AI Analysis
Final verdict: SUSPICIOUS
The package shows low risk in terms of network, shell, and obfuscation activities, with no detected credential risks. However, the incomplete metadata and inactive author status raise concerns about potential supply-chain risks.
- Incomplete and inactive author information
- Potential supply-chain attack risk due to author status
Per-check LLM notes
- Network: No network calls detected, which is normal for packages not requiring external API interactions.
- Shell: No shell execution patterns detected, indicating no direct system command invocations.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The author's information is incomplete and they appear to be inactive, raising some suspicion but not conclusive evidence of malice.
Package Quality Overall: Low (3.0/10)
◈ Medium
Test Suite
6.0
Partial test coverage signals detected
1 test file(s) detected (e.g. test_source.py)
○ Low
Documentation
1.0
No documentation detected
No documentation URL, doc files, or meaningful description found
○ Low
Contributing Guide
2.0
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium
Type Annotations
5.0
Partial type annotation coverage
18 type-annotated function signatures detected in source
○ Low
Multiple Contributors
1.0
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
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: gmail.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 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 authsources-keycloak
Create a user authentication mini-application using the 'authsources-keycloak' Python package. This application will serve as a simple web-based login system where users can authenticate themselves using their Keycloak credentials. Here’s a step-by-step guide on how to build this application: 1. **Setup Environment**: Ensure you have Python installed on your machine along with the necessary libraries like Flask for web development. 2. **Install Dependencies**: Use pip to install 'authsources-keycloak', Flask, and other required packages. 3. **Configure Keycloak**: Set up a Keycloak server instance and create a realm and client for your application. Configure the client settings to allow public access and note down the client ID and secret. 4. **Application Structure**: Design the basic structure of your Flask application including routes for home page, login, and logout. 5. **Authentication Mechanism**: Integrate 'authsources-keycloak' to handle authentication requests. Use the package to connect to your Keycloak server and validate user credentials. 6. **User Sessions**: Implement session management to keep track of logged-in users and invalidate sessions upon logout. 7. **Security Measures**: Add security measures such as CSRF protection and ensure all communication is over HTTPS. 8. **Testing**: Thoroughly test the application to ensure it correctly handles authentication, authorization, and secure communication. Suggested Features: - User registration redirection to Keycloak for new users - Profile viewing for authenticated users - Secure password reset functionality linked to Keycloak - Multi-factor authentication support through Keycloak This project will demonstrate how to leverage 'authsources-keycloak' for secure and scalable user authentication in a Flask application.
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