AI Analysis
Final verdict: SAFE
The package has low risks across all categories except metadata, where it shows some concern due to low maintainer activity and poor metadata quality. However, there's no concrete evidence of malicious intent.
- Low risk in network, shell, obfuscation, and credential aspects.
- Metadata quality and maintainer activity are suboptimal.
Per-check LLM notes
- Network: The use of httpx for making HTTP requests is common and does not inherently indicate malicious activity; however, it should be verified if the package requires legitimate network calls.
- Shell: No shell execution patterns were detected, which is normal and indicates no immediate risk from this aspect.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
- Credentials: No credential harvesting patterns detected, suggesting safe handling of sensitive information.
- Metadata: The package shows low maintainer activity and poor metadata quality, which could indicate potential risks but does not conclusively point to malice.
Heuristic Checks
Outbound Network Calls
score 1.5
Found 1 network call pattern(s)
httpx async with httpx.AsyncClient() as client: resp = await client.get(f"{self
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
No author email provided
Suspicious Page Links
All external links appear legitimate
Git Repository History
score 2.5
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forks
Maintainer History
score 6.0
3 maintainer concern(s) found
Author name is missing or very shortAuthor "" 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 agentity-middleware-python
Create a fully functional mini-application using the 'agentity-middleware-python' package that integrates with FastAPI to streamline API requests handling. Your task is to develop a simple yet robust microservice that manages user authentication and authorization processes. This application will serve as a foundational tool for securing other services in a larger ecosystem. Here’s a detailed breakdown of your project requirements and features: 1. **Project Overview**: Design an application named 'AuthMicroservice' that acts as a middleware layer between client applications and backend services. It should handle user registration, login, and session management. 2. **Core Features**: - **User Registration**: Implement a feature where users can register themselves with unique usernames and passwords. Store hashed passwords securely. - **Login Mechanism**: Enable users to log into the system via username/password combinations. Upon successful login, generate secure JWT tokens. - **Session Management**: Use JWT tokens to manage user sessions. Ensure token validation on each request and implement token refresh functionality. - **Role-Based Access Control (RBAC)**: Define different roles (e.g., admin, user) and restrict access to certain endpoints based on these roles. 3. **Utilizing 'agentity-middleware-python'**: - Integrate 'agentity-middleware-python' to enhance the security and efficiency of your API endpoints. Use it to validate incoming requests, manage authentication headers, and enforce role-based permissions. - Explore its capabilities to customize error responses and improve logging mechanisms. 4. **Additional Enhancements**: - Add a feature to reset forgotten passwords via email verification. - Implement rate limiting to prevent brute force attacks. - Consider adding support for multi-factor authentication (MFA). 5. **Development Steps**: - Set up a virtual environment and install necessary dependencies including 'fastapi', 'uvicorn', 'pydantic', and 'agentity-middleware-python'. - Design models for User and Token classes. - Create API routes for user registration, login, logout, and token refresh. - Implement middleware functions to handle authentication and authorization. - Test your application thoroughly using tools like Postman or curl. 6. **Documentation**: - Provide clear documentation on how to set up the application, including database configuration, environment variables setup, and API endpoint descriptions. - Include instructions on how to integrate this microservice with other services in a production environment. This project not only enhances your understanding of user authentication and authorization but also showcases your ability to leverage third-party libraries to build secure and scalable applications.