Awesome Threat Detection is a curated list of threat detection and hunting resources organized across tools, detection rules, datasets, frameworks, research materials, and training content.
The project addresses the challenge of discovering and organizing the fragmented landscape of threat detection tooling and knowledge. It works by maintaining a structured index that categorizes resources across multiple dimensions: detection platforms and automation tools, endpoint and network monitoring solutions, detection rule repositories, datasets for testing and research, educational frameworks for Windows and macOS systems, data science approaches, research papers, blogs, podcasts, newsletters, videos, and hands-on labs. This organization allows security practitioners to navigate from high-level platform choices down to specific detection techniques and learning materials.
Teams building detection capabilities should use this list as a reference when evaluating tools and approaches for their environment. It suits organizations establishing or expanding threat detection programs, incident response teams seeking hunting resources, and security engineers researching detection methodologies. The breadth of coverage spans from commercial detection platforms to open-source tools, from endpoint-focused monitoring to network-based approaches, and from practical labs to academic research, making it useful across different organizational maturity levels and budgets.
The project maintains an active curation model with regular updates to reflect new tools and resources entering the threat detection space. Contributions are welcomed through a documented process, indicating ongoing community engagement with the list's evolution. The resource maintains comprehensive coverage across multiple detection domains rather than focusing narrowly on any single tool or approach.
