CLAW skill security
CLAW and OpenClaw skills execute real code on your machine — reading files, calling APIs, launching browsers, and running scripts. Before granting an agent skill access to your environment, run this 5-step security review so you know exactly what you are installing.
This guide covers manifest review, secrets scanning across the full git history, dependency CVE auditing, static analysis with the OWASP ruleset, and scanning the skill's deployed web endpoint with CyberLens AI.
Before running any scanner, read what the skill claims to do. Check the manifest for declared permissions: filesystem access, network calls, browser control, messaging. A skill that needs write access outside its working directory or credentials to external accounts warrants extra scrutiny.
Clone the skill repository and run gitleaks across the full commit history. AI-generated and community-contributed skills frequently contain API keys, tokens, or passwords committed during development — including in deleted files and rebase history.
Skills that install npm, pip, or container dependencies inherit their vulnerability surface. Run npm audit, pip-audit, or Trivy before granting the skill access to your environment.
Semgrep with the OWASP Top 10 ruleset catches risky patterns that secrets and dependency scanners miss: command injection, path traversal, unsafe deserialization, and overly permissive network configurations.
If the skill exposes a web interface, admin panel, or API endpoint, run a CyberLens AI website scan against it. This surfaces missing security headers, TLS misconfigurations, and runtime risks that static analysis cannot detect.
OpenClaw and CLAW skills are installable workflow packages for AI assistants. They extend an agent's capabilities by providing tools, automation scripts, and configuration that the agent can invoke. Because skills execute real code — accessing files, calling APIs, or launching browsers — their security posture matters before installation.
Passing these checks significantly reduces obvious risk but does not certify a skill as safe. Skills touching production systems, customer data, external accounts, or high-privilege operations still warrant a manual code review and clear human oversight.
Yes. AI-assisted development tools frequently generate code with hardcoded credentials, overly permissive configurations, and vulnerable dependency versions. Run the same 5-step workflow against skills you create before sharing or publishing them.
CyberLens AI scans the web interface or API endpoint of a deployed skill for missing security headers, TLS issues, exposed metadata, and other runtime risks. It gives you a plain-English risk summary and prioritized remediation steps.
Do not install or activate the skill until the issue is resolved. For skills you maintain, fix the finding, re-run all five scan steps, and confirm the issue is gone before granting agent access.
CyberLens AI guidance is informed by established security standards and public vulnerability intelligence.