
SkillSpector
Security scanner for AI agent skills. Detect vulnerabilities, malicious patterns, and security risks.
The Lens
By Erik Loyd, SaaS CEO and former COO/CFO of an AWS Premier Partner.
Updated Oct 2026
SkillSpector checks AI agent skills before you install them. Skills are instructions and scripts that Claude Code, Codex and friends run with your permissions, usually grabbed from strangers unread. Point it at a Git repo, URL, zip or folder and you get a 0-100 risk score with a SAFE, CAUTION or DO NOT INSTALL call. Free under Apache 2.0, from NVIDIA.
Install with uv tool install from the repo or build the included Dockerfile. Checks span 17 categories, from prompt injection and data exfiltration to supply-chain tricks, YARA malware signatures and MCP tool poisoning. Output comes as terminal, JSON, Markdown or SARIF, and an MCP server mode lets your agent scan before it installs.
No paid tier. Solo, small and large teams: free, and worth wiring into CI. Know this first: the LLM review stage is on by default and sends skill file contents to your provider, NVIDIA's build.nvidia.com unless you change it. Ollama or --no-llm keeps file contents local.
The catch: a CAUTION score still exits 0, so a default CI gate passes anything scoring up to 50. Add --fail-on-findings. And it never runs the skill, so a clean scan means nothing known turned up, not that it's safe.
Free vs Self-Hosted vs Paid
fully freeFree: Everything, under Apache 2.0: static analysis across 17 categories (the README counts 71 patterns), Python AST and taint tracking, YARA signatures, live CVE lookups against OSV.dev with an offline fallback, 0-100 risk scoring, baselines to suppress accepted findings, terminal/JSON/Markdown/SARIF output, MCP registry snapshot comparison, an MCP server mode, and Pi and OpenCode extensions.
Self-hosted: The only way it runs. Python 3.12+ via uv tool install pointed at the GitHub repo, from source with make install, or a Docker image you build from the included Dockerfile (no published image). No account. Dependency names and versions go to OSV.dev on every scan, even with --no-llm.
Paid: Nothing sold by NVIDIA. The LLM review stage is on by default and bills to whichever provider you set: NVIDIA build.nvidia.com (the default, GLM-5.3), OpenAI (gpt-5.4 default), Anthropic (claude-opus-4-6 default), Bedrock, Gemini on Google Cloud, Azure OpenAI, any OpenAI-compatible endpoint, or a local Claude, Gemini or OpenCode CLI login. Ollama or --no-llm keeps a scan at $0.
Free under Apache 2.0. The LLM review stage is on by default and bills to your model provider; `--no-llm` or a local Ollama model keeps every scan at $0.
What to do by team size
- Solo
- free; run it with `--no-llm` or Ollama before installing any skill
- Small team
- free; add it to CI with `--fail-on-findings`
- Medium team
- free; pin one LLM provider so file contents only go where you've approved
- Large team
- free; gate installs through the MCP server or CI and keep baselines in the repo
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Trust Signals
License: Apache License 2.0
Use freely. Patent grant included.
Commercial use: ✓ Yes
About
- Owner
- NVIDIA Corporation (Organization)
- Stars
- 24,829
- Forks
- 2,165
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