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GenAI Security Literature Review

Validate Data Deploy Webapp Fetch Papers License: MIT

A comprehensive, community-driven, auto-updating literature review of GenAI and LLM security research, standards, tools, and resources. Currently tracking 100 resources across 42 categories with weekly automated updates from academic APIs.

Browse the Interactive Webapp

What's Inside

This repository maintains a curated and continuously growing database of GenAI/LLM security resources spanning:

Categories

Domain Topics
Attacks & Threats Prompt injection, jailbreaking, data poisoning, model extraction, membership inference, adversarial examples, supply chain, social engineering, agentic threats
Defenses & Mitigations Input filtering, output moderation, guardrails, access control, monitoring, sandboxing, cryptographic controls, watermarking
Privacy Differential privacy, federated learning, data anonymization, machine unlearning, confidential computing
Governance & Compliance Risk frameworks (NIST, ISO, EU AI Act), model governance, audit & assurance, responsible AI, incident response
Red Teaming & Evaluation Red teaming methodology, safety benchmarks, LLM fuzzing, vulnerability disclosure
Infrastructure & Deployment Model serving security, RAG security, fine-tuning security, MLOps, cloud AI security
Agentic AI Security Agent architecture, tool-use security, memory security, human-in-the-loop, autonomous operations
Surveys & Meta Literature surveys, threat modeling, industry reports, books, conference proceedings

Framework Mappings

Every entry is mapped (where applicable) to:

  • OWASP Top 10 for LLM Applications
  • OWASP Top 10 for Agentic AI
  • MITRE ATLAS (Adversarial Threat Landscape for AI Systems)
  • NIST AI Risk Management Framework
  • ISO/IEC 42001 (AI Management System)

How It Works

Auto-Discovery

A weekly GitHub Action queries academic APIs (arXiv, Semantic Scholar, CrossRef) for new GenAI security publications. New entries are submitted as pull requests for human review before merging.

Community Contributions

Anyone can submit resources via GitHub Issues or pull requests. See CONTRIBUTING.md for details.

Interactive Webapp

The static webapp (deployed to GitHub Pages) provides:

  • Full-text fuzzy search across all entries
  • Color-coded category browsing by domain
  • Filter by type, year, framework mapping, and review status
  • Framework mapping explorer (OWASP, NIST, MITRE, ISO)
  • Individual entry detail pages with BibTeX citation export

Repository Structure

data/
  literature.json      # Core database (100 curated entries)
  taxonomy.json        # 8 domains, 42 category definitions
  frameworks.json      # OWASP/NIST/MITRE/ISO framework definitions
  sources.json         # Automation source configuration
schemas/               # JSON Schema for data validation
scripts/               # Python automation (fetch, dedup, validate)
webapp/                # Astro static site (Preact + Tailwind)
.github/workflows/     # CI/CD (validation, weekly fetch, deploy)

Quick Start

Browse Online

Visit the Interactive Webapp -- no installation needed.

Run Locally

git clone https://github.com/emmanuelgjr/GenAI-Security-Literature-Review.git
cd GenAI-Security-Literature-Review

# Run the webapp
cd webapp
npm install
npm run dev

Validate Data

pip install -r scripts/requirements.txt
python scripts/validate_data.py

Contributing

We welcome contributions of all kinds -- new papers, tools, corrections, framework mappings, and webapp improvements. See CONTRIBUTING.md.

License

This work is licensed under the MIT License.

Maintainer

Emmanuel Guilherme (@emmanuelgjr) -- OWASP contributor, GenAI data security researcher.

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