About
An open index of research on securing generative AI
The GenAI Security Literature Review is a community-driven, auto-updating database of research, standards, tools and resources on the security of large language models and AI systems. It currently tracks 1,386 resources across 46 categories in 8 domains.
How it works
- 01
Auto-discovery
A weekly GitHub Action collects new papers from arXiv, Semantic Scholar and CrossRef and proposes them in a pull request for human review before they are merged into the database.
- 02
Curation
Curated entries are categorized using the taxonomy, mapped to security frameworks (OWASP, NIST, MITRE ATLAS, ISO 42001) and tagged. Automatically added entries get keyword-based categories and stay marked as not yet reviewed until a maintainer vets them.
- 03
Quality signals
Entries marked "reviewed" have been vetted by a human; unreviewed entries carry a badge. Every change to the data is validated against the schema in CI. Citation counts, open-access status and venue help you prioritize what to read.
Coverage
- Attacks & Threats
Offensive techniques and threat vectors targeting LLM and AI systems
- Defenses & Mitigations
Defensive techniques and countermeasures for LLM security
- Privacy
Privacy-preserving techniques and data protection for AI systems
- Governance & Compliance
Policy, regulation, and organizational governance for AI security
- Red Teaming & Evaluation
Offensive security testing and evaluation methodologies for AI
- Infrastructure & Deployment
Secure deployment patterns and infrastructure security for AI systems
- Agentic AI Security
Security specific to autonomous AI agents and multi-agent systems
Framework mappings
Entries are mapped, where applicable, to these frameworks:
- OWASP Top 10 for LLM Applications
- The most widely adopted LLM security risk list
- OWASP Top 10 for Agentic Applications
- Security risks specific to autonomous AI agents
- MITRE ATLAS
- Adversarial tactics, techniques and case studies for AI systems
- NIST AI RMF
- The US government's AI risk management framework
- ISO/IEC 42001
- International standard for AI management systems
Download the dataset
The full database is available for analysis, citation managers and systematic reviews. Files are regenerated on every deploy.
| Format | All entries (1,386) | Reviewed only (95) |
|---|---|---|
| JSON complete records | literature.json | filter on reviewed |
| CSV spreadsheets, pandas | literature.csv | literature-reviewed.csv |
| BibTeX Zotero, LaTeX | literature.bib | literature-reviewed.bib |
1,291 entries have reviewed: false: they were added automatically from academic APIs and have not been curated yet. Licensed under MIT; citation keys match the BibTeX shown on each entry page.
Contribute
Suggest a paper, tool or standard, or report a correction on GitHub.
Maintainer
Emmanuel Guilherme (@emmanuelgjr), OWASP contributor and GenAI data security researcher. Licensed under the MIT License.