azure-mgmt-powerbidedicated

v1.0.1 suspicious
4.0
Medium Risk

Microsoft Azure Powerbidedicated Management Client Library for Python

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risks in terms of network and shell activities, but incomplete author metadata and potential obfuscation techniques raise concerns about its authenticity and purpose.

  • Incomplete author information
  • Potential obfuscation techniques
Per-check LLM notes
  • Network: No network calls detected, which is unusual but not necessarily indicative of malicious activity without additional context.
  • Shell: No shell execution patterns detected, indicating the package does not execute external commands.
  • Obfuscation: The observed pattern is a common method to extend module search path and is generally not indicative of malicious activity.
  • Credentials: No patterns indicative of credential harvesting were detected.
  • Metadata: The author information is incomplete and the account seems new or inactive, which raises some suspicion but does not strongly indicate malice.

📦 Package Quality Overall: Medium (6.4/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • 1 test file(s) detected (e.g. disable_test_cli_mgmt_powerbidedicated.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (5891 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Type checker (mypy / pyright / pytype) referenced in project
  • 89 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-powerbidedicated 
Develop a Python-based utility named 'PowerBIResourceManager' that leverages the 'azure-mgmt-powerbidedicated' package to manage Power BI Dedicated resources within your Azure environment. This utility will allow users to perform various operations such as provisioning new dedicated capacity instances, managing existing ones, and retrieving detailed information about their current state.

### Key Features:
1. **Provisioning**: Users should be able to create a new dedicated capacity instance for Power BI, specifying parameters like name, region, SKU tier, and any additional configurations required.
2. **Management Operations**: Implement functionalities to start, stop, and delete dedicated capacity instances. Also include the ability to update certain properties of an existing instance.
3. **Information Retrieval**: Provide methods to fetch detailed information about a specific dedicated capacity instance, including its status, pricing tier, and other relevant details.
4. **List All Instances**: Allow the user to list all dedicated capacity instances within their subscription, displaying essential attributes for quick overview.
5. **Usage Statistics**: Integrate with Azure Monitor to gather and display usage statistics for each dedicated capacity instance over a specified period.

### Utilization of 'azure-mgmt-powerbidedicated':
- Use the 'azure-mgmt-powerbidedicated' package to authenticate with Azure and manage Power BI Dedicated resources through its client library functions. Specifically, utilize classes and methods provided by the package to interact with the Azure API endpoints responsible for handling dedicated capacity instances.

### Implementation Steps:
1. **Setup Environment**: Ensure you have Python installed along with the necessary packages (azure-mgmt-powerbidedicated, azure-identity).
2. **Authentication**: Implement Azure authentication using the DefaultAzureCredential class from azure-identity.
3. **Create Client**: Instantiate the PowerBIDedicatedClient object with the authenticated credentials.
4. **Implement Provisioning Functionality**: Write functions to create new dedicated capacity instances based on user input.
5. **Add Management Functions**: Develop functions to perform management actions (start, stop, delete) on existing instances.
6. **Fetch Information**: Create functions to retrieve and display detailed information about dedicated capacity instances.
7. **List Instances**: Implement functionality to list all dedicated capacity instances within a subscription.
8. **Integrate Usage Statistics**: Fetch and present usage statistics for each dedicated capacity instance.
9. **User Interface**: Optionally, develop a simple command-line interface or web-based UI for easier interaction with the utility.
10. **Testing & Documentation**: Thoroughly test the utility and document its usage, including examples and explanations of key features.

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