azure-mgmt-securityinsight

v1.0.0 safe
3.0
Low Risk

Microsoft Azure Security Insight Management Client Library for Python

🤖 AI Analysis

Final verdict: SAFE

The package shows no signs of malicious activity and is from a known entity, Microsoft Corporation. While the low number of packages from this author on PyPI is somewhat unusual, it does not outweigh the other positive indicators.

  • No network calls detected
  • No shell execution patterns
  • No obfuscation or credential harvesting
Per-check LLM notes
  • Network: No network calls detected, which is unusual for a service management package but may be due to lazy loading or external configuration.
  • Shell: No shell execution patterns detected, aligning with the expected behavior for a legitimate package.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author Microsoft Corporation has only one package on PyPI, which could indicate a new or less active account but does not strongly suggest malicious intent.

📦 Package Quality Overall: Low (4.2/10)

○ Low Test Suite 1.0

No test suite detected

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

Some documentation present

  • Detailed PyPI description (12608 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
✦ 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

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 Azure/azure-sdk-for-python appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Microsoft Corporation" 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-securityinsight 
Create a Python-based mini-application that integrates with Microsoft Azure Security Center using the 'azure-mgmt-securityinsight' library. This application will serve as a monitoring tool for security alerts and incidents within an organization's Azure environment. The application should be able to perform the following tasks:

1. Authenticate with Azure using Azure Active Directory credentials.
2. Retrieve and display a list of all active security alerts and incidents for a specified subscription ID.
3. Allow users to filter alerts based on severity levels (Low, Medium, High).
4. Provide options to acknowledge or dismiss alerts through the application interface.
5. Integrate a feature to export alert details into a CSV file for further analysis or reporting purposes.
6. Implement logging functionality to track actions performed on alerts within the application.
7. Ensure the application has a user-friendly command-line interface for easy interaction.

To achieve these functionalities, you'll utilize key components from the 'azure-mgmt-securityinsight' package such as managing security insights, working with alerts, and handling incidents. The application should demonstrate proficiency in handling exceptions, maintaining secure connections, and efficiently processing large amounts of data. Additionally, ensure that your code is well-documented and includes comments explaining each significant step and decision made during implementation.

💬 Discussion Feed

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