AI Analysis
Final verdict: SAFE
The package appears to be legitimate and safe based on the analysis. It has minimal risks associated with network, shell, obfuscation, and credential handling.
- Low risk scores across all categories
- No signs of malicious activities
Per-check LLM notes
- Network: The detection of network calls is expected as 'async-firebase' likely interacts with Firebase services.
- Shell: No shell execution patterns detected, indicating no immediate risk from 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, which might indicate a new or less active account.
Package Quality Overall: Medium (7.2/10)
✦ High
Test Suite
9.0
Test suite present — 9 test file(s) found
Test runner config found: conftest.pyTest runner config found: pyproject.toml9 test file(s) detected (e.g. __init__.py)
◈ Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (9223 chars)
◈ Medium
Contributing Guide
7.0
Some contribution signals present
Separate author ("Oleksandr Omyshev") and maintainer ("Healthjoy Developers") listedDevelopment Status classifier >= Beta
◈ Medium
Type Annotations
5.0
Partial type annotation coverage
56 type-annotated function signatures detected in source
✦ High
Multiple Contributors
10.0
Active multi-contributor project
11 unique contributor(s) across 100 commits in healthjoy/async-firebaseActive community — 5 or more distinct contributors
Heuristic Checks
Outbound Network Calls
score 1.5
Found 1 network call pattern(s)
self._http_client = httpx.AsyncClient( timeout=httpx.Timeout(**self._request_t
Code Obfuscation
No obfuscation patterns detected
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: healthjoy.com
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository healthjoy/async-firebase appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Oleksandr Omyshev" 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-firebase
Create a real-time chat application using Python that leverages Firebase Cloud Messaging (FCM) for push notifications. Your application should allow users to sign up, log in, and participate in chat rooms where they can send messages to other participants. When a user sends a message, the app should broadcast this message to all active participants in the chat room via FCM, ensuring that even those who are offline receive the message when they come back online. Additionally, implement a feature that allows users to receive a notification if someone mentions them in a chat message. This project will utilize the 'async-firebase' package to handle the asynchronous communication with Firebase, allowing for smooth and efficient message broadcasting without blocking the main thread of your application. Here are the steps to follow: 1. Set up a Firebase project and obtain necessary credentials. 2. Install the required Python packages including 'async-firebase'. 3. Design a simple UI for user registration and login. 4. Implement backend logic to manage user sessions and chat rooms. 5. Use 'async-firebase' to set up listeners for new messages in a chat room. 6. Integrate FCM to send push notifications to users based on their activity status. 7. Add functionality to mention users and trigger personalized notifications. 8. Test the application thoroughly to ensure reliability and performance.
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