skills/mukul975/anthropic-cybersecurity-skills/detecting-model-extraction-attacks/Gen Agent Trust Hub
detecting-model-extraction-attacks
Pass
Audited by Gen Agent Trust Hub on Jun 23, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill provides defensive tools and scripts for monitoring AI inference APIs and performing authorized red-teaming exercises against the user's own models.
- [EXTERNAL_DOWNLOADS]: The skill references standard, well-known Python packages including 'adversarial-robustness-toolbox', 'scikit-learn', and 'numpy'. All external links point to reputable sources such as the MITRE ATLAS project, NIST, and official project documentation on GitHub and ReadTheDocs.
- [COMMAND_EXECUTION]: The provided Python script ('scripts/agent.py') performs local audit log parsing and model training for authorized security testing. It does not use unsafe execution functions like 'eval()' or 'exec()', nor does it spawn arbitrary subprocesses.
- [DATA_EXFILTRATION]: The skill implements best practices for privacy by hashing input data ('hashlib.sha256') before logging. There are no network operations detected that could exfiltrate sensitive data.
Audit Metadata