AI Analysis
The package shows minimal risk indicators across all categories. It appears to be a legitimate async client library with expected network calls and no signs of malicious activity.
- Low network risk due to expected functionality
- No evidence of obfuscation, shell execution, or credential harvesting
Per-check LLM notes
- Network: The detection of network calls is expected for an async client library, as it likely communicates with a service to manage sessions and JSON data.
- Shell: No shell execution patterns were detected, which is normal and expected.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer has a single package and lacks PyPI classifiers, indicating low effort or newness, but no clear signs of malicious intent.
Package Quality Overall: Low (3.6/10)
Test suite present β 12 test file(s) found
12 test file(s) detected (e.g. test_default_api.py)
No documentation detected
No documentation URL, doc files, or meaningful description found
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
16 type-annotated function signatures detected in source
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked β contributor count unavailable
Heuristic Checks
Found 1 network call pattern(s)
self.pool_manager = aiohttp.ClientSession( connector=aiohttp.TCPConnector(limit=self.m
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: openapitools.org
All external links appear legitimate
No GitHub repository linked
No GitHub repository link found
2 maintainer concern(s) found
Author "OpenAPI Generator community" appears to have only 1 package on PyPI (new or inactive account)Package has no PyPI classifiers (low effort / metadata quality)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a fully functional mini-application using the Python package 'aind-session-json-service-async-client'. This application will serve as a session management tool for a simple web-based chat application. Your task is to implement a system where users can log in, maintain their sessions, and interact with each other in real-time. Hereβs a detailed breakdown of what your application should accomplish: 1. **User Registration**: Allow new users to register with unique usernames and passwords. 2. **Login System**: Implement a login system that authenticates users based on their credentials and manages sessions. 3. **Real-Time Chat**: Enable logged-in users to send messages to each other in real-time. 4. **Session Management**: Use 'aind-session-json-service-async-client' to manage user sessions asynchronously. This includes storing session data, validating sessions, and handling session timeouts. 5. **Security Measures**: Ensure that all sensitive information is handled securely, including hashing passwords before storage and using secure methods for session management. 6. **UI/UX Design**: While not the primary focus, consider basic UI/UX principles to make the application user-friendly. ### Utilizing 'aind-session-json-service-async-client' - **Session Storage**: Use the package to store and retrieve session data for authenticated users. - **Session Validation**: Implement logic to validate sessions upon user actions such as sending a message or logging out. - **Timeout Handling**: Set up automatic session expiration after a period of inactivity. ### Additional Features (Optional) - **Message History**: Store recent messages for each user session so they can view past conversations. - **Online Status**: Display whether a user is currently active or offline. - **User Profiles**: Allow users to customize their profiles with additional information like profile pictures or bio details. Your goal is to create a robust, secure, and efficient application that leverages the asynchronous capabilities of 'aind-session-json-service-async-client' to enhance performance and scalability.
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