AI Analysis
The package presents moderate risk due to its network and metadata characteristics, though it does not exhibit high-risk behaviors such as shell execution or credential harvesting.
- moderate network risk
- high metadata risk
Per-check LLM notes
- Network: Network calls to external URLs are present and could potentially be used for legitimate purposes like API interactions, but may also indicate unauthorized data exchange.
- Shell: No shell execution patterns were detected.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows several red flags including a missing repository and an author with minimal information, indicating potential risk.
Package Quality Overall: Low (2.8/10)
No test suite detected
No test files or test-runner configuration detected
Some documentation present
Detailed PyPI description (8479 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
4 type-annotated function signatures (partial)
Could not retrieve contributor data from GitHub
GitHub API error: 404
Heuristic Checks
Found 2 network call pattern(s)
": res = requests.get(url, headers=headers, timeout=5) else:e: res = requests.post(url, headers=headers, json=payload, timeout=5)
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: authnull.com>
All external links appear legitimate
Repository not found (deleted or private)
Repository not found (deleted or private)
3 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Your task is to create a simple yet powerful web application using Flask, which integrates the 'authsec-crewai' package to manage secure AI delegation tokens for users. This application will serve as a bridge between human users and AI services, ensuring that all interactions are authenticated and authorized through secure token management. ### Core Functionality: 1. **User Registration & Login**: Users must be able to register and log in securely. Upon successful login, the application should use 'authsec-crewai' to retrieve a secure AI delegation token. 2. **Token Management**: Once logged in, users should have access to a dashboard where they can view their current AI delegation token and request new ones if needed. The application should handle token expiration and renewal seamlessly. 3. **Secure Token Storage**: Ensure that tokens are stored securely on the server-side and never exposed directly to the user interface. 4. **Role-Based Access Control (RBAC)**: Implement basic RBAC so that different types of users (e.g., admin, regular user) have varying levels of access to token management features. 5. **Logging & Monitoring**: Maintain logs of token requests and usage for auditing purposes. ### Suggested Features: - **Two-Factor Authentication (2FA)**: Add an extra layer of security during login. - **Token Usage Tracking**: Allow admins to see how many times a token has been used. - **Grace Period for Token Expiration**: Provide a grace period before a token expires to allow ongoing tasks to complete. - **API Integration**: Enable users to integrate their tokens into third-party applications via an API. - **User Feedback System**: Implement a system where users can report issues or suggest improvements related to token usage. ### How to Utilize 'authsec-crewai': - **Authentication**: Use 'authsec-crewai' to authenticate users and generate secure tokens upon successful login. - **Token Retrieval**: Integrate 'authsec-crewai' methods to fetch and manage tokens for each user session. - **Security Enhancements**: Leverage 'authsec-crewai' features to enhance the security of token storage and transmission. - **Audit Logs**: Use 'authsec-crewai' logging capabilities to keep track of token-related activities. This project aims to demonstrate the practical application of secure token management in real-world scenarios, emphasizing both functionality and security.
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