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 snyk · MCP Server · ★ 3.1k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is agent-scan safe to install? View the security audit →
Snyk Agent Scan Discover and scan agent components on your machine for prompt injections and vulnerabilities (including agents, MCP servers, skills). NEW Read our technical report on the emerging threats of the agent skill eco-system published together with Agent Scan 0.4, which adds support for scanning agent skills. Agent Scan helps you keep an inventory of all your installed agent components (harnesses, MCP servers, skills) and scans them for common threats like prompt injections, sensitive data handling, or malware payloads hidden in natural language. Highlights Auto-discover MCP configurations, agent tools, skills Scanning of Claude, Cursor, Windsurf, Ge
| Stars | 3,079 |
| Forks | 278 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 76.0379718621251/100 |
| Open Issues | 13 |
| Last Updated | 2026-09-22 |
| Created | 2025-04-07 |
| Platforms | mcp, python |
| Est. Tokens | ~15k |
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agent-scan is Security scanner for AI agents, MCP servers and agent skills.. It is categorized as a MCP Server with 3.1k GitHub stars.
agent-scan is primarily written in Python. It covers topics such as agent, ai, mcp.
You can find installation instructions and usage details in the agent-scan GitHub repository at github.com/snyk/agent-scan. The project has 3.1k stars and 278 forks, indicating an active community.
agent-scan is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to agent-scan on Agent Skills Hub include AI-Infra-Guard, metorial, octocode-mcp. 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: