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🚀 One-Stop AI Red Teaming Platform by Tencent Zhuque Lab

A.I.G (AI-Infra-Guard) brings together OpenClaw security checks, Agent security scanning, AI tool and skill scanning, AI infrastructure vulnerability scanning, and LLM security assessment (jailbreak evaluation), aiming to provide the most comprehensive, intelligent, and easy-to-use way to check AI security risks.

We are committed to making A.I.G(AI-Infra-Guard) the industry-leading AI red teaming platform. More stars help this project reach a wider audience, attracting more developers to contribute, which accelerates iteration and improvement. Your star is crucial to us!

Table of Contents

• 🚀 Quick Start
• 🧰 Standalone Use
• 🖼️ Showcase
• 📖 User Guide
• 🏗️ Architecture Evolution
• 📝 Contribution Guide
• 🛡️ About the Team
• 🙏 Acknowledgements
• 💬 Join the Community
• 📖 Citation
• 📄 License
  
  

🚀 Quick Start

🐳 Deploy A.I.G with Docker

Docker	RAM	Disk Space
20.10 or higher	4GB+	10GB+

# This method pulls pre-built images from Docker Hub for a faster start
git clone https://github.com/Tencent/AI-Infra-Guard.git
cd AI-Infra-Guard
# For Docker Compose V2+, replace 'docker-compose' with 'docker compose'
docker-compose -f docker-compose.images.yml up -d

Once the service is running, you can access the A.I.G web interface at: http://localhost:8088

Other Installation Methods

Method 2: One-Click Install Script （Recommended）

# This method will automatically install Docker and launch A.I.G with one command
curl https://raw.githubusercontent.com/Tencent/AI-Infra-Guard/refs/heads/main/docker.sh | bash

Method 3: Build and run from source

git clone https://github.com/Tencent/AI-Infra-Guard.git
cd AI-Infra-Guard
# This method builds a Docker image from local source code and starts the service
# (For Docker Compose V2+, replace 'docker-compose' with 'docker compose')
docker-compose up -d

Note: The AI-Infra-Guard project is positioned as an AI red teaming platform for internal use by enterprises or individuals. It currently lacks an authentication mechanism and should not be deployed on public networks.

For more information, see: https://tencent.github.io/AI-Infra-Guard/?menu=getting-started

🧰 Standalone Use

The five scanners can be used from the command line without starting the web service. Only the shortest usage is shown below. See each README for parameters and examples.

AI Infrastructure Scan

Scan a domain, IP, or URL and match fingerprints and vulnerabilities.

pip install aig-infra-scan
aig-infra-scan -t https://example.com

View README

LLM Security Assessment / Jailbreak

Evaluate a model that exposes an OpenAI-compatible API.

pip install aig-model-scan
aig-model-scan \
  --model "gpt-4o-mini" \
  --base_url "https://api.openai.com/v1" \
  --api_key "your-api-key" \
  --max_concurrent 10 \
  --scenarios Bias \
  --techniques Raw

View README

MCP Scan

Scan an MCP server source directory, or connect to a service that is already running.

pip install aig-mcp-scan
export LLM_API_KEY="your-api-key"
aig-mcp-scan --repo /path/to/mcp-server -o result.sarif.json

View README

Skill Scan

Audit a local Agent Skill directory.

pip install aig-skill-scan
export LLM_API_KEY="your-api-key"
aig-skill-scan --repo /path/to/your/skill -o result.sarif.json

View README

Agent Scan

Send test prompts to a running Agent. target.yaml describes the Agent under test. The API key is for the model used by the scanner.

pip install aig-agent-scan
export LLM_API_KEY="your-api-key"
aig-agent-scan --agent_provider target.yaml -o result.json

View README

🖼️ Showcase

A.I.G Main Interface