apify

v3.4.1 safe
3.0
Low Risk

Apify SDK for Python

🤖 AI Analysis

Final verdict: SAFE

The package is deemed safe with low risk scores across all categories except for obfuscation, which still remains within acceptable levels.

  • Low network and shell risks
  • Moderate obfuscation risk due to base64 encoding practices
  • Low credential risk
Per-check LLM notes
  • Network: The use of async HTTP requests is common for fetching remote resources and does not necessarily indicate malicious activity.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: The use of base64 encoding and decoding for sensitive data suggests some level of obfuscation, but it's also common practice in many applications to encode/decode data securely.
  • Credentials: No direct evidence of credential harvesting is found, but caution should be exercised as handling of encoded credentials requires proper security measures.

📦 Package Quality Overall: Medium (6.4/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://docs.apify.com/sdk/python/docs/overview
  • Detailed PyPI description (7845 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

  • 192 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 12 unique contributor(s) across 100 commits in apify/apify-sdk-python
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • nput() async with httpx.AsyncClient() as client: response = await client.get(act
⚠ Code Obfuscation score 10.0

Found 5 obfuscation pattern(s)

  • encrypted_password_bytes = base64.b64decode(encrypted_password.encode('utf-8')) encrypted_value_byte
  • ) encrypted_value_bytes = base64.b64decode(encrypted_value.encode('utf-8')) # Decrypt the password
  • load_pem_private_key( base64.b64decode(private_key_file_base64.encode('utf-8')), password=p
  • alization.load_pem_public_key(base64.b64decode(public_key_file_base64.encode('utf-8'))) if not isinstan
  • scrapy_request_dict = pickle.loads(codecs.decode(scrapy_request_dict_encoded.encode(), 'base64'
✓ 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: apify.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository apify/apify-sdk-python 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 apify 
Create a web scraping utility named 'WebScraperPro' using the Apify SDK for Python. This utility will allow users to scrape data from any website they input and store the scraped data in a structured format such as CSV or JSON. The application should include the following core functionalities:

1. User Input: The user should be able to input the URL of the website they want to scrape.
2. Customizable Scraping Rules: Users should have the option to define which elements on the webpage they want to extract (e.g., title, description, images).
3. Pagination Handling: If the website has multiple pages of content, the utility should be able to navigate through these pages and scrape all available data.
4. Data Storage: Once the data is scraped, it should be saved in a structured format such as CSV or JSON.
5. Error Handling: Implement error handling to manage issues like connection timeouts or broken links.
6. Logging: The application should log all actions and errors for debugging purposes.
7. Optional Features: Consider adding features like email notifications upon completion of scraping or support for scraping AJAX-based websites.

To utilize the Apify SDK for Python, you'll need to initialize an Apify client within your Python script. Use the `ApifyClient` class to interact with Apify's services. For instance, you might use actors or datasets provided by Apify to streamline the scraping process and data storage. Make sure to include detailed comments in your code explaining each step of the process and how Apify's SDK is being utilized.

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