pydicom
Pass
Audited by Gen Agent Trust Hub on Apr 9, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill relies on industry-standard Python libraries for medical imaging (pydicom), numerical analysis (numpy), and visualization (matplotlib, pillow). All dependencies are well-known and appropriate for the stated purpose.
- [SAFE]: No unauthorized network access or data exfiltration patterns were identified. The scripts operate locally on provided DICOM files.
- [SAFE]: The inclusion of a dedicated anonymization script (
scripts/anonymize_dicom.py) demonstrates a security-first approach to handling sensitive Protected Health Information (PHI) within medical records. - [SAFE]: The provided scripts follow best practices for CLI utilities, including proper argument parsing, error handling, and dependency checks.
- [SAFE]: No evidence of prompt injection, code obfuscation, or persistence mechanisms was found across the instruction files and scripts.
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