AI / LLM Red Team Field Manual & Consultant's Handbook

A complete operational toolkit for conducting AI/LLM red team assessments on Large Language Models, AI agents, RAG pipelines, and AI-enabled applications.

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Quick Start

# Clone the repository
git clone https://github.com/shiva108/ai-llm-red-team-handbook.git
cd ai-llm-red-team-handbook

# Manual testing: Open docs/AI_LLM Red Team Field Manual.md

# Automated testing:
cd scripts
pip install -r requirements.txt
python runner.py --config config.py

📖 Detailed setup: See Configuration Guide

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Repository Contents

Resource	Description
Field Manual	Compact operational reference with attack prompts, tooling, OWASP/MITRE mappings
Handbook	Full consultancy guide with methodology, threat modeling, RoE/SOW templates
Building AI Red Teams	Strategic guide for building security teams
Report Template	Client-ready assessment report template
Python Framework	Automated testing suite for prompt injection, jailbreaks, data leakage, tool misuse

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Prerequisites

Manual Testing: Any text editor + target LLM access

Automated Testing:

• Python 3.8+
• Dependencies: requests, pytest, pydantic, python-dotenv
• API credentials for target LLM

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Python Testing Framework

Test Suites

• test_prompt_injection.py - Automated prompt injection attacks
• test_safety_bypass.py - Jailbreak and guardrail bypass tests
• test_data_exposure.py - Data leakage and PII extraction
• test_tool_misuse.py - Function-calling and plugin abuse
• test_fuzzing.py - Adversarial input fuzzing
• test_integrity.py - Model integrity and consistency

Configuration

Create scripts/.env:

API_ENDPOINT=https://api.example.com/v1/chat/completions
API_KEY=your-secret-api-key
MODEL_NAME=gpt-4

Run tests:

python runner.py                           # All tests
python runner.py --test prompt_injection   # Specific test
python runner.py --verbose                 # Verbose output

📖 Full configuration options: Configuration Guide

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Use Cases

Red Team Engagements: Use Field Manual attack prompts and Python framework for assessments

Training: Leverage Handbook for onboarding and team development

Client Work: Export PDFs for proposals and methodology documents

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Roadmap

Planned:

• Sample RAG and LLM test environments
• Additional attack case studies
• Extended multimodal AI coverage

Contributions welcome via issues and PRs.

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License

Licensed under CC BY-SA 4.0. See LICENSE for details.

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Disclaimer

⚠️ For authorized security testing only.

Ensure:

• Written authorization (SOW/RoE) is in place
• Compliance with applicable laws and regulations
• No unauthorized testing on production systems

The authors accept no liability for unauthorized use.