aio.core

v0.11.1 suspicious
5.0
Medium Risk

A collection of functional utils for asyncio

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate risk due to potential code obfuscation and shell execution capabilities, which may serve legitimate purposes but require closer scrutiny to rule out malicious intent.

  • High obfuscation risk
  • Potential misuse of subprocess.run
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package is expected to perform network operations.
  • Shell: Use of subprocess.run suggests shell execution capability, which could be legitimate but also warrants further investigation to ensure it's not being used maliciously.
  • Obfuscation: The code pattern suggests an attempt to dynamically import modules using a potentially obfuscated method, which could be used to hide the true purpose of the imports.
  • Credentials: No clear patterns indicating credential harvesting were detected.
  • Metadata: The author has only one package on PyPI, which could indicate a new or less active maintainer, but no other red flags are present.

📦 Package Quality Overall: Low (4.6/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
○ Low Documentation 1.0

No documentation detected

  • No documentation URL, doc files, or meaningful description found
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • 110 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 5 unique contributor(s) across 100 commits in envoyproxy/toolshed
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 4.0

Found 2 obfuscation pattern(s)

  • sed = name.pop(0) found = __import__(used) for n in name: used += '.' + n try:
  • t AttributeError: __import__(used) found = getattr(found, n) return found #
⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

  • pletedProcess: return subprocess.run(*args, **kwargs) def subprocess_args(self, *args, **kwa
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: synca.io

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository envoyproxy/toolshed appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Ryan Northey" 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 aio.core 
Your task is to develop a simple yet efficient asynchronous web scraper using Python's aio.core package. This application will fetch data from multiple URLs concurrently, demonstrating the power of asynchronous programming and aio.core's utility functions. Here’s a detailed breakdown of the project requirements:

1. **Project Overview**: Create a web scraping tool that takes a list of URLs as input and scrapes specific information (e.g., titles, meta descriptions, keywords) from each page. The tool should be able to handle a large number of URLs efficiently.

2. **Features**:
   - Input: Accept a list of URLs from a user.
   - Output: Display scraped data (titles, meta descriptions, keywords) for each URL in a structured format.
   - Error Handling: Implement error handling to manage scenarios such as unreachable URLs or timeouts.
   - Logging: Include logging mechanisms to track the process and any errors encountered during execution.
   - Asynchronous Execution: Use aio.core to ensure the scraping tasks run asynchronously, maximizing efficiency.

3. **Implementation Steps**:
   - Step 1: Install the required packages (`aio.core`, `requests`, `beautifulsoup4`).
   - Step 2: Define a function that scrapes a single URL using BeautifulSoup. This function should utilize aio.core's utility functions to handle asynchronous operations.
   - Step 3: Create a main function that accepts a list of URLs and uses aio.core to manage concurrent scraping tasks.
   - Step 4: Implement logging and error handling within the scraping functions to ensure robustness.
   - Step 5: Test the application with a set of sample URLs to verify its functionality and performance.

4. **Utilizing aio.core**: aio.core provides several utility functions that simplify working with asyncio. Use aio.core's async utilities to manage concurrency, handle exceptions, and optimize your scraping tasks. For example, you might use aio.core to create a pool of workers that can scrape URLs concurrently, ensuring that the application scales well with more URLs.

5. **Additional Enhancements**: Consider adding features like command-line argument parsing for easier usage, or integrating with a database to store scraped data persistently.

Your goal is to demonstrate proficiency in asynchronous programming while showcasing the capabilities of aio.core in a real-world scenario.

💬 Discussion Feed

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