amd-torchvision-device-gfx1153

v0.0.1.dev0 suspicious
4.0
Medium Risk

Placeholder for amd-torchvision-device-gfx1153

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has low technical risks but raises concerns due to metadata issues suggesting poor quality control or transparency.

  • Metadata risk indicates potential lack of transparency
  • Placeholder description suggests incomplete or abandoned project
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires network interactions for its functionality.
  • Shell: No shell execution patterns detected, indicating the package does not execute external commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of malicious credential theft.
  • Metadata: The package shows signs of low effort and potential lack of transparency, raising concerns about its legitimacy.

📦 Package Quality Overall: Low (1.2/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
○ Low Documentation 1.0

No documentation detected

  • No documentation URL, doc files, or meaningful description found
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: example.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ Maintainer History score 8.0

4 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with amd-torchvision-device-gfx1153 
Create a small image processing application using Python that leverages the 'amd-torchvision-device-gfx1153' package for optimized image transformations on AMD GPUs. This application will serve as a basic tool for photographers and graphic designers who want to quickly apply various effects to their images before sharing them online or printing. Here are the steps and features you should include in your project:

1. **Setup**: Ensure the environment is set up with Python 3.8+ and the necessary libraries including 'amd-torchvision-device-gfx1153'.
2. **Image Loading**: Implement functionality to load images from a local directory or URL.
3. **Effect Selection**: Provide a menu of predefined image effects such as grayscale conversion, sepia tone, and blur. Users should be able to select one or more effects to apply.
4. **GPU Acceleration**: Use the 'amd-torchvision-device-gfx1153' package to accelerate the transformation process on AMD GPUs, ensuring fast performance even with high-resolution images.
5. **Preview and Save**: Allow users to preview the transformed image before saving it locally or uploading it to a specified cloud storage service like AWS S3 or Google Drive.
6. **Logging**: Integrate logging to record actions performed on images, such as which effects were applied and when.
7. **User Interface**: Develop a simple command-line interface (CLI) for easy interaction. Consider adding a graphical user interface (GUI) using a library like PyQt or Tkinter for a more interactive experience.

The application should demonstrate efficient use of 'amd-torchvision-device-gfx1153' by showing significant speed improvements in image processing tasks compared to CPU-only methods. Additionally, ensure the code is well-documented and modular for future expansion or integration into larger projects.

💬 Discussion Feed

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