audd

v1.5.12 suspicious
4.0
Medium Risk

Official Python SDK for the AudD music recognition API.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows typical behavior for legitimate use but raises some concerns due to incomplete author metadata and potentially inactive account.

  • Incomplete author metadata
  • Potentially inactive package account
Per-check LLM notes
  • Network: The observed network patterns are typical for packages that make HTTP requests to external services, suggesting legitimate API interactions.
  • Shell: No shell execution patterns were detected, indicating no immediate risk associated with unauthorized command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author's information is incomplete and the account seems new or inactive, raising some suspicion. However, no clear malicious activities are indicated.

📦 Package Quality Overall: Medium (6.0/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://docs.audd.io
  • Detailed PyPI description (15911 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • 121 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 4 commits in AudDMusic/audd-python
  • Two distinct contributors found

🔬 Heuristic Checks

⚠ Outbound Network Calls score 6.0

Found 4 network call pattern(s)

  • elf._client = httpx_client or httpx.Client( timeout=timeouts, headers={"User-Ag
  • elf._client = httpx_client or httpx.AsyncClient( timeout=timeouts, headers={"User-Ag
  • elf._client = httpx_client or httpx.Client( timeout=httpx.Timeout(connect=10.0, read=120.0,
  • elf._client = httpx_client or httpx.AsyncClient( timeout=httpx.Timeout(connect=10.0, read=120.0,
✓ 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: audd.io>

⚠ Suspicious Page Links score 2.0

Found 1 suspicious link(s) on the package page

  • Non-HTTPS external link: http://corp-proxy:8080
✓ Git Repository History

Repository AudDMusic/audd-python 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 audd 
Create a music recognition app using the 'audd' Python package. Your application will allow users to upload audio clips or record short snippets of music and then identify the song title and artist. Here are the steps and features you need to implement:

1. **Setup Environment**: Ensure your development environment is set up with Python and the 'audd' package installed.
2. **User Interface**: Develop a simple yet intuitive user interface where users can either upload an audio file or use their device's microphone to capture a short clip of music.
3. **Audio Processing**: Use the 'audd' package to process the uploaded or recorded audio clip. The package allows for easy integration with the AudD API for music recognition.
4. **Display Results**: Once the song is identified, display the results on the UI, including the song title, artist name, album cover, and a link to the song on Spotify or another streaming platform if available.
5. **Optional Features**:
   - **History Feature**: Keep track of all recognized songs and allow users to view their history.
   - **Favorites**: Enable users to mark their favorite recognized songs.
   - **Integration with Social Media**: Allow users to share their recognized songs directly to social media platforms like Twitter or Instagram.
6. **Testing and Deployment**: Test the application thoroughly to ensure it works as expected, then deploy it on a web server or a cloud service like Heroku.

The 'audd' package simplifies the process of integrating the AudD API into your application, allowing you to focus more on building out the user experience and additional features.

💬 Discussion Feed

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