SkillSpector

Read the source on GitHub Project homepage

What it does

An editorial selection.

Security scanner for AI agent skills that detects malicious patterns and vulnerabilities before you install them.

Why it is listed

NVIDIA's research found 26% of 31k skills had vulnerabilities and 5% looked malicious. Run it before installing skills from strangers.

GitHub describes it as: Security scanner for AI agent skills. Detect vulnerabilities, malicious patterns, security risks, prompt injection, data exfiltration, and supply-chain risks in Claude Code, Codex, and MCP skills before you install them.

Counts were observed on 27/10/2026, 23:15:40 UTC. Observations older than 36 hours are excluded from current movement rankings.

Repository at a glance

Stars: 22,725
Forks: 1,970
Open issues: 82
Merged PRs: 415
Commits, last 30 days: 1,109
Stars, 7 days: unavailable
Stars, 30 days: unavailable

Counts observed on 27/10/2026, 23:15:40 UTC. Growth uses complete dated windows; see Methodology.

History

History: 2 observations, 2026-10-27 to 2026-10-28. Dots are observations; lines connect consecutive daily observations only.

Project details

Language: Python
Licence: Apache-2.0
Created: 21 Mar 2026
Last push: 27 Oct 2026
Latest release: v2.13.1 · 23 Oct 2026
Category: Security
Topics: agent-security agent-skills agentic-ai ai-security claude-code mcp prompt-injection security-scanner security-tools security-workflow
Observed: 2026-10-27 23:15:40 UTC

Explore and get started

Use the project's own documentation for supported platforms, dependencies and installation steps. The README and release notes are maintained by NVIDIA.

Read the README and setup instructionsFeatures, prerequisites, examples and documentation links.
Browse releases and changelogsPublished versions and the changes made between releases.
Check licence and usage termsApache-2.0 is the licence reported by GitHub; read the repository terms before use.
Read pull requestsProposed changes and development discussions.
Browse reported issuesKnown problems, feature requests and maintainer responses.

Development context

These are observations of work in the repository. They do not establish quality, security or support commitments.

Total commits on default branch: 1,713
Open pull requests: 99
Closed issues, lifetime: 244
Median time to close an issue: 7.9 days
Median time to merge a pull request: 6.4 days

Close and merge times use up to 20 most recently updated closed issues or merged pull requests. They omit unresolved work and are context, not a maintenance score. Sample limits.

Other projects in Security, ordered by shared topics and then name. These are discovery links, not equivalence claims.