audio-transcriber

v0.32.0 suspicious
5.0
Medium Risk

Transcribe your .wav .mp4 .mp3 .flac files to text or record your own audio!

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows signs of potential misuse through shell command execution and obfuscated code, which could be leveraged for malicious purposes. However, there is insufficient evidence to conclusively label it as malicious.

  • High shell risk due to potential misuse of shell commands
  • Moderate obfuscation risk suggesting possible hidden logic or data
Per-check LLM notes
  • Network: The network call might be for legitimate API requests related to audio transcription services.
  • Shell: Executing shell commands like 'git ls-files' could indicate interaction with version control systems, but it may also pose risks if used for unintended purposes.
  • Obfuscation: The use of base64 encoding is common for data transmission and storage, but the partial code suggests potential for hiding logic or data, warranting further scrutiny.
  • Credentials: No direct evidence of credential harvesting was found in the provided snippet.
  • Metadata: The package has no GitHub link and the maintainer's information is sparse, indicating potential unreliability.

📦 Package Quality Overall: Medium (5.2/10)

✦ High Test Suite 9.0

Test suite present — 10 test file(s) found

  • Test runner config found: conftest.py
  • 10 test file(s) detected (e.g. conftest.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (12030 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

  • Type checker (mypy / pyright / pytype) referenced in project
  • 37 type-annotated function signatures detected in source
○ 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 score 1.5

Found 1 network call pattern(s)

  • able?", ] async with httpx.AsyncClient(timeout=10000.0) as client: for q in questions:
⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

  • yield base64.b64decode(data["audio"]) except json.JSONDecodeEr
⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

  • h): try: result = subprocess.run( ["git", "ls-files", "--cached", "--others", "--
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

⚠ Suspicious Page Links score 2.0

Found 1 suspicious link(s) on the package page

  • Non-HTTPS external link: http://audio-transcriber-mcp:8000/mcp
✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ 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 audio-transcriber 
Develop a user-friendly mini-application named 'AudioTranscribe' using Python that leverages the 'audio-transcriber' package to transcribe audio files into text. The application should support various file formats including .wav, .mp4, .mp3, and .flac. Additionally, it should allow users to record their own audio directly from their device's microphone and transcribe it. The application should have the following functionalities:

1. **File Upload**: Users should be able to upload their audio files via a simple interface.
2. **Recording Audio**: Implement a feature where users can record new audio clips directly within the application.
3. **Transcription**: Upon uploading or recording, the application should automatically transcribe the audio content into text.
4. **Saving Transcriptions**: After transcription, the text should be saved either locally or uploaded to a cloud storage service like AWS S3, allowing users to retrieve their transcriptions later.
5. **Real-time Progress Updates**: During the transcription process, display real-time progress updates to inform the user about the status of the transcription.
6. **Error Handling**: Ensure robust error handling to manage cases where the file format is unsupported, the audio quality is too poor for transcription, or other potential issues.
7. **User Interface**: Design a clean and intuitive user interface that guides users through each step of the process, from file upload/recording to viewing the transcribed text.
8. **Customization Options**: Allow users to customize the output text format (e.g., plain text, markdown) and choose between different languages for transcription.

To achieve these goals, you will need to utilize the 'audio-transcriber' package for its core functionality of converting audio files into text. Pay special attention to integrating the package's API seamlessly with your application's workflow, ensuring a smooth user experience.

💬 Discussion Feed

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