by killertcell428 · MCP Server · ★ 54
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
pip install pyaigis
docker run -p 8080:8080 ghcr.io/killertcell428/aigis
Taken from the project's README on GitHub.
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.
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.
| Stars | 54 |
| Forks | 8 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 70/100 |
| Open Issues | 9 |
| Last Updated | 2026-09-02 |
| Created | 2026-04-11 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~17k |
Aigis The open-source trust layer for bringing Claude Code (and other autonomous AI agents) to work — with your security team's approval. Your company won't approve Claude Code? The blocker is rarely the model — it's the missing answer to "what can it run, and where's the audit trail?" Aigis is the layer that answers it: deterministic guardrails on every tool call, tamper-evident audit logs, and...
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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: