cellpose-cell-segmentation

Pass

Audited by Gen Agent Trust Hub on Apr 28, 2026

Risk Level: SAFE
Full Analysis
  • [SAFE]: The skill serves as a technical manual for the Cellpose library. Analysis across all threat categories (obfuscation, exfiltration, prompt injection, etc.) yielded no findings.
  • [EXTERNAL_DOWNLOADS]: The skill recommends installing standard scientific Python packages including cellpose, numpy, matplotlib, torch, torchvision, torchaudio, scikit-image, and pandas. Installation commands for GPU support correctly reference the official PyTorch download index (download.pytorch.org).
  • [COMMAND_EXECUTION]: Code snippets demonstrate local file operations using scikit-image for reading images and numpy/pandas for saving results. These operations are within the expected scope of an image processing workflow.
  • [INDIRECT_PROMPT_INJECTION]: While the skill ingests external image data via io.imread, this represents a standard data processing surface with negligible risk of prompt injection in this specific scientific context.
Audit Metadata
Risk Level
SAFE
Analyzed
Apr 28, 2026, 02:12 PM