azure-ai-agentserver-core

v2.0.0b5 safe
3.0
Low Risk

Foundation utilities and host framework for Azure AI Hosted Agents

🤖 AI Analysis

Final verdict: SAFE

Based on the analysis, there are no clear indicators of malicious activity. However, the incomplete author metadata and new/inactive account raise minor concerns.

  • Network risk is moderate due to ASGI and HTTPX usage.
  • Incomplete author metadata and possibly new/inactive account.
Per-check LLM notes
  • Network: The use of ASGI and HTTPX for network calls is consistent with typical web service functionality, but further investigation into the purpose and destinations of these calls is advised.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: The observed pattern is commonly used for extending module search paths and does not inherently indicate malicious activity.
  • Credentials: No patterns indicative of credential harvesting were detected.
  • Metadata: The author's details are incomplete and the account seems new or inactive, which raises some concern but does not conclusively indicate malicious intent.

📦 Package Quality Overall: Medium (6.6/10)

✦ High Test Suite 9.0

Test suite present — 10 test file(s) found

  • Test runner config found: conftest.py
  • 10 test file(s) detected (e.g. conftest.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (5116 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 83 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 35 unique contributor(s) across 100 commits in Azure/azure-sdk-for-python
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

  • ost's ASGI app.""" return httpx.AsyncClient( transport=httpx.ASGITransport(app=agent), b
  • AgentServerHost() return httpx.AsyncClient( transport=httpx.ASGITransport(app=agent), b
⚠ Code Obfuscation score 8.0

Found 4 obfuscation pattern(s)

  • __path__ = __import__("pkgutil").extend_path(__path__, __name__) __path__ = __import__("pkg
  • path__, __name__) __path__ = __import__("pkgutil").extend_path(__path__, __name__) __path__ = __import__("pkg
  • path__, __name__) __path__ = __import__("pkgutil").extend_path(__path__, __name__) # ------------------------
  • _stream, ) """ __path__ = __import__("pkgutil").extend_path(__path__, __name__) from ._base import AgentSe
✓ 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> license-expression: mit

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository Azure/azure-sdk-for-python 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 azure-ai-agentserver-core 
Create a mini-application that leverages the 'azure-ai-agentserver-core' package to manage and interact with Azure AI Hosted Agents. Your application should serve as a simplified agent management console, enabling users to perform basic operations such as listing available agents, starting, stopping, and monitoring the status of these agents. Here’s a detailed breakdown of the requirements:

1. **Setup**: Begin by installing the 'azure-ai-agentserver-core' package and setting up your development environment. Ensure you have access to an Azure account where you can deploy and manage hosted agents.
2. **Authentication**: Implement user authentication to securely connect to Azure services. Use Azure Active Directory for managing user credentials and permissions.
3. **Agent Management**: Develop functionalities to list all hosted agents within a specified subscription, start a new agent if needed, stop an existing agent, and retrieve the current status of any agent.
4. **Monitoring**: Include real-time monitoring capabilities to track the health and performance metrics of hosted agents. Display these metrics in a user-friendly format.
5. **User Interface**: Design a simple command-line interface (CLI) for interacting with the application. Additionally, consider integrating a basic web interface using Flask or Django for a more interactive experience.
6. **Documentation**: Provide comprehensive documentation on how to install and use the application, including sample commands and expected outputs.

This project will not only showcase the power of 'azure-ai-agentserver-core' but also offer practical insights into managing Azure resources programmatically.

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