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 microsoft · Agent Tool · ★ 6.2k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is agent-governance-toolkit safe to install? View the security audit →
Welcome to Agent Governance Toolkit! [!IMPORTANT] Community Preview — Not Official Microsoft-Signed Releases All packages currently published from this repository (PyPI, npm, NuGet) are community preview releases for testing and evaluation purposes only. They are not official Micro
| Stars | 6,227 |
| Forks | 1,112 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 66.6692411296415/100 |
| Open Issues | 264 |
| Last Updated | 2026-09-08 |
| Created | 2026-03-02 |
| Platforms | python |
| Est. Tokens | ~17k |
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agent-governance-toolkit is AI Agent Governance Toolkit — Policy enforcement, zero-trust identity, execution sandboxing, and reliability engineering for autonomous AI agents. Covers 10/10 OWASP Agentic Top 10.. It is categorized as a Agent Tool with 6.2k GitHub stars.
agent-governance-toolkit is primarily written in Python. It covers topics such as agent-framework, ai-agents, ai-safety.
You can find installation instructions and usage details in the agent-governance-toolkit GitHub repository at github.com/microsoft/agent-governance-toolkit. The project has 6.2k stars and 1112 forks, indicating an active community.
agent-governance-toolkit is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to agent-governance-toolkit on Agent Skills Hub include better-agents, hive, mcp-agent. 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: