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 sinewaveai · MCP Server · ★ 121
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is agent-security-scanner-mcp safe to install? View the security audit →
agent-security-scanner-mcp Security scanner for AI coding agents and autonomous assistants Scans code for vulnerabilities, detects hallucinated packages, blocks prompt injection, and provides LLM-powered semantic code review — via MCP (Claude Code, Cursor, Windsurf, Cline) or CLI (OpenClaw, CI/CD). 🎯 Two Versions Available 🔥 ProofLayer (Lightweight) - NEW! Ultra-fast, zero-Python security scanner — 81.5KB package, 4-second install [](https://www.npmjs.com/package/@proofl
| Stars | 121 |
| Forks | 11 |
| Language | JavaScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 73.1379037846838/100 |
| Open Issues | 14 |
| Last Updated | 2026-09-02 |
| Created | 2026-02-04 |
| Platforms | claude-code, codex, mcp, node |
| Est. Tokens | ~25k |
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agent-security-scanner-mcp is Security scanner MCP server for AI coding agents. Prompt injection firewall, package hallucination detection (4.3M+ packages), 1000+ vulnerability rules with AST & taint analysis, auto-fix.. It is categorized as a MCP Server with 121 GitHub stars.
agent-security-scanner-mcp is primarily written in JavaScript. It covers topics such as agent-security, ai-agent-security, ai-security.
You can find installation instructions and usage details in the agent-security-scanner-mcp GitHub repository at github.com/sinewaveai/agent-security-scanner-mcp. The project has 121 stars and 11 forks, indicating an active community.
agent-security-scanner-mcp is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to agent-security-scanner-mcp on Agent Skills Hub include shellward, node9-proxy, agentseal. 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: