What is Al-Infra-Guard?
Al-Infra-Guard is an efficient, lightweight, and easy-to-use AI infrastructure security assessment tool developed and open-sourced by Tencent. It is designed to identify and detect potential security risks in AI systems. Al-Infra-Guard supports fingerprint recognition for 28 AI frameworks and covers a database of over 200 security vulnerabilities. The tool enables rapid scanning and vulnerability identification, requiring no complex configurations. It provides flexible YAML-based rule definitions and matching syntax. Its core components are simple and efficient, with low resource consumption and cross-platform support. Users can perform security assessments through local scanning, targeting specific systems, or reading targets from files. Additionally, AI analysis capabilities enhance its detection performance.
Key Features of Al-Infra-Guard
Efficient Scanning：Supports fingerprint recognition for 28 mainstream AI frameworks, quickly identifying AI components within a system.
Vulnerability Detection：Provides detailed vulnerability information, including descriptions, severity ratings, and remediation recommendations.
Flexible Usage Options：Offers both a web-based UI and a command-line interface (CLI) to cater to different user needs.
Lightweight Design：The core components are highly efficient, with a small binary footprint and low resource consumption.
Easy Extensibility：Users can customize rules as needed.
Sends HTTP requests to target systems and analyzes response content (e.g., headers, body, metadata) to extract feature information.
Uses predefined fingerprint rules stored in YAML files and matching logic (e.g., regular expressions, fuzzy matching) to identify AI frameworks and components.
Vulnerability Matching Mechanism：Matches identified AI components against entries in a vulnerability database.
Vulnerability rules are defined in YAML format, containing details such as descriptions, impact scope, and remediation recommendations.
Uses logical operators (e.g., &&, ||) to combine multiple matching conditions, ensuring accurate vulnerability detection.
AI-Enhanced Analysis：Supports integration with external AI models (e.g., Hunyuan) via API calls for deeper analysis.
AI models help identify complex vulnerability patterns and provide intelligent detection recommendations.
Lightweight Architecture：The core components are developed in efficient programming languages (e.g., Go) to optimize performance and resource utilization.
Modular design separates functionalities such as fingerprint recognition, vulnerability matching, and user interface, improving system maintainability and scalability.
Cross-Platform Compatibility：Compiled as a static binary executable, allowing the tool to run on Windows, Linux, and macOS.
Project Repository
GitHub: https://github.com/Tencent/Al-Infra-Guard
Use Cases of Al-Infra-Guard
AI Development & Deployment：Helps development teams quickly detect security vulnerabilities in AI frameworks and components during model development and deployment, ensuring system security.
Cloud Service Security：Enables cloud platforms to scan AI services, promptly identify and fix vulnerabilities, and safeguard user data and platform security.
Security Auditing & Compliance：Supports enterprises in conducting security audits, generating vulnerability reports, and meeting industry compliance requirements.
IT Operations & Maintenance：Allows enterprise IT teams to regularly scan AI systems, monitor security status, and rapidly respond to and resolve security issues.
Security Research & Community Contributions：Assists researchers and the security community in developing new vulnerability detection methods and contributing new fingerprint and vulnerability rules.
