AI Analysis
Final verdict: SAFE
The package shows no signs of malicious activity with minimal risk factors identified.
- No network calls detected
- No shell execution patterns
- No obfuscation or credential harvesting attempts
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires network interactions for its functionality.
- Shell: No shell execution patterns detected, indicating the package does not execute external commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
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
Repository microsoft/agent-governance-toolkit appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Microsoft Corporation" 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 a2a_agentmesh
Create a mini-application called 'SecureAgentConnector' that leverages the 'a2a_agentmesh' package to facilitate secure, trust-verified communication between agents following the A2A protocol. This application will serve as a bridge to connect different agents, ensuring that all communications are encrypted and verified through a trust model. Here’s a detailed breakdown of what your SecureAgentConnector should achieve: 1. **Setup and Configuration**: Start by setting up a basic environment for your application. Ensure you have the 'a2a_agentmesh' package installed. Configure your application to accept two types of agents - senders and receivers. 2. **Trust Verification Model**: Implement a trust verification mechanism that allows agents to verify each other's identities before establishing a connection. This could involve exchanging digital certificates or using a predefined trust network. 3. **Communication Channels**: Utilize 'a2a_agentmesh' to establish encrypted channels between agents. Each channel should be unique and identifiable by the sender and receiver pair. 4. **Message Passing**: Develop a feature that allows agents to send and receive messages over these secure channels. Messages should be encrypted and decrypted using the 'a2a_agentmesh' package. 5. **Error Handling and Logging**: Include robust error handling and logging mechanisms to track any issues that arise during the communication process. This will help in debugging and maintaining the application. 6. **User Interface (Optional)**: For a more interactive experience, consider developing a simple UI where users can input sender and receiver details, and see real-time status updates on message passing. 7. **Testing**: Finally, thoroughly test your application to ensure that all aspects of the communication process work as expected. Test different scenarios including successful connections, failed verifications, and message transmission failures. The 'a2a_agentmesh' package is crucial in this project as it provides the necessary tools for establishing secure, trust-verified connections between agents. It simplifies the process of implementing encryption, decryption, and trust verification, allowing developers to focus on building the application logic.