Scan Report
5 /100
mouse-yolo-factory
Mouse YOLO Factory - YOLO integration skill for mouse product defect detection including scratch generation, auto-labeling, and dataset merging
This is a legitimate YOLO-based computer vision tool for mouse product defect detection with no malicious behavior detected.
Safe to install
This skill is safe to use. No security concerns were identified.
| Resource | Declared | Inferred | Status | Evidence |
|---|---|---|---|---|
| Filesystem | NONE | READ | ✓ Aligned | All scripts perform image I/O operations |
| Filesystem | NONE | WRITE | ✓ Aligned | Creates output directories and saves processed images |
| Network | NONE | READ | ✓ Aligned | YOLO model loading is standard ML behavior |
| Shell | NONE | NONE | — | No shell execution found |
| Environment | NONE | NONE | — | No environment variable access |
| credential | NONE | NONE | — | No credential access detected |
File Tree
5 files · 45.9 KB · 1250 lines Python 4f · 1219L
Markdown 1f · 31L
├─
DatasetManager.py
Python
├─
datatool.py
Python
├─
drawbox_and_dataset_savejson_with_model.py
Python
├─
Mouse_produce_scratch.py
Python
└─
SKILL.md
Markdown
Dependencies 6 items
| Package | Version | Source | Known Vulns | Notes |
|---|---|---|---|---|
ultralytics | * | pip | No | YOLO framework - standard ML library |
opencv-python | * | pip | No | Standard computer vision library |
numpy | * | pip | No | Standard numerical library |
torch | * | pip | No | PyTorch - standard ML framework |
tqdm | * | pip | No | Progress bar utility |
pandas | * | pip | No | Data manipulation library |
Security Positives
✓ Uses standard, well-known ML libraries (ultralytics, opencv, numpy, torch)
✓ No network exfiltration or C2 communication
✓ No credential harvesting or environment variable iteration
✓ No obfuscation techniques (base64, eval, etc.)
✓ Documentation accurately describes functionality
✓ No remote script execution or curl|bash patterns
✓ No access to sensitive paths (~/.ssh, ~/.aws, .env)
✓ No supply chain risks detected in dependencies