No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by Tencent · MCP Server · ★ 6.4k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is AI-Infra-Guard safe to install? View the security audit →
Documentation | 中文 <a href="https://www.blackhat.com/eu-25/arsenal/schedule/index
| Stars | 6,441 |
| Forks | 595 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 63.005055242275/100 |
| Open Issues | 33 |
| Last Updated | 2026-09-18 |
| Created | 2024-12-25 |
| Platforms | mcp, python |
| Est. Tokens | ~8430k |
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AI-Infra-Guard is 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.. It is categorized as a MCP Server with 6.4k GitHub stars.
AI-Infra-Guard is primarily written in Python. It covers topics such as agent, ai, benchmark.
You can find installation instructions and usage details in the AI-Infra-Guard GitHub repository at github.com/Tencent/AI-Infra-Guard. The project has 6.4k stars and 595 forks, indicating an active community.
AI-Infra-Guard is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to AI-Infra-Guard on Agent Skills Hub include CyberStrike, Anthropic-Cybersecurity-Skills, cursor-talk-to-figma-mcp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: