Security for your OpenClaw agent skill before they run
Summary
SecureSkill is a tool that performs 10-layer security analysis on OpenClaw agent skills before execution, detecting threats like credential harvesting, outbound calls, and shell scripts. It produces a signed audit report mapped to OWASP, MITRE, NIST, and EU AI Act standards.
Similar Articles
ClawHub Security Signals: When VirusTotal, Static Analysis, and SkillSpector Disagree
This paper investigates security scanner disagreement for AI agent skills, finding that VirusTotal, static analysis, and NVIDIA SkillSpector flag different skills with minimal overlap. It releases a sanitized dataset of over 67,000 skill versions to support further research on layered security governance.
Where OpenClaw Security Is Heading
OpenClaw details its security architecture using `fs-safe` for filesystem boundaries and Proxyline for network egress control, aiming to make its AI personal assistant trustworthy and auditable.
I analyzed 800+ OpenClaw skills on GitHub so you don't have to. Here's what I found
The author analyzed over 800 OpenClaw skills on GitHub and is building a better alternative to ClawHub, targeting developers using Claude, Cursor, or OpenClaw. Beta launching soon.
Built Skill Factory, a meta-skill for creating OpenClaw skills
The author released 'Skill Factory', a meta-skill for OpenClaw that provides a structured workflow for creating, iterating, and publishing skills, aiming to improve transparency and ease of construction.
I got paranoid about OpenClaw skills injecting crap into my system prompt, so I built a quarantine pipeline with two LLMs as reviewers (93.75% detection, zero false negatives)
A developer built a quarantine pipeline using two LLM reviewers (Claude and Codex) to detect injection attacks in OpenClaw skills, achieving 93.75% detection rate with zero false negatives. The system uses a dual mandate of checklist-based pattern matching and open analysis to catch both known and novel injection techniques.