Overview
SkillSpector is a robust security scanner designed to protect your AI agent ecosystem. It proactively identifies vulnerabilities, malicious patterns, and security risks within AI agent skills before they are installed, mitigating potential threats and ensuring the integrity of your AI deployments. With a significant percentage of agent skills found to contain vulnerabilities, SkillSpector is an essential tool for maintaining a secure AI environment.
Key Features
- Comprehensive Vulnerability Detection: Analyzes for 64 distinct vulnerability patterns across 16 categories, including prompt injection, data exfiltration, privilege escalation, supply chain attacks, excessive agency, and more.
- Multi-Format Input Support: Seamlessly scans skills from various sources: Git repositories, URLs, ZIP archives, local directories, or individual files.
- Advanced Two-Stage Analysis: Combines rapid static analysis with an optional, powerful LLM semantic evaluation for deeper insights and reduced false positives.
- Real-Time CVE Lookups: Integrates with OSV.dev for live vulnerability data on dependencies, with automatic offline fallback capabilities.
- Flexible Reporting: Generates reports in multiple formats, including terminal (human-readable), JSON (machine-readable), Markdown (documentation-friendly), and SARIF (for CI/CD integration and IDEs).
- Actionable Risk Scoring: Provides a clear 0-100 risk score, severity labels (LOW to CRITICAL), and specific recommendations for each identified issue.
- LLM Integration Flexibility: Supports multiple LLM providers (OpenAI, Anthropic, NVIDIA Build) and allows easy configuration for local or cloud-hosted endpoints.
Typical Use Cases
- Pre-installation Security Vetting: Integrate SkillSpector into your CI/CD pipeline or development workflow to automatically scan and approve or flag agent skills before they are deployed or shared.
- Auditing Existing Skills: Regularly audit your current library of agent skills to identify and remediate any latent security risks.
- Securing Open-Source Contributions: Ensure that any community-contributed agent skills meet your security standards by performing an automated scan.
- Developer Productivity: Empower developers with immediate security feedback on their agent skill creations, allowing them to address vulnerabilities early in the development lifecycle.
- LLM Ecosystem Security: Provide a critical layer of defense for platforms and frameworks that rely on extensible AI agent skills.
