awesome-ai-security-tools: A curated list of public-source, research, and commercial tools for AI security and AI-assisted cybersecurity

by scadastrangelove · Agent Tool · ★ 1.7k

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

Security audit verdict: SAFE · quality 55/100

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.

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Quick Facts

Stars1,676
Forks428
LanguagePython
CategoryAgent Tool
Quality Score55/100
Open Issues5
Last Updated2026-10-22
Created2026-05-27
Platformspython
Est. Tokens~25k

About awesome-ai-security-tools

Awesome AI Security Tools A curated list of public-source, research, and commercial tools for AI security and AI-assisted cybersecurity — autotriage, agent security, AI/ML supply chain, pentest agents, AI SAST, LLM-driven fuzzing, threat intelligence, SOC/SIEM triage, reverse engineering, LLM red-teaming, and more.

Compatible Skills

These tools work well together with awesome-ai-security-tools for enhanced workflows:

  • awesome-ai-plugins — semantic(0.27)+complementary+same_lang+similar_pop+shared_platform (59%)
  • repo-forensics — semantic(0.25)+complementary+same_lang+similar_pop+shared_platform (59%)
  • MCP-Dandan — semantic(0.27)+complementary+rare_topics+same_lang+similar_pop+shared_platform (59%)
  • awesome-code-docs — semantic(0.22)+complementary+rare_topics+same_lang+similar_pop+shared_platform (57%)
  • openclaw-skills-security — semantic(0.20)+complementary+same_lang+similar_pop+shared_platform (57%)

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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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