AI Analysis
Final verdict: SAFE
The package appears to be safe based on the provided analysis notes, showing no signs of network, shell, or obfuscation risks. However, the metadata risk score suggests low maintainer activity and poor metadata quality.
- No network, shell, or obfuscation risks detected
- Metadata risk due to low maintainer activity and poor metadata quality
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires external services.
- Shell: No shell execution detected, indicating no immediate risk from command injection.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows signs of low maintainer activity and poor metadata quality, but lacks clear indicators of malicious intent.
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
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-registry
Develop a decentralized identity management system using the Python package 'agentity-registry'. This system will serve as a user-friendly interface for managing Decentralized Identifiers (DIDs), enabling users to perform operations such as DID registration, revocation, and verification. Additionally, the system should allow for real-time monitoring of DID status changes through WebSocket connections. **Step-by-Step Project Outline:** 1. **Setup and Initialization**: Begin by installing the required packages, including 'agentity-registry'. Set up your development environment with Python and necessary libraries. 2. **User Interface Design**: Create a simple yet effective UI using Flask or Django for handling HTTP requests related to DID operations. 3. **DID Management Functions**: Implement functionalities to register new DIDs, retrieve information about existing DIDs, and revoke DIDs when necessary. Use 'agentity-registry' APIs for these operations. 4. **WebSocket Integration**: Integrate WebSocket capabilities to provide real-time updates on DID status changes. Users should be able to subscribe to specific DIDs and receive notifications via WebSocket. 5. **Audit and Logging**: Ensure all operations are logged securely and auditable. Implement a feature where users can view logs of their actions and system administrators can monitor overall system activity. 6. **Security Measures**: Incorporate security best practices throughout the application, ensuring data integrity and confidentiality. 7. **Testing and Deployment**: Thoroughly test the application for functionality, performance, and security before deploying it on a server. **Suggested Features**: - User authentication and authorization for secure access to DID management functions. - Detailed error messages and validation checks to prevent misuse of the system. - An administrative panel for managing users and overseeing system health. - Comprehensive documentation for both end-users and developers. Incorporate the 'agentity-registry' package by utilizing its REST API endpoints for DID operations and WebSocket services for real-time communication. This will enable seamless integration of decentralized identity management into your application.