agent-framework-gemini

v1.0.0a260521 suspicious
4.0
Medium Risk

Google Gemini integration for Microsoft Agent Framework.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risks in direct threats like network calls, shell execution, and obfuscation. However, the metadata risk is elevated due to the maintainer's author name being missing or too short, and the package appears new or inactive.

  • Metadata risk due to incomplete maintainer information
  • New or inactive package
Per-check LLM notes
  • Network: No network calls detected, which is typical unless the package requires external services.
  • Shell: No shell execution patterns detected, indicating no immediate signs of malicious shell command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer's author name is missing or very short and seems to be new or inactive, raising some suspicion.

🔬 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

Email domain looks legitimate: microsoft.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository microsoft/agent-framework 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)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with agent-framework-gemini 
Create a Python-based desktop application named 'GeminiAgentBot' that integrates Google Gemini's capabilities with Microsoft's Agent Framework through the 'agent-framework-gemini' package. This application will serve as a personal assistant, capable of performing various tasks such as scheduling appointments, sending emails, and providing weather updates, all powered by Gemini's advanced AI capabilities. Here’s a step-by-step guide on how to build this application:

1. **Setup Environment**: Begin by setting up your development environment with Python installed. Ensure you have the 'agent-framework-gemini' package installed via pip. Also, include necessary libraries like 'requests' for HTTP requests and 'schedule' for task scheduling.

2. **Project Structure**: Organize your project into modules such as 'agents', 'tasks', 'config', and 'main'. Each module will handle different aspects of the application.

3. **Configuration Module**: In the 'config' module, store API keys, endpoints, and other settings required to interact with Google Gemini and Microsoft Agent Framework. Use environment variables to keep sensitive information secure.

4. **Agents Module**: Utilize the 'agent-framework-gemini' package within the 'agents' module to define agents that can communicate with Google Gemini. These agents should be able to perform actions based on user commands or scheduled events.

5. **Tasks Module**: Develop functions within the 'tasks' module that leverage these agents to accomplish specific tasks. For example, create a function to schedule appointments using a calendar API, another to send emails, and one to fetch weather updates from a weather service API.

6. **Main Module**: In the 'main' module, implement a command-line interface (CLI) or a simple GUI using a library like 'tkinter' where users can interact with the application. The interface should allow users to input commands or set schedules for tasks.

7. **Integration & Testing**: Integrate all components and test thoroughly to ensure smooth operation. Pay special attention to error handling and user feedback mechanisms.

8. **Deployment**: Once tested, consider deploying the application as a standalone executable using tools like PyInstaller. Make sure to include comprehensive documentation explaining setup, usage, and customization options.

Suggested Features:
- A natural language processing interface for more intuitive interaction.
- Support for voice commands using a speech-to-text library.
- Integration with more services like news feeds, social media updates, etc.
- Customizable alerts and notifications based on user preferences.
- Enhanced security measures for data privacy.