anson.py3

v0.5.1 suspicious
6.0
Medium Risk

Anson for Python3

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits signs of obfuscation and lacks critical metadata, raising suspicion about its legitimacy and potential for malicious activities.

  • Obfuscation risk is high at 7/10
  • Missing maintainer's author name and potentially inactive maintainer
Per-check LLM notes
  • Obfuscation: The code shows signs of obfuscation through unconventional method invocations and variable names which could be used to hide malicious activity.
  • Credentials: No clear patterns indicative of credential harvesting were found.
  • Metadata: The maintainer's author name is missing and they seem to be new or inactive, which raises some concerns but does not definitively indicate malicious intent.

📦 Package Quality Overall: Medium (5.6/10)

✦ High Test Suite 9.0

Test suite present — 17 test file(s) found

  • 17 test file(s) detected (e.g. ansontypes.py)
◈ Medium Documentation 7.0

Some documentation present

  • 1 documentation file(s) (e.g. singleton.py)
  • Detailed PyPI description (3666 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 97 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 5.0

Limited contributor diversity

  • 1 unique contributor(s) across 100 commits in odys-z/antson
  • Single author but highly active (100 commits)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • k(False)) resp = requests.post(f'{self.myservRt}/{req.port.value}',
⚠ Code Obfuscation score 6.0

Found 3 obfuscation pattern(s)

  • ath}.{m}' module = __import__(adjustMoudlename(m), fromlist=[clssn]) cls = getattr(module, clssn) c
  • ".join(parts[:-1]) # m = __import__(module if module is not None else '__main__') # for comp in parts[1:]: # m = getattr(m, com
  • port the module module = __import__(module_name, fromlist=[class_name]) # Get the class cls = getattr(module, class_nam
⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

  • windows() else 'python3' os.system(f'{python} {script_path}') test_loader = unittest.TestLoa
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository odys-z/antson appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" 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 anson.py3 
Create a fully-functional mini-app that leverages the 'anson.py3' package to manage and analyze audio files efficiently. Your application should allow users to perform various operations on their audio files such as converting formats, extracting metadata, and performing basic analysis like duration calculation and file size optimization. Additionally, the app should support batch processing of multiple files at once.

Step-by-Step Instructions:
1. Setup your development environment with Python 3.x and install the 'anson.py3' package along with any other necessary dependencies.
2. Design a user-friendly interface where users can upload one or more audio files for processing.
3. Implement functionality to convert uploaded audio files into different formats supported by 'anson.py3'.
4. Add a feature to extract and display metadata from the audio files such as title, artist, album, and duration.
5. Develop a simple analysis tool within the app to calculate the total duration of all uploaded files combined.
6. Include an option for users to optimize file sizes without significant loss in quality using 'anson.py3' capabilities.
7. Ensure the app supports batch processing; users should be able to select multiple files for conversion, metadata extraction, analysis, or optimization at once.
8. Test each feature thoroughly to ensure they work as expected.
9. Document your code and provide clear instructions on how to run the application.

Suggested Features:
- Support for common audio formats (MP3, WAV, FLAC).
- Ability to save converted files directly to a specified directory.
- Enhanced error handling to gracefully manage unsupported file types or issues during processing.
- Option to download processed files directly from the app.
- User authentication and file storage management for registered users.

How 'anson.py3' is Utilized:
- Use 'anson.py3' for reading, writing, and converting between different audio file formats.
- Leverage its metadata extraction capabilities to gather and display information about each file.
- Employ 'anson.py3' for analyzing audio files, including calculating durations and optimizing file sizes while maintaining acceptable sound quality.

💬 Discussion Feed

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