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shiva108
165 lines
5.7 KiB
Markdown
165 lines
5.7 KiB
Markdown
# AI / LLM Red Team Field Manual & Consultant's Handbook
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A comprehensive operational toolkit for conducting **AI/LLM red team assessments** on Large Language Models, AI agents, RAG pipelines, and AI-enabled applications. This repository provides both tactical field guidance and strategic consulting frameworks.
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📖 **GitBook Navigation:** See [SUMMARY.md](docs/SUMMARY.md) for the complete chapter structure.
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---
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## 📚 Overview
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This repository represents the **Gold Master** release of the AI LLM Red Team Handbook. It contains a fully standardized, 46-chapter curriculum covering the entire spectrum of AI security—from prompt injection and jailbreaking to adversarial machine learning and federated learning attacks.
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### Core Resources
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1. **AI LLM Red Team Handbook** (46 Chapters, Completed)
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- Professional consultancy guide with standardized metadata, abstracts, and navigation.
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- Covers Ethics, Architectures, RAG Security, Agentic Threats, and Compliance (EU AI Act/ISO 42001).
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2. **AI LLM Red Team Field Manual**
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- Compact operational reference for field use (checklists, payloads, methodology).
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3. **Python Testing Framework** (`scripts/`)
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- Automated suites for prompt injection, fuzzing, and safety validation.
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---
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## 📁 Repository Structure
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```text
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ai-llm-red-team-handbook/
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├── docs/ # The Handbook (Chapters 01-46)
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│ ├── archive/ # Historical versions
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│ ├── assets/ # Diagrams, charts, and visual aids
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│ ├── field_manuals/ # Operational checklists and quick-refs
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│ ├── templates/ # Report and SOW templates
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│ └── SUMMARY.md # Master Table of Contents
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├── scripts/ # Automated testing tools (Python)
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├── workflows/ # CI/CD and automation workflows
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├── .agent/ # Agentic memory and context
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├── LICENSE # CC BY-SA 4.0 License
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└── README.md # This file
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```
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---
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## 🚀 Installation & Usage
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### 1. Manual Exploration (The Handbook)
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The primary way to use this repository is as a reference.
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- Start at [SUMMARY.md](docs/SUMMARY.md) to browse all chapters.
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- View the [Field Manual](docs/AI_LLM%20Red%20Team%20Field%20Manual.md) for quick lookups during an engagement.
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### 2. Automated Testing Environment
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To run the provided Python scanning and fuzzing scripts:
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**Prerequisites:**
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- Python 3.8+
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- API Access to a target LLM (OpenAI, Anthropic, or local Ollama)
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**Setup:**
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```bash
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# Clone the repository
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git clone https://github.com/shiva108/ai-llm-red-team-handbook.git
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cd ai-llm-red-team-handbook
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# Install dependencies
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cd scripts
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pip install -r config/requirements.txt
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```
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**Running Tests:**
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```bash
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# Set up your environment variables (API Keys)
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cp .env.example .env
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nano .env
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# Run the test runner
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python examples/runner.py --target "gpt-4" --test "prompt_injection"
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```
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---
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## 📖 Chapter Roadmap (Completed)
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This handbook is divided into 8 strategic parts. All chapters are now **complete** and audited.
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### Part I: Professional Foundations
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- **Ch 01-04:** Introduction, Ethics, Mindset, Rules of Engagement.
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### Part II: Project Preparation
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- **Ch 05-08:** Threat Modeling, Scoping, Lab Setup, Chain of Custody.
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### Part III: Technical Fundamentals
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- **Ch 09-11:** LLM Architectures, Tokens, Plugins/APIs.
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### Part IV: Pipeline Security
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- **Ch 12-13:** RAG Pipelines, Supply Chain Security.
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### Part V: Attacks & Techniques
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- **Ch 14-24:** Prompt Injection, Data Leakage, Jailbreaking, API Exploitation, Evasion, Poisoning, Model Theft, DoS, Multimodal, Social Engineering.
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### Part VI: Defense & Mitigation
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- **Ch 25-30:** Adversarial ML, Supply Chain Defense, Federated Learning, Privacy, Model Inversion, Backdoors.
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### Part VII: Advanced Operations
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- **Ch 31-39:** Reconnaissance, Attack Frameworks, Automation, Defense Evasion, Post-Exploitation, Reporting, Remediation, Continuous Red Teaming, Bug Bounties.
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### Part VIII: Advanced Topics
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- **Ch 40-46:** Compliance (EU AI Act), Industry Best Practices, Case Studies, Future of Red Teaming, Emerging Threats, Program Building, Conclusion.
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---
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## 🤝 Contributing
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We welcome contributions to keep this handbook living and breathing.
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1. **Fork** the repository.
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2. **Create** a feature branch (`git checkout -b feature/new-jailbreak`).
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3. **Submit** a Pull Request with a clear description of the change.
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4. Please ensure all new content follows the **Chapter Template** in `docs/templates/`.
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---
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## ⚠️ Disclaimer
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**For Authorized Security Testing Only.**
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The techniques and tools described in this repository are for educational purposes and for use by authorized security professionals to test systems they own or have explicit permission to test.
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- **Do not** use these tools on public LLMs (e.g., ChatGPT, Claude) without complying with their Terms of Service.
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- **Do not** use these techniques for malicious purposes.
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The authors and contributors accept no liability for misuse of this material.
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---
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## 📬 Contact
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- **Issues:** [GitHub Issues](https://github.com/shiva108/ai-llm-red-team-handbook/issues)
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- **License:** [CC BY-SA 4.0](LICENSE)
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---
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**Version:** 1.46.263
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