auditok

v0.4.2 safe
3.0
Low Risk

An audio/acoustic activity detection and audio segmentation tool

🤖 AI Analysis

Final verdict: SAFE

The package does not exhibit significant risks, with no network calls or credential harvesting detected. However, the incomplete maintainer profile and use of subprocess execution warrant further attention.

  • Incomplete maintainer profile
  • Subprocess execution
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external services.
  • Shell: Subprocess execution may be legitimate for certain functionalities but could indicate potential risk if commands are dynamically generated from user input.
  • Obfuscation: The observed patterns suggest the use of Base64 encoding and decoding which is commonly used for data serialization and not necessarily indicative of malicious activity.
  • Credentials: No suspicious patterns related to credential harvesting were detected.
  • Metadata: The maintainer has an incomplete profile and seems to be new or inactive, raising some suspicion but not conclusive evidence of malintent.

📦 Package Quality Overall: Medium (6.0/10)

✦ High Test Suite 9.0

Test suite present — 13 test file(s) found

  • Test runner config found: pyproject.toml
  • 13 test file(s) detected (e.g. test_AudioReader.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://auditok.readthedocs.io/
  • Detailed PyPI description (12384 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

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

Limited contributor diversity

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

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 6.0

Found 3 obfuscation pattern(s)

  • x('"', start) wav_bytes = base64.b64decode(html[start:end]) buf = io.BytesIO(wav_bytes) with wa
  • , sw=2, ch=1) wav_bytes = base64.b64decode(b64) buf = io.BytesIO(wav_bytes) with wave.open(buf,
  • = {} original_init = __import__( "auditok.io", fromlist=["FFmpegAudioSource"] ).FFmpegAudioSource.__init__ def spy_init(
⚠ Shell / Subprocess Execution score 10.0

Found 5 shell execution pattern(s)

  • t(file=filename) os.system(command) if self._logger is not None:
  • : self._process = subprocess.Popen( cmd, stdout=subprocess.PIPE
  • ile)] try: proc = subprocess.Popen( cmd, stdin=subprocess.PIPE,
  • and): try: with subprocess.Popen( command, stdin=open(os.devnull, "
  • filepath), ] result = subprocess.run(cmd, capture_output=True, text=True) info = json.loads(r
✓ 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

Repository amsehili/auditok 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 auditok 
Create a real-time speech activity detector using the 'auditok' package in Python. This application will monitor live audio input from a microphone and detect moments of speech activity, marking these segments for further processing or logging. The app should be able to differentiate between periods of silence and speech, outputting timestamps for when speech begins and ends. Additionally, implement a feature to save detected speech segments as separate audio files for later analysis or transcription. Consider adding options to adjust sensitivity levels to account for varying environmental noise conditions. The application should also include a user-friendly interface to control settings such as input source selection, sensitivity adjustment, and output format preferences. Use 'auditok' to handle the core functionality of audio segmentation and activity detection.

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