azurefunctions-agents-runtime

v0.1.0b3 suspicious
4.0
Medium Risk

A markdown-first programming model for building AI agents on Azure Functions, powered by the Microsoft Agent Framework.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows moderate signs of potential misuse due to its use of shell commands and lack of clear maintainer information. However, there are no definitive indicators of malicious activity.

  • Moderate shell risk due to use of subprocess.run()
  • Lack of maintainer metadata
Per-check LLM notes
  • Network: The use of aiohttp.ClientSession() is common for making HTTP requests and may be legitimate depending on the package's functionality.
  • Shell: Use of subprocess.run() suggests the package may execute shell commands, which could be risky if not properly sanitized or used to run arbitrary code.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows signs of low maintainer effort and lacks a proper author name and repository, which raises some suspicion but does not conclusively indicate malicious intent.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 22 test file(s) found

  • 22 test file(s) detected (e.g. test_app.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (24800 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 431 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • : _http_session = aiohttp.ClientSession() logger.debug( "dynamic_sessions_code_i
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

  • n" "- Shell commands: use subprocess.run(), not '!' syntax.\n" "- Common packages are pre-install
✓ 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

No GitHub repository linked

  • No GitHub repository link found
⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with azurefunctions-agents-runtime 
Create a mini-app that acts as a personal assistant for managing tasks and reminders using the 'azurefunctions-agents-runtime' package. This app should allow users to interact via a simple chat interface where they can add tasks, set reminders, and get updates on their schedule. The goal is to demonstrate the capabilities of the azurefunctions-agents-runtime package by leveraging its markdown-first programming model to build an intelligent agent on Azure Functions.

Steps to create the app:
1. Set up an Azure Function App with the necessary configurations for hosting your agent.
2. Use the azurefunctions-agents-runtime package to define the agent's behavior through markdown files, specifying actions like adding tasks, setting reminders, and fetching schedules.
3. Implement a simple front-end chat interface using HTML/CSS/JavaScript that allows users to input commands and receive responses from the agent.
4. Integrate the chat interface with the Azure Function App so that user inputs are processed by the agent and appropriate responses are returned.
5. Test the app thoroughly to ensure that all functionalities work as expected.
6. Deploy the final version of the app to Azure for public access.

Suggested Features:
- Ability to add new tasks with due dates and descriptions.
- Setting reminders for specific times or dates.
- Retrieving a list of upcoming tasks and reminders.
- Updating task statuses (completed, pending).
- Deleting tasks and reminders.
- User authentication for personalized experiences.

How to Utilize 'azurefunctions-agents-runtime':
- Define the agent's logic in markdown files, detailing how it should respond to different user commands and queries.
- Utilize the package's capabilities to run these markdown-defined workflows on Azure Functions, enabling serverless execution of the agent's tasks.
- Take advantage of the integration with the Microsoft Agent Framework to enhance the intelligence and functionality of the agent.

💬 Discussion Feed

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