agent-scan
Snyk's security scanner for AI agents, MCP servers and agent skills.
NVIDIA's security scanner for AI agent skills - check before you install
SkillSpector is an open-source ai agents project by NVIDIA (NVIDIA/SkillSpector on GitHub). It has 19,702 GitHub stars and 1,722 forks, is released under the Apache-2.0 license, and was last updated on GitHub on 8 October 2026.
Choose a skill directory, a single SKILL.md, a Git repository or a zip file to vet.
Install it as a uv tool, from a clone with make install, or use the Docker image.
Scan the target and review findings in the terminal, or export JSON, Markdown or SARIF.
Add the scan to your workflow or CI so unreviewed skills do not reach your agents.
Scans local skill directories, single SKILL.md files, Git repositories and zip archives.
Looks for prompt injection, data exfiltration, malicious patterns and supply-chain risks in skills.
Reports in the terminal or as JSON, Markdown or SARIF for CI/CD and IDE integration.
Run fully static with --no-llm, or enable LLM-assisted analysis by providing credentials.
A Docker build lets you scan without a Python environment.
An optional mcp extra packages SkillSpector for MCP-based workflows.
Get the source code from GitHub and enter the project directory.
git clone https://github.com/NVIDIA/SkillSpector.git
cd SkillSpectorThe recommended install registers skillspector as an isolated uv tool.
# Install uv first if needed, then install the tool from the repo - see README Quick StartPoint the scanner at a skill directory; add --no-llm for a fully offline static scan.
skillspector scan ./my-skill/ --no-llmIt is maintained by NVIDIA as an open-source project on GitHub.
Yes - SkillSpector is Apache-2.0 licensed and free to use.
No key is needed for static scanning (--no-llm). The optional LLM-assisted analysis uses a model provider you configure with your own credentials.
Compared with generic code scanners like Semgrep, SkillSpector is purpose-built for agent skills - prompt injection, exfiltration and skill supply-chain patterns that general SAST does not model.
Install it with uv per the README, then run skillspector scan on a skill directory and read the report.
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