Senior Computer Vision
PassAudited by ClawScan on May 10, 2026.
Overview
This skill appears purpose-aligned for computer-vision work, with the main caution that its model-analysis script should only load trusted model files.
This skill looks appropriate for computer-vision development, but run its scripts only on datasets and model files you trust. Be especially careful with PyTorch .pt/.pth files from unknown sources, and consider using an isolated environment for model analysis and training workflows.
Findings (2)
Artifact-based informational review of SKILL.md, metadata, install specs, static scan signals, and capability signals. ClawScan does not execute the skill or run runtime probes.
If a user analyzes a malicious model file, running the script could execute code on their machine.
The optimizer loads user-supplied PyTorch model files. PyTorch checkpoint loading can involve pickle-style deserialization in common configurations, so an untrusted .pt/.pth file may execute code when analyzed. This is purpose-aligned and user-directed, but it needs caution.
checkpoint = torch.load(str(self.model_path), map_location='cpu')
Only run this script on trusted model files. For untrusted weights, prefer safer formats such as safetensors or ONNX, or update the script to use safer PyTorch loading options where available.
Users have less external context for verifying where the code came from or how it is maintained.
The skill includes runnable Python scripts, but the registry information does not provide an upstream source or homepage for provenance checking.
Source: unknown Homepage: none
Review the included scripts before use, run them in a controlled environment, and pin/install ML dependencies from trusted sources.