abstractvoice

v0.10.17 suspicious
5.0
Medium Risk

Remote-compatible and local TTS/STT, streaming voice output, and optional voice cloning for AI applications

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows moderate risk due to its obfuscated code, which could potentially hide malicious activities, despite having no clear evidence of harmful intent or actions.

  • High obfuscation risk
  • Incomplete and possibly new/inactive author metadata
Per-check LLM notes
  • Network: The observed network calls appear to be legitimate HTTP GET requests used for fetching resources, which is common for packages that require downloading models or other assets.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: The code shows signs of obfuscation through base64 encoding and padding, which may be used to hide the true nature of the data being processed.
  • Credentials: No clear patterns indicating credential harvesting were detected.
  • Metadata: The author's details are incomplete and the account seems new or inactive, which raises some concerns but does not conclusively indicate malicious intent.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 7.5

Found 5 network call pattern(s)

  • n if session is not None else requests.Session() def _headers(self, extra: Optional[Mapping[str, str]]
  • try: with requests.get(url, stream=True, timeout=60) as r:
  • try: resp = requests.get(self.models_url, timeout=timeout) resp.raise_for
  • try: resp = requests.get(self.models_url, timeout=timeout) return resp.st
  • ns), } resp = requests.post(self.chat_url, json=payload, timeout=timeout) resp.r
⚠ Code Obfuscation score 10.0

Found 5 obfuscation pattern(s)

  • raw += "=" * pad return base64.b64decode(raw, validate=False) def extract_audio_bytes_from_response
  • raw + ("=" * pad) return base64.b64decode(raw, validate=False) def _require_store(store: Any) -> Med
  • pass model.eval() try: tokenizer = AutoTokenize
  • ) model.eval() stdout_ctx = contextlib.redirect_stdout(io.String
  • try: model.eval() except Exception: pass self._
✓ 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: abstractcore.ai>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository lpalbou/abstractvoice 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 abstractvoice 
Create a versatile voice assistant application using the 'abstractvoice' package in Python. This application should serve as both a Text-to-Speech (TTS) engine and a Speech-to-Text (STT) converter, with an added feature of voice cloning for personalized experiences. Here’s a detailed breakdown of the steps and features to implement:

1. **Setup**: Begin by installing the 'abstractvoice' package and any other necessary dependencies. Ensure you have a development environment set up with Python.
2. **Core Functionality**: Implement basic TTS and STT functionalities. Use 'abstractvoice' to convert text input from users into spoken words and vice versa, converting spoken words into text.
3. **Voice Cloning**: Integrate voice cloning capabilities into your app. Users should be able to upload their own voice samples which can then be cloned to personalize the TTS experience.
4. **User Interface**: Develop a simple command-line interface (CLI) for interacting with the voice assistant. Additionally, consider adding a graphical user interface (GUI) for a more interactive experience.
5. **Streaming Voice Output**: Utilize 'abstractvoice's streaming capabilities to allow continuous speech output without waiting for full sentences to be processed.
6. **Remote Compatibility**: Ensure the application supports remote execution, allowing users to access the voice assistant over the internet. This could involve setting up a web server or cloud service.
7. **Security and Privacy**: Address user privacy concerns by implementing secure data handling practices and providing options for users to control how their voice data is stored and used.
8. **Testing and Documentation**: Thoroughly test the application for functionality and performance. Document all features and provide instructions on how to use and extend the application.

By following these steps and utilizing the core features of 'abstractvoice', you will create a robust and user-friendly voice assistant application capable of enhancing communication through advanced voice technologies.