auvux

v0.1.0a8 safe
3.0
Low Risk

Annotate faster. See deeper. Sound smarter.

🤖 AI Analysis

Final verdict: SAFE

The package appears safe with minimal risks identified. The primary concern lies in the metadata risk due to sparse maintainer information, but this alone does not conclusively indicate malicious intent.

  • Network calls are likely legitimate for API interactions.
  • Sparse maintainer information raises minor concerns.
Per-check LLM notes
  • Network: The observed network calls are likely for authentication and API interactions, which could be legitimate depending on the package's functionality. However, the specific endpoints and data being transmitted should be reviewed.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, suggesting no immediate risk related to secret or credential theft.
  • Metadata: The repository is not found and the maintainer information is sparse, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Low (2.8/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (3560 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

  • 72 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Could not retrieve contributor data from GitHub

  • GitHub API error: 404

🔬 Heuristic Checks

⚠ Outbound Network Calls score 7.5

Found 5 network call pattern(s)

  • UA string. """ req = urllib.request.Request( api_base.rstrip("/") + "/api/auth/cli-excha
  • method="POST", ) with urllib.request.urlopen(req, timeout=30) as resp: return json.loads(
  • de(fields).encode() req = urllib.request.Request( url, data=data, headers={
  • as bot traffic.""" req = urllib.request.Request(url, headers={ "User-Agent": "auvux/0.1 (+ht
  • cept": "*/*", }) with urllib.request.urlopen(req, timeout=60) as resp: return resp.read()
✓ 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: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 3.0

Repository not found (deleted or private)

  • Repository not found (deleted or private)
⚠ 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 auvux 
Create a mini-application named 'SoundExplorer' that leverages the capabilities of the 'auvux' Python package to provide users with an interactive and efficient way to analyze audio files. This application will enable users to upload their audio files, perform real-time annotations, and gain deep insights into the sound characteristics through visualizations and summaries. Here’s a step-by-step guide on how to develop this application:

1. **Setup Environment**: Begin by setting up your development environment. Ensure you have Python installed along with necessary libraries such as Flask for web framework and auvux for sound analysis.
2. **Application Structure**: Design the application structure. It should include a user-friendly interface where users can upload their audio files, view real-time annotations, and access detailed reports.
3. **Audio Upload Feature**: Implement a feature that allows users to easily upload their audio files. Use Flask's file handling capabilities to manage file uploads.
4. **Real-Time Annotation**: Utilize the 'auvux' package to enable real-time annotation of uploaded audio files. Users should be able to interactively mark sections of interest within the audio timeline.
5. **Deep Analysis & Visualization**: Develop functionalities within the application to perform deep analysis on the annotated segments using 'auvux'. Visualize the results through graphs and charts, providing insights into sound patterns, frequencies, and more.
6. **Summary Report Generation**: Create a feature that generates comprehensive summary reports based on the analyzed data. These reports should highlight key findings from the audio analysis.
7. **User Interface Enhancements**: Improve the user interface to ensure it is intuitive and accessible. Include features like zoom-in/zoom-out functionality for better interaction with the audio timeline.
8. **Testing & Validation**: Rigorously test the application to ensure all functionalities work as expected. Validate the accuracy of the annotations and analysis provided by 'auvux'.
9. **Deployment**: Prepare the application for deployment. Consider hosting options such as Heroku or AWS to make the application accessible online.

Suggested Features:
- Real-time playback of audio files within the application.
- Interactive controls to adjust playback speed and volume.
- Support for exporting annotations and summary reports in various formats (CSV, PDF).
- Integration with social media platforms for sharing analysis results.

By following these steps and incorporating the suggested features, you'll create a powerful tool for anyone interested in exploring and understanding audio content more deeply.

💬 Discussion Feed

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