autofacemonker

v0.2.0 suspicious
4.0
Medium Risk

Automatic 3D facial template registration via MVMP + MeshMonk

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows some benign risks, particularly regarding shell execution and metadata, which could suggest less established or potentially suspicious developer behavior.

  • Shell risk detected, though likely benign
  • Lack of a GitHub repository and single package from the maintainer
Per-check LLM notes
  • Network: No network calls were detected, which is generally safe.
  • Shell: The shell execution appears to be testing command-line interface help functionality, which is usually benign but should be reviewed for context.
  • 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 maintainer has only one package and lacks a GitHub repository, which may indicate a less established or potentially suspicious activity.

📦 Package Quality Overall: Low (3.6/10)

✦ High Test Suite 9.0

Test suite present — 3 test file(s) found

  • Test runner config found: pyproject.toml
  • 3 test file(s) detected (e.g. test_autofacemonker.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (2880 chars)
○ 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 score 2.0

Found 1 shell execution pattern(s)

  • test_cli_help(): result = subprocess.run( [sys.executable, "-m", "autofacemonker._cli", "--he
Credential Harvesting

No credential harvesting patterns detected

Typosquatting

No typosquatting candidates detected

Registered Email Domain

No author email provided

Suspicious Page Links

All external links appear legitimate

Git Repository History

No GitHub repository linked

  • No GitHub repository link found
Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "gfacchi-dev" appears to have only 1 package on PyPI (new or inactive account)
Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with autofacemonker
Create a facial recognition mini-app using the 'autofacemonker' package in Python. This app will enable users to upload images of faces and automatically register them into a 3D facial template database using the MVMP (Multi-View Matching Process) and MeshMonk techniques provided by the package. The application should include the following features:

1. User Interface: A simple and intuitive web interface where users can upload face images.
2. Image Processing: Utilize 'autofacemonker' to process the uploaded images, converting them into 3D facial templates.
3. Database Storage: Store the generated 3D templates in a local SQLite database.
4. Template Matching: Implement a feature to match new uploaded faces against existing templates to identify previously registered faces.
5. Visualization: Display a 3D visualization of the matched face template for verification.
6. Security Measures: Ensure all user-uploaded images are stored securely and deleted after processing.

How 'autofacemonker' is utilized:
- Use 'autofacemonker' to perform the automatic 3D facial template registration from the uploaded images.
- Apply MVMP and MeshMonk functionalities provided by 'autofacemonker' to enhance the accuracy of the facial templates.
- Integrate 'autofacemonker' functions to compare new face images with the stored templates for identification purposes.

This project aims to demonstrate the power of 'autofacemonker' in real-world applications and provide a practical tool for facial recognition tasks.

💬 Discussion Feed

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