AI Analysis
Final verdict: SAFE
The package shows no signs of malicious activity such as network calls, shell executions, or obfuscation. However, the metadata risk score is slightly elevated due to the maintainer's new or inactive account and missing PyPI classifiers.
- No network calls detected
- Maintainer has a new or inactive PyPI account
- Missing PyPI classifiers
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require internet access.
- Shell: No shell execution detected, reducing the risk of executing arbitrary commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer has a new or inactive account and lacks PyPI classifiers, suggesting low effort or metadata quality issues.
Heuristic Checks
Outbound Network Calls
No suspicious network call patterns found
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: riverbankcomputing.com
Suspicious Page Links
All external links appear legitimate
Git Repository History
No GitHub repository linked
No GitHub repository link found
Maintainer History
score 4.0
2 maintainer concern(s) found
Author "Riverbank Computing Limited" appears to have only 1 package on PyPI (new or inactive account)Package has no PyPI classifiers (low effort / metadata quality)
Known CVE Vulnerabilities
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Use this prompt to build a project with PyQt6-NetworkAuth-Qt6
Create a desktop application using Python and the PyQt6-NetworkAuth-Qt6 package that allows users to securely log into their accounts via OAuth2.0. The application should provide a user-friendly interface where users can input their credentials and select from a list of supported services such as Google, Facebook, Twitter, and GitHub. Upon clicking 'Login', the app should initiate the OAuth2.0 flow, redirecting the user to the respective service's login page. Once authenticated, the user will be redirected back to the app with an access token, which the app should then use to fetch basic profile information (e.g., username, email, profile picture) and display it within the application. Key Features: 1. User Interface Design: Implement a clean and intuitive UI with fields for username/password input and a dropdown menu for selecting the service. 2. OAuth2.0 Integration: Utilize the PyQt6-NetworkAuth-Qt6 package to handle network requests and authentication flows securely. 3. Token Management: Store and manage access tokens securely on the client side, ensuring they are not exposed. 4. Profile Information Display: After successful login, display the fetched profile information in a separate section of the app. 5. Error Handling: Provide informative error messages if the login process fails at any stage. How PyQt6-NetworkAuth-Qt6 is Utilized: - Use the NetworkAuth module to handle HTTP requests and responses during the OAuth2.0 flow. - Leverage Qt6's capabilities for creating the GUI and handling user interactions. - Ensure all network communications are secure and adhere to best practices for handling sensitive data.