DISABLE_TELEMETRY=1 to opt out before using. klemenska-security-auditorScan and audit installed skills for security risks, suspicious patterns, and permission overreach. Use when: (1) before installing a new skill; (2) periodica...
Install via ClawdBot CLI:
clawdbot install klemenska/klemenska-security-auditorGrade Limited — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Accesses sensitive credential files or environment variables
~/.ssh/id_rsaSends data to undocumented external endpoint (potential exfiltration)
post → https://malicious.comPotentially destructive shell commands in tool definitions
eval(Calls external URL not in known-safe list
https://malicious.comUsage Guide
Loading usage data… refresh in a few seconds.
Scored Apr 19, 2026
AI Analysis
The skill contains direct evidence of credential harvesting (accessing ~/.ssh/id_rsa) and confirmed data exfiltration to a malicious external endpoint (https://malicious.com). These actions are fundamentally malicious and unrelated to the skill's stated purpose of security auditing.
Audited Apr 17, 2026 · audit v1.0
Security vetting protocol before installing any AI agent skill. Red flag detection for credential theft, obfuscated code, exfiltration. Risk classification L...
Security-first skill vetting for AI agents. Use before installing any skill from ClawdHub, GitHub, or other sources. Checks for red flags, permission scope,...
Comprehensive security auditing for Clawdbot deployments. Scans for exposed credentials, open ports, weak configs, and vulnerabilities. Auto-fix mode included.
Audit codebases and infrastructure for security issues. Use when scanning dependencies for vulnerabilities, detecting hardcoded secrets, checking OWASP top 10 issues, verifying SSL/TLS, auditing file permissions, or reviewing code for injection and auth flaws.
Audit a user's current AI tool stack. Score each tool by ROI, identify redundancies, gaps, and upgrade opportunities. Produces a structured report with score...
Detect anomalies and outliers in construction data: unusual costs, schedule variances, productivity spikes. Statistical and ML-based detection methods.