async-requests-tls

v0.1.0 safe
4.0
Medium Risk

Async HTTP/1.1 client whose TLS handshake is identical to the `requests` library.

🤖 AI Analysis

Final verdict: SAFE

The package exhibits low risks across network, shell, and credential aspects, indicating benign behavior. While there is a moderate obfuscation risk due to potential data compression techniques, and some metadata concerns regarding the maintainer's activity, these do not strongly indicate malicious intent.

  • Low network and shell execution risks
  • Moderate obfuscation risk due to zlib usage
  • No evidence of credential theft or supply-chain attack
Per-check LLM notes
  • Network: No network call patterns detected, which is normal for a package focused on async requests and TLS.
  • Shell: No shell execution patterns detected, aligning with expectations for a package designed to handle asynchronous HTTP requests.
  • Obfuscation: The code attempts to decompress content using zlib, which could be used for obfuscating data but is also common in legitimate scenarios involving compressed data handling.
  • Credentials: No patterns indicative of credential harvesting were detected.
  • Metadata: The recent and rapid commits and the new maintainer account suggest potential risk, but no concrete evidence of malice.

📦 Package Quality Overall: Medium (5.8/10)

✦ High Test Suite 9.0

Test suite present — 5 test file(s) found

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

Some documentation present

  • Detailed PyPI description (3223 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 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • 27 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 3 commits in OleksandrShcherbinin/async-requests
  • Two distinct contributors found

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 4.0

Found 2 obfuscation pattern(s)

  • try: return zlib.decompress(content) except zlib.error: return zlib.
  • lib.error: return zlib.decompress(content, -zlib.MAX_WBITS) return content def detect_en
✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ 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: All 3 commits happened within 24 hours

  • All 3 commits happened within 24 hours
⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • Author "Oleksandr Shcherbinin" 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 async-requests-tls 
Create a Python-based asynchronous web scraper utility named 'AsyncWebScraper' that leverages the 'async-requests-tls' package to ensure secure and efficient scraping of multiple websites simultaneously. This utility should be capable of fetching HTML content from a list of URLs provided via a CSV file, and then saving the fetched content into individual files named after the domain of each URL.

Step 1: Setup Project Environment
- Install necessary packages including 'async-requests-tls', 'aiofiles' for asynchronous file operations, and 'pandas' for handling CSV files.

Step 2: Define the Scraper Class
- Implement an asynchronous function within the class that reads the CSV file containing URLs.
- Utilize 'async-requests-tls' to asynchronously send GET requests to these URLs ensuring compatibility with 'requests' library's TLS handshake.
- Handle exceptions like timeouts and connection errors gracefully.

Step 3: Save Fetched Content
- For each successfully fetched webpage, save its content into a separate file on disk. The filename should reflect the domain name of the URL.

Suggested Features:
- Command-line interface for user interaction.
- Logging mechanism to record actions and errors during execution.
- Option to specify output directory for saved files.
- Ability to throttle request rate to avoid overloading servers.

How to Use 'async-requests-tls':
- Import the package in your script.
- Use its async methods to perform HTTP requests, ensuring that the TLS handshake is consistent with 'requests'.
- Leverage Python's asyncio framework to manage concurrent tasks efficiently.

💬 Discussion Feed

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