README

SkillSpector

Security scanner for AI agent skills. Detect vulnerabilities, malicious patterns, and security risks before installing agent skills.




 Overview

AI agent skills (used by Claude Code, Codex CLI, Gemini CLI, etc.) execute with implicit trust and minimal vetting. In the 31,132-skill analyzed subset of the research dataset, 26.1% of skills contain vulnerabilities and 5.2% show likely malicious intent.

SkillSpector helps you answer: "Is this skill safe to install?"

SkillSpector is part of the NVIDIA Verified Skills pipeline, which scans, evaluates, and signs agent skills before publication. Skills that pass are published to the NVIDIA skills catalog.

 Documentation

- Scan agent skills before installation — Hosted guide: when to scan, how to read a report, and how to gate installs.
- Development guide — Architecture, package layout, and how to extend the analyzer pipeline.
- Security policy — Report suspected vulnerabilities privately to NVIDIA PSIRT.
- Analysis resource bounds — Fail-closed bundle, parser, nested-artifact, ledger, and finding ceilings.
- Pi extension — Install SkillSpector as a Pi tool for scanning skills from inside agent sessions.
- OpenCode extension — Install SkillSpector as an OpenCode tool and /skillspector command for scanning skills from inside agent sessions.

 Features

- Multi-format input: Scan Git repos, URLs, zip files, directories, or single files
- 71 vulnerability patterns across 17 categories: prompt injection, data exfiltration, privilege escalation, supply chain, excessive agency, output handling, system prompt leakage, memory poisoning, tool misuse, rogue agent, anti-refusal, trigger abuse, dangerous code (AST), taint tracking, YARA signatures, MCP least privilege, and MCP tool poisoning
- Two-stage analysis: Fast static analysis + optional LLM semantic evaluation
- Live vulnerability lookups: SC4 queries OSV.dev for real-time CVE data with automatic offline fallback
- Multiple output formats: Terminal, JSON, Markdown, and SARIF reports
- Risk scoring: 0-100 score with severity labels and clear recommendations
- Baseline / false-positive suppression: Accept known findings via a glob-rule or fingerprint baseline so re-scans surface only new issues (docs)

 Quick Start

 Installation

 Open-source software notice: This project will download and install additional third-party open source software projects. Review the license terms of these open source projects before use.

Create and activate a virtual environment first (all make targets assume the venv is active). Use uv or pip; the Makefile uses uv if available, otherwise pip.

Quick install with uv (CLI-only):

bash
uv tool install git+https://github.com/NVIDIA/skillspector.git
 Update later: uv tool update skillspector


If you plan to run skillspector mcp, install the MCP extra at install time:

bash
uv tool install 'skillspector[mcp] @ git+https://github.com/NVIDIA/skillspector.git'


From source:

bash
 Clone the repository
git clone https