoft Sentinel, mapped to MITRE ATT&CK for Cloud, credential access, lateral movement, exfiltration, defense evasion, and more
A userscript that enhances the SentinelOne PowerQuery interface with a custom threat hunting button that follow the website UI / UX design interface.
Sigma detections for real ATT&CK techniques, compiled to Wazuh, Splunk and Sentinel from one source. 67 rules, 64 techniques, Windows + Linux, ATT&CK Navigator layer, MIT.
Huntable CTI Studio is an AI-assisted cyber threat intelligence workbench that turns open-source CTI into Sigma rules.
A command line tool that takes a txt file containing threat intelligence and turns it into a detection rule.
Docker Container for Elastic Detection CLI
A collection of custom-built dashboards for threat hunting.
The project utilizes of a wazuh-manager installed on WSL or a Linux machine, allowing testing custom rules locally before moving to production.
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