assemblyai-transcriber

v0.1.0 suspicious
6.0
Medium Risk

AssemblyAI audio transcription wrapper with optional YouTube download.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits medium risk due to its high shell risk and suspicious repository metadata, despite having no direct evidence of malicious activity or credential harvesting.

  • High shell risk due to subprocess usage
  • Suspicious repository metadata and low activity
Per-check LLM notes
  • Network: The network call to upload data is likely intended for transcribing audio files using AssemblyAI's service.
  • Shell: Executing commands via subprocess.run can be risky if not properly sanitized, suggesting potential for misuse or accidental execution of harmful commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The repository shows signs of being a throwaway account with suspicious commit patterns and very low activity, raising concerns about potential malicious intent.

📦 Package Quality Overall: Low (4.6/10)

✦ High Test Suite 9.0

Test suite present — 5 test file(s) found

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

Some documentation present

  • Detailed PyPI description (1888 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

  • 31 type-annotated function signatures detected in source
○ Low Multiple Contributors 2.0

Single-author or unverifiable project

  • 1 unique contributor(s) across 3 commits in jerturowetz/assemblyai-transcriber
  • Single author with few commits — possibly a personal or throwaway project

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

  • le_handle: response = requests.post( BASE_URL + "/v2/upload", headers=_g
  • sal-2"], } session = requests.Session() retry = Retry( total=3, backoff_factor
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

  • d.url, ] try: subprocess.run(command, check=True) except subprocess.CalledProcessErro
✓ 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 score 7.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
  • Single contributor with only 3 commit(s) — possibly throwaway account
  • All 3 commits happened within 24 hours
⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • Author "Jeremy Turowetz" 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 assemblyai-transcriber 
Create a command-line utility called 'AudioMaven' that leverages the 'assemblyai-transcriber' package to transcribe audio files from various sources including YouTube videos. This utility should provide users with a seamless way to convert audio content into written text, enhancing accessibility and analysis capabilities. Here are the key steps and features to include:

1. **Setup and Configuration**: Begin by installing the necessary packages, including 'assemblyai-transcriber'. Configure your API keys for AssemblyAI within your application.
2. **User Input Handling**: Design the application to accept user inputs through command-line arguments. Users should be able to specify whether they want to transcribe a local file or a YouTube video URL.
3. **YouTube Video Downloading**: If the user provides a YouTube video URL, utilize the 'assemblyai-transcriber' package's ability to download the video and extract the audio automatically.
4. **Transcription Process**: Implement a feature where the application sends the audio file to AssemblyAI's transcription service via the 'assemblyai-transcriber' package. Ensure the process is efficient and handles large audio files gracefully.
5. **Output Options**: Allow users to choose how they want the transcription outputted. They can opt for the result to be printed directly to the console or saved as a text file on their local machine.
6. **Error Handling and Feedback**: Incorporate robust error handling to manage issues like network errors, unsupported formats, or failed downloads. Provide clear feedback messages to guide users.
7. **Optional Enhancements**: Consider adding features such as automatic language detection, real-time transcription updates, or even integration with other services for further analysis of the transcript data.

By following these guidelines, you'll develop a versatile tool that significantly simplifies the task of converting audio content into text using Python and the 'assemblyai-transcriber' package.

💬 Discussion Feed

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