audia

v0.7.3 suspicious
4.0
Medium Risk

An agentic Python package that converts ideas and documents into audio – PDF papers, reports, and regulations turned into podcast-style audio files.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package audia v0.7.3 exhibits moderate risks due to potential shell execution and network calls to external sources, which could pose a threat if these sources are compromised or malicious.

  • Moderate network risk
  • Potential shell execution risks
Per-check LLM notes
  • Network: The network calls appear to be fetching resources from URLs which may be part of the package's functionality, but could also indicate external dependency on untrusted sources.
  • Shell: The shell execution patterns seem to open files or URLs using OS commands based on the operating system type, which is potentially risky as it can lead to arbitrary command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has only one package on PyPI, which might indicate a new or less active account, but no other red flags were found.

📦 Package Quality Overall: Medium (5.8/10)

✦ High Test Suite 9.0

Test suite present — 11 test file(s) found

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

Some documentation present

  • Documentation URL: "Documentation" -> https://audia.readthedocs.io
  • Detailed PyPI description (8820 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

  • 105 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 52 commits in yauheniya-ai/audia
  • Two distinct contributors found

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

  • try: with socket.create_connection((_host, _port), timeout=0.5): break
  • header&start=0" req = urllib.request.Request(url, headers={"User-Agent": "audia/0.1 (research fal
  • rch fallback)"}) with urllib.request.urlopen(req, timeout=40) as resp: body = resp.re
  • aper.arxiv_id}" req = urllib.request.Request( pdf_url, headers={
  • }, ) with urllib.request.urlopen(req, timeout=30) as resp: target.write_b
  • "audia.agents.research.urllib.request.urlopen", return_value=fake_response ) as mock_o
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 4.0

Found 2 shell execution pattern(s)

  • f system == "Darwin": subprocess.call(["open", path]) elif system == "Linux": subproce
  • if system == "Linux": subprocess.call(["xdg-open", path]) elif system == "Windows": im
✓ 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

Repository yauheniya-ai/audia appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Yauheniya Varabyova" 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 audia 
Develop a Python-based mini-application named 'DocToPod' that leverages the 'audia' package to convert academic articles from PDF format into podcast-style audio files. This application will be particularly useful for researchers and students who prefer listening to their reading material on-the-go. Here’s a detailed step-by-step guide on how to build this application:

1. **Project Setup**: Begin by setting up your Python environment and installing necessary packages including 'audia', 'PyPDF2' for PDF handling, and 'tqdm' for progress tracking.
2. **User Interface**: Create a simple command-line interface (CLI) where users can input the path of the PDF file they wish to convert.
3. **PDF Parsing**: Implement a function to parse the content of the PDF using 'PyPDF2'. Ensure that any non-text elements like images and tables are ignored.
4. **Text Cleaning**: Develop a text cleaning mechanism within the 'audia' package integration to remove unnecessary formatting and ensure the text flows well when read aloud.
5. **Voice Selection**: Allow users to select from different voice options provided by 'audia' for the conversion process. Include at least three different voices to cater to various preferences.
6. **Audio Generation**: Use 'audia' to convert the cleaned text into an audio file. Customize the output settings to mimic a podcast style, such as adding introductory and closing remarks, and possibly background music.
7. **Output Delivery**: Once the conversion is complete, save the audio file in a specified directory and provide feedback to the user about its location and name.
8. **Error Handling**: Implement robust error handling to manage cases where the PDF file is corrupted or the text cannot be converted due to complex formatting issues.
9. **Testing & Documentation**: Conduct thorough testing of the application with various types of PDFs and document structures. Write clear documentation detailing how to install and use the application effectively.

This project not only showcases the capabilities of 'audia' but also provides a practical solution for converting static documents into dynamic, listenable formats.

💬 Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!