AI Analysis
Final verdict: SAFE
The package shows minimal risk with no evidence of malicious intent or obfuscation. While there are some potential risks associated with network and shell operations, these are typical functionalities for a tool of this nature.
- Low obfuscation and credential risk
- Incomplete author metadata
- Common use of 'requests' library
- Use of subprocess for potentially legitimate tasks
Per-check LLM notes
- Network: The use of 'requests' to make HTTP GET calls is common for fetching remote resources and checking health status.
- Shell: Running Python scripts via subprocess can be legitimate for executing tasks within the application, but it may also pose risks if not properly controlled.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The author information is incomplete, but there are no other suspicious flags.
Package Quality Overall: Medium (7.0/10)
✦ High
Test Suite
9.0
Test suite present — 22 test file(s) found
Test runner config found: pyproject.toml22 test file(s) detected (e.g. test_bridge.py)
◈ Medium
Documentation
7.0
Some documentation present
Documentation URL: "Documentation" -> https://yeongseon.github.io/azure-functions-openapi-python/Detailed PyPI description (13284 chars)
○ 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 :: Typed113 type-annotated function signatures detected in source
✦ High
Multiple Contributors
8.0
Active multi-contributor project
3 unique contributor(s) across 100 commits in yeongseon/azure-functions-openapi-pythonSmall but multi-author team (3–4 contributors)
Heuristic Checks
Outbound Network Calls
score 3.0
Found 2 network call pattern(s)
requests.Response: return requests.get(f"{BASE_URL}{path}", timeout=30, **kwargs) # type: ignore[atry: r = requests.get(f"{BASE_URL}/api/health", timeout=10) if r.statu
Code Obfuscation
No obfuscation patterns detected
Shell / Subprocess Execution
score 2.0
Found 1 shell execution pattern(s)
import sys result = subprocess.run( [ sys.executable,
Credential Harvesting
No credential harvesting patterns detected
Typosquatting
No typosquatting candidates detected
Registered Email Domain
Email domain looks legitimate: gmail.com>
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository yeongseon/azure-functions-openapi-python appears legitimate
Maintainer History
score 4.0
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" 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 azure-functions-openapi
Create a fully functional mini-application that integrates Azure Functions with OpenAPI using the 'azure-functions-openapi' package. Your goal is to develop a simple weather forecast service that allows users to query weather data for specific cities. This application should demonstrate the core functionalities of the 'azure-functions-openapi' package, such as generating OpenAPI specifications from Azure Functions, and handling HTTP requests efficiently.
Steps:
1. Set up your development environment with Python 3.9+ and install necessary packages including 'azure-functions', 'azure-functions-openapi', and any other dependencies you might need.
2. Define a set of Azure Functions within your project. Each function should represent an endpoint for interacting with the weather forecast service (e.g., GET /forecast/{city}, POST /update-forecast).
3. Utilize the 'azure-functions-openapi' package to generate an OpenAPI specification for your Azure Functions. Ensure that the generated spec accurately reflects the endpoints, their methods, and required parameters.
4. Implement a mock weather data source (in-memory or file-based) to simulate fetching weather forecasts. This will serve as the backend for your Azure Functions.
5. Test your application thoroughly by making HTTP requests to each defined endpoint and verifying that the responses match the expected behavior.
6. Document your code and the steps taken to integrate 'azure-functions-openapi'. Include any challenges faced and solutions implemented.
Suggested Features:
- Implement rate limiting on API calls to prevent abuse.
- Add support for caching weather data to reduce load on the mock data source.
- Integrate error handling mechanisms to gracefully manage invalid requests or data issues.
- Provide a user-friendly interface or documentation based on the generated OpenAPI spec for easy consumption of the weather forecast service.
This project aims to showcase the power and flexibility of integrating Azure Functions with OpenAPI using 'azure-functions-openapi', while also delivering practical value through a real-world application.
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