codeinspectus: Local-first MCP security scanner for AI-generated apps: four open-source engines plus the Synvoya engine

by Synvoya · MCP Server · ★ 50

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install codeinspectus

npx codeinspectus setup
npx codeinspectus setup --status

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 64/100

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.

ai-generated-codeai-securityappsecclaude-codecodexcursordevsecopsgitleakslocal-firstmcp

Quick Facts

Stars50
Forks10
LanguageTypeScript
CategoryMCP Server
LicenseApache-2.0
Quality Score64/100
Open Issues5
Last Updated2026-11-05
Created2026-07-01
Platformsclaude-code, codex, mcp, node
Est. Tokens~26k

About codeinspectus

CodeInspectus, by Synvoya A local-first, privacy-preserving security MCP server and CLI. Any AI coding agent (Claude Code, Cursor, Codex, Windsurf, Cline, Aider) can invoke CodeInspectus to scan AI-generated / "vibe-coded" code for real vulnerabilities, map findings to compliance frameworks as honest code-level coverage, and drive a scan → fix → rescan loop — fully on your machine, with no...

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How this security grade is produced

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:

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