azure-mgmt-changeanalysis

v1.0.2 suspicious
4.0
Medium Risk

Microsoft Azure Changeanalysis Management Client Library for Python

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has been deprecated and will not be maintained, raising concerns about its future reliability and security. Incomplete author information and an inactive account add to the suspicion.

  • Deprecated package with no future maintenance planned
  • Incomplete author information and potentially inactive account
Per-check LLM notes
  • Network: No network calls detected, which is unusual but not necessarily indicative of malicious activity for a management package.
  • Shell: No shell execution patterns detected, aligning with expectations for a legitimate package.
  • Obfuscation: The observed pattern is likely used for legitimate purposes such as extending module search path, rather than malicious obfuscation.
  • Credentials: No patterns indicative of credential harvesting were detected.
  • Metadata: The author's information is incomplete and the account seems new or inactive, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Low (4.6/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Brief PyPI description (473 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

  • 39 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

No suspicious network call patterns found

⚠ Code Obfuscation score 4.0

Found 2 obfuscation pattern(s)

  • __path__ = __import__("pkgutil").extend_path(__path__, __name__) # type: ignore __path__ =
  • ) # type: ignore __path__ = __import__("pkgutil").extend_path(__path__, __name__) # type: ignore # coding=u
✓ 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-mgmt-changeanalysis 
Develop a Python-based application that leverages the 'azure-mgmt-changeanalysis' package to monitor and analyze changes within a Microsoft Azure environment. This application will serve as a change management tool for IT administrators, allowing them to track modifications made to their Azure resources over time. Here’s a step-by-step guide on how to approach building this application:

1. **Setup and Configuration**: Begin by setting up your development environment with Python installed. Ensure you have access to an Azure subscription and the necessary permissions to manage resources. Install the 'azure-mgmt-changeanalysis' package using pip.

2. **Authentication**: Implement Azure Active Directory (AAD) authentication to securely connect to the Azure Change Analysis service. Use the Azure CLI or Azure SDK to handle authentication tokens.

3. **Resource Monitoring**: Design a feature that allows users to select specific Azure resources (e.g., virtual machines, storage accounts) they want to monitor for changes. The application should periodically check these resources for any modifications.

4. **Change Detection**: Utilize the 'azure-mgmt-changeanalysis' package to detect changes in monitored resources. Your application should be able to identify when a resource has been modified and record details such as the type of change (create, update, delete), timestamp, and who made the change.

5. **Notification System**: Implement a notification system that alerts users via email or SMS whenever a significant change occurs in their monitored resources. Consider integrating with services like Twilio for SMS notifications or SMTP for emails.

6. **Reporting**: Develop a reporting module that generates detailed reports summarizing all changes detected over a specified period. These reports should be easy to read and include visual aids like graphs or charts to highlight trends.

7. **User Interface**: Although not mandatory, consider adding a simple web interface using Flask or Django to make it easier for users to interact with the application. This could include features like setting up resource monitoring, viewing change logs, and accessing reports.

8. **Testing and Documentation**: Thoroughly test your application under various scenarios to ensure reliability and accuracy. Document your code and provide clear instructions for setup, usage, and troubleshooting.

💬 Discussion Feed

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