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AI Infra Guard

A full-stack AI Red Teaming platform securing AI ecosystems via OpenClaw Security Scan, Agent Scan, Skills Scan, MCP scan, AI Infra scan and LLM jailbreak evaluation.

Install / Use

npx skills add Tencent/AI-Infra-Guard

Installs into whichever agent you are using.

README

<p align="center"> <h1 align="center"><img vertical-align="middle" width="400px" src="img/logo-full-new.png" alt="A.I.G"/></h1> </p> <p align="center"> <a href="https://tencent.github.io/AI-Infra-Guard/">📖 Documentation</a> &nbsp;|&nbsp; 🌐 <a href="./readme/README_ZH.md">🇨🇳 中文</a> · <a href="./readme/README_JA.md">🇯🇵 日本語</a> · <a href="./readme/README_ES.md">🇪🇸 Español</a> · <a href="./readme/README_DE.md">🇩🇪 Deutsch</a> · <a href="./readme/README_FR.md">🇫🇷 Français</a> · <a href="./readme/README_KR.md">🇰🇷 한국어</a> · <a href="./readme/README_PT.md">🇧🇷 Português</a> · <a href="./readme/README_RU.md">🇷🇺 Русский</a> </p> <p align="center"> <a href="https://github.com/tencent/AI-Infra-Guard/stargazers"> <img src="https://img.shields.io/github/stars/tencent/AI-Infra-Guard?style=social" alt="GitHub stars"> </a> <a href="https://github.com/Tencent/AI-Infra-Guard"> <img alt="GitHub downloads" src="https://img.shields.io/github/downloads/Tencent/AI-Infra-Guard/total"> </a> <a href="https://github.com/Tencent/AI-Infra-Guard"> <img alt="docker pulls" src="https://img.shields.io/docker/pulls/zhuquelab/aig-server.svg?color=gold"> </a> <a href="https://github.com/Tencent/AI-Infra-Guard"> <img alt="Release" src="https://img.shields.io/github/v/release/Tencent/AI-Infra-Guard?color=green"> </a> <a href="https://deepwiki.com/Tencent/AI-Infra-Guard"> <img src="https://deepwiki.com/badge.svg" alt="Ask DeepWiki"> </a> </p> <p align="center"> <a href="https://clawhub.ai/aigsec/edgeone-clawscan" target="_blank"> <img src="https://img.shields.io/badge/ClawHub-EdgeOne%20ClawScan-a870dc" alt="EdgeOne ClawScan"> </a> <a href="https://clawhub.ai/aigsec/edgeone-skill-scanner" target="_blank"> <img src="https://img.shields.io/badge/ClawHub-EdgeOne%20Skill%20Scanner-2ea44f" alt="EdgeOne Skill Scanner"> </a> <a href="https://clawhub.ai/aigsec/aig-scanner" target="_blank"> <img src="https://img.shields.io/badge/ClawHub-AIG%20Scanner-e6a817" alt="AIG Scanner"> </a> </p> <p align="center"> <a href="https://trendshift.io/repositories/13637" target="_blank"><picture><source media="(prefers-color-scheme: dark)" srcset="https://trendshift.io/api/badge/repositories/13637"><source media="(prefers-color-scheme: light)" srcset="https://trendshift.io/api/badge/repositories/13637"><img src="https://trendshift.io/api/badge/repositories/13637" alt="Tencent%2FAI-Infra-Guard | Trendshift" width="250" height="55"/></picture></a>&nbsp; <a href="https://www.blackhat.com/eu-25/arsenal/schedule/index.html#aigai-infra-guard-48381" target="_blank"><img src="img/blackhat.png" alt="Tencent%2FAI-Infra-Guard | blackhat" width="175" height="55"/></a>&nbsp; <a href="https://github.com/deepseek-ai/awesome-deepseek-integration" target="_blank"><img src="img/awesome-deepseek.png" alt="Tencent%2FAI-Infra-Guard | awesome-deepseek-integration" width="273" height="55"/></a> </p> <br> <p align="center"> <h2 align="center">🚀 AI Red Teaming Platform by Tencent Zhuque Lab</h2> </p>

<b>A.I.G (AI-Infra-Guard)</b> integrates capabilities such as ClawScan(OpenClaw Security Scan), Agent Scan,AI infra vulnerability scan, MCP Server & Agent Skills scan, and Jailbreak Evaluation, aiming to provide users with the most comprehensive, intelligent, and user-friendly solution for AI security risk self-examination.

<p> 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! </p> <p align="center"> <a href="https://github.com/Tencent/AI-Infra-Guard"> <img src="https://img.shields.io/badge/⭐-Give%20us%20a%20Star-yellow?style=for-the-badge&logo=github" alt="Give us a Star"> </a> </p> <br>

📋 User Feedback Survey

Help us improve A.I.G! Please take 3-5 minutes to fill out our User Feedback Survey. Users who provide high-quality feedback and leave a valid email address will receive an exclusive Tencent souvenir gift.

<br>

🚀 What's New

  • 2026-07-30 · v4.5.1 — Jailbreak Evaluation: 4 multi-turn jailbreak attacks (Many-Shot, PAIR, GOAT, ActorAttack); Agent-Scan: 5 new OWASP skills + web-exfiltration detection (10 skills total); MCP-Scan: 4 new security rules
  • 2026-07-27 · v4.5.0 — AI Security Skill Market launched (3 official skills); frontend fully open-sourced; Skill scan engine upgraded (9 risk categories, SkillTrustBench top score 0.9848); Skill/MCP/Agent scan as standalone CLI; vuln library expanded to 130 components, 1888 rules
  • 2026-06-25 · v4.1.15 — MCP Scan: 3 new threat detection rules (tool poisoning, credential exfiltration, command injection); 6 new llama.cpp CVE rules; model.token now optional with system default fallback.
  • 2026-06-18 · v4.1.14 — Prompt Security: 9 new single-turn jailbreak operators; new aig-agent-redteam skill for comprehensive Agent red-team assessment.
  • 2026-06-11 · v4.1.13 — New version check API endpoint; security scoring switched to absolute deduction model for clearer risk assessment.
  • 2026-06-08 · v4.1.12 — Fingerprint library expanded: 39 new AI Web fingerprints added, 18 existing fingerprints enhanced.

👉 Earlier releases · 🛒 AI Security Skill Market · 🔍 skill-scan CLI · 🔍 mcp-scan CLI · 🔍 agent-scan CLI · 📊 SkillTrustBench

Table of Contents

🚀 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 <br>

Use from OpenClaw

You can also call A.I.G directly from OpenClaw chat via the aig-scanner skill.

clawhub install aig-scanner

Then configure AIG_BASE_URL to point to your running A.I.G service.

For more details, see the aig-scanner README.

<details> <summary><strong>More installation options</strong></summary>

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

</details>

⚡ Install aig-skill-scan with a Single Command

Agent Skill security audit tool, easily integrated into enterprise CI/CD pipelines. Vulnerability classification aligns with SkillTrustBench T01–T09 taxonomy. Learn more →

pip install aig-skill-scan

# Set API key via environment variable
export LLM_API_KEY="your-api-key"

# Scan a local Skill project directory
aig-skill-scan --repo /path/to/your/skill \
           -m deepseek-v4-flash \
           --language en \
           -o result.json

🌟 Try the Online Pro Version

Experience the Pro version with advanced features and improved performance. The Pro version requires an invitation code and is prioritized for contributors who have submitted issues, pull requests, or discussions, or actively help grow the community. Visit: https://aigsec.ai/.

<br> <br>

✨ Features

🔍 aig-skill-scan Performance & Coverage

Performance on SkillTrustBench with different LLMs:

| # | Model | F1 | Precision | Recall | FPR | |:--|:------|:---|:----------|:-------|:----| | 1 | Claude Opus 4.6 | 0.9848 | 0.9725

Related Skills

View on GitHub
GitHub Stars4.4k
CategoryDevelopment
Updated5h ago
Forks435

Languages

Python

Security Score

100/100

Audited on Aug 8, 2026

No findings