AI-Infra-Guard: A full-stack AI Red Teaming platform securing AI ecosystems via OpenClaw Security Scan, Agent Scan, Skills

by Tencent · MCP Server · ★ 6.4k

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install AI-Infra-Guard

git clone https://github.com/Tencent/AI-Infra-Guard.git

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 63/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agentaibenchmarkinfrajailbreakllmmcpopenclawred-teamsafety

Quick Facts

Stars6,441
Forks595
LanguagePython
CategoryMCP Server
LicenseApache-2.0
Quality Score63/100
Open Issues33
Last Updated2026-09-18
Created2024-12-25
Platformsmcp, python
Est. Tokens~8430k

About AI-Infra-Guard

Documentation | 中文 <a href="https://www.blackhat.com/eu-25/arsenal/schedule/index

Compatible Skills

These tools work well together with AI-Infra-Guard for enhanced workflows:

  • fuzzforge_ai — semantic(0.15)+complementary+rare_topics+same_lang+similar_pop+shared_platform (60%)
  • Auditor — semantic(0.15)+complementary+rare_topics+same_lang+similar_pop+shared_platform (59%)
  • skill-scanner — semantic(0.23)+complementary+same_lang+similar_pop+shared_platform (53%)
  • moonshot — semantic(0.22)+complementary+same_lang+similar_pop+shared_platform (53%)
  • agentic-radar — semantic(0.36)+rare_topics+same_lang+similar_pop+shared_platform (51%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

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