audawispr

v0.1.4 suspicious
5.0
Medium Risk

Turn language-learning audio into Anki-ready study materials.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate risks related to shell execution and metadata, which require closer scrutiny. Although no immediate malicious activities are evident, the combination of these factors raises concerns about potential supply-chain risks.

  • Moderate shell execution risk
  • Inactive maintainer with low community engagement
Per-check LLM notes
  • Network: No network calls detected, indicating low risk for direct exfiltration or command and control activities.
  • Shell: Shell execution patterns are present but appear to be for version checks or utility operations, suggesting moderate risk that requires further investigation into the purpose of these commands.
  • Obfuscation: The obfuscation pattern is somewhat unusual but does not necessarily indicate malicious intent; it could be an attempt to avoid simple code analysis.
  • Credentials: No patterns indicative of credential harvesting were found.
  • Metadata: The maintainer seems new or inactive, and the repository lacks community engagement.

📦 Package Quality Overall: Medium (5.2/10)

✦ High Test Suite 9.0

Test suite present — 12 test file(s) found

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

Some documentation present

  • Detailed PyPI description (5542 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

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

Limited contributor diversity

  • 1 unique contributor(s) across 100 commits in lanhhoang/audawispr
  • Single author but highly active (100 commits)

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

  • ry: exc = getattr(__import__("audawispr", fromlist=[name]), name) exception_objects[name] = exc
⚠ Shell / Subprocess Execution score 6.0

Found 3 shell execution pattern(s)

  • try: completed = subprocess.run( [ ffprobe.path,
  • try: result = subprocess.run( [ ffmpeg_path,
  • try: completed = subprocess.run( [str(path), "-version"], check=Fals
✓ 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 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Lanh Hoang" 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 audawispr 
Create a mini-application named 'AnkiAuditor' that leverages the 'audawispr' package to convert language learning audio files into structured Anki flashcard decks. The application should perform the following steps:

1. Allow users to upload one or more audio files of language lessons.
2. Process these audio files using 'audawispr' to extract key phrases and vocabulary.
3. Automatically generate Anki flashcards from the extracted content, ensuring each card includes the phrase/vocabulary, its translation, and an example sentence if available.
4. Provide an option for users to review and edit the generated flashcards before finalizing the deck.
5. Export the finalized flashcard deck in the Anki format (.apkg file).

Suggested Features:
- Support for multiple languages through user selection or automatic detection.
- Integration with cloud storage services like Google Drive or Dropbox for easy sharing and backup.
- A user-friendly GUI built with PyQt or Tkinter for a seamless experience.
- Advanced settings allowing customization of flashcard types (e.g., cloze deletion, image recognition).

The 'audawispr' package will be utilized throughout the process for extracting meaningful content from audio files, which is then transformed into educational material suitable for Anki.

💬 Discussion Feed

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