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 EdoardoBambini · Agent Tool · ★ 120
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is IAGA-Sentinel safe to install? View the security audit →
Featured in: Agent Governance
IAGA Sentinel The EU AI Act conformity evidence layer for AI agents. Cryptographically signed, replay-verifiable, EU-sovereign proof of every action an agent takes, mapped to AI Act Article 12 and Annex IV. Documentation · Quickstart · Community vs Enterprise · Who we are · License Built in the EU by three founders (French, German, Italian) and research-validated, not marketing-validated: peer-reviewed at AISec 2026 (ACM
| Stars | 120 |
| Forks | 1 |
| Language | Rust |
| Category | Agent Tool |
| Quality Score | 59.2894776434141/100 |
| Last Updated | 2026-05-28 |
| Created | 2026-03-24 |
| Platforms | claude-code, rust |
| Est. Tokens | ~1211k |
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IAGA-Sentinel is AI agents are getting tool access — shell, file system, databases, APIs, secrets. But **nobody is governing what they actually do with it**. Frameworks like LangChain, CrewAI, AutoGen, and Claude Cod. It is categorized as a Agent Tool with 120 GitHub stars.
IAGA-Sentinel is primarily written in Rust.
You can find installation instructions and usage details in the IAGA-Sentinel GitHub repository at github.com/EdoardoBambini/IAGA-Sentinel. The project has 120 stars and 1 forks, indicating an active community.
The top alternatives to IAGA-Sentinel on Agent Skills Hub include claude-plugins, tutor-skills, repren. 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: