a2a-adapter

v0.2.12 safe
4.0
Medium Risk

Convert any AI agent into an A2A Protocol server in 3 lines

πŸ€– AI Analysis

Final verdict: SAFE

The package a2a-adapter v0.2.12 is assessed as safe with a moderate metadata risk due to incomplete author information. However, no other significant risks were identified.

  • Network connections are established, but this is common and requires further review for unauthorized endpoints.
  • Metadata risk is elevated due to incomplete author details.
Per-check LLM notes
  • Network: The package establishes network connections, which is common but should be reviewed to ensure it's not communicating with unauthorized endpoints.
  • Shell: No shell execution patterns detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
  • Metadata: The author information is incomplete, which may indicate lack of transparency or a newly created account.

πŸ”¬ Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

  • d: self._client = httpx.AsyncClient(timeout=self.timeout) return self._client async
  • ut self._client = httpx.AsyncClient(timeout=timeout) return self._client async def
  • ): self._client = httpx.AsyncClient(timeout=self.timeout) return self._client def _
  • self._http_client = httpx.AsyncClient(timeout=30.0) return self._http_client async de
  • ore() push_httpx_client = httpx.AsyncClient() push_sender = BasePushNotificationSender( http
  • (adapter) async with httpx.AsyncClient( transport=httpx.ASGITransport(app=app),
βœ“ Code Obfuscation

No obfuscation patterns detected

βœ“ Shell / Subprocess Execution

No shell execution patterns detected

βœ“ Credential Harvesting

No credential harvesting patterns detected

βœ“ Typosquatting

No typosquatting candidates detected

βœ“ Registered Email Domain

Email domain looks legitimate: hybro.ai>

βœ“ Suspicious Page Links

All external links appear legitimate

βœ“ Git Repository History

Repository hybroai/a2a-adapter appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
βœ“ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

πŸ’‘ AI App Starter Prompt

Use this prompt to build a project with a2a-adapter
Create a mini-application called 'AI Agent Connector' that leverages the 'a2a-adapter' package to seamlessly convert various AI agents into servers following the A2A Protocol. Your task is to design a user-friendly interface where users can input details of their AI agents and see them converted into A2A Protocol servers in just three lines of code. Here’s how your application should work:

1. **User Input:** Allow users to specify the type of AI agent they want to convert (e.g., a chatbot, a recommendation system). Users should also provide necessary configuration details such as API endpoints, authentication tokens, etc.
2. **Conversion Process:** Utilize the 'a2a-adapter' package to automatically generate the required code snippets to convert the specified AI agent into an A2A Protocol server. This process should be transparent to the user, showing step-by-step what transformations are being made.
3. **Server Deployment:** Provide options for users to deploy their newly converted AI agent as a server locally or on cloud services like AWS, Google Cloud, or Azure. The application should guide users through the deployment process, including setting up necessary security measures.
4. **Monitoring & Management:** Offer tools within the application to monitor the performance of deployed servers, including real-time logs, usage statistics, and alerts for potential issues.
5. **Documentation & Support:** Ensure that comprehensive documentation is provided within the application for each step of the process, from setup to deployment. Include FAQs, troubleshooting guides, and links to further resources.

Suggested Features:
- Integration with popular AI platforms (e.g., Dialogflow, TensorFlow)
- Customizable templates for different types of AI agents
- Automated testing before deployment to ensure compatibility with the A2A Protocol
- User feedback system to improve future versions of the application