AI Analysis
Final verdict: SAFE
The package shows minimal risk indicators with no network calls, shell executions, obfuscation, or credential harvesting. However, the incomplete author information and potential inactivity of the maintainer slightly elevate the metadata risk.
- No network calls detected
- Incomplete maintainer's author information
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require internet connectivity.
- Shell: No shell execution patterns detected, indicating the package does not execute system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
- Credentials: No credential harvesting patterns detected, indicating low risk of malicious activity.
- Metadata: The maintainer's author information is incomplete, and the author seems to be new or inactive.
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 shortAuthor "" 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-foundry
Create a Python-based mini-application that leverages the 'agent-framework-foundry' package to interact with Microsoft Foundry and manage agents within the Microsoft Agent Framework ecosystem. This application will serve as a bridge between local development environments and the Microsoft Foundry platform, enabling developers to easily deploy, monitor, and manage their agents without needing direct access to Foundry's internal systems. The application should include the following core functionalities: 1. Authentication: Allow users to authenticate their Foundry credentials securely. Use OAuth2.0 for authentication, ensuring that all interactions with Foundry are authorized. 2. Agent Management: Provide commands to create, update, delete, and retrieve information about agents registered within the Foundry environment. Users should be able to specify agent details such as name, description, and associated workflows. 3. Workflow Integration: Enable users to integrate custom workflows with their agents. This involves uploading workflow definitions, linking them to specific agents, and managing these associations. 4. Monitoring & Logging: Implement real-time monitoring capabilities to track agent status and performance metrics. Additionally, log all interactions and events related to agents for auditing purposes. 5. Notifications: Set up a notification system to alert users about critical events or changes in agent status, such as when an agent fails or completes a task successfully. 6. CLI Interface: Develop a command-line interface (CLI) for interacting with the application. The CLI should support all core functionalities mentioned above and provide clear, concise output. 7. Documentation: Generate comprehensive documentation for the application, including setup instructions, API reference, and examples of how to use each feature. To achieve these objectives, you'll need to utilize the 'agent-framework-foundry' package effectively. Specifically, you'll leverage its functions for authenticating against Foundry, managing agent lifecycle operations, integrating workflows, and retrieving agent-related data. Ensure that your implementation adheres to best practices in software engineering, focusing on modularity, maintainability, and security.