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AI Composition Analysis. Open security intelligence for the AI component ecosystem.

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AI Component Security Index

By CodeThreat

AI Composition Analysis

AI Component
Security Index

Open security intelligence for the AI component ecosystem. We index, scan, and publish risk profiles for MCP servers and Agent Skills so you can make informed decisions before adoption.

The Problem

We believe skills, MCP servers, and other AI-related components are new undeterministic attack surfaces of the agentic era. AI agents rely on them from public registries — yet most have no standardized security assessment, and many introduce real risk.

MCP Server Risks

Exposed tools can leak secrets, execute arbitrary code, or exfiltrate data. Registry metadata rarely includes security context.

There is no standard way to assess risk before adding an MCP server to your stack.

Agent Skill Risks

SKILL.md and tool definitions can contain prompt injection, data exfiltration, or unsafe syscalls. Skills are distributed across GitHub, SkillsMP, Tessl — with no central security view.

Duplicate skill names can confuse or deceive users about what they are actually running.

What We Do

We run a continuous pipeline: ingest from 10+ registries, run multi-phase security scans, and publish risk profiles.

Ingest

Discover and index MCP servers and Agent Skills from official registries, GitHub, npm, and more.

Scan

We use Cisco MCP-scanner, Cisco skill-scanner, and CodeThreat shift-ql to run data flow analysis on files.

Publish

Risk scores, severity breakdowns, and actionable findings.

Fast Check

skillaudit.sh is an easy-to-run fast checker. Scan a skill or MCP before adoption — no signup, no pipeline.

Why We Do This

We provide open, standardized vulnerability data for the AI component ecosystem — comparable to Sonatype OSS Index or Socket.dev, but for MCP servers and Agent Skills. Developers can see risk before they adopt.

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Scan your own AI components

Full SAST + SCA agentic security analysis for MCP servers and Skills.

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