azure-mgmt-datashare

v1.0.1 suspicious
4.0
Medium Risk

Microsoft Azure Datashare Management Client Library for Python

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits low risks in terms of network, shell execution, and credential handling. However, the metadata and obfuscation risks indicate potential issues that warrant further investigation.

  • Metadata risk due to incomplete author information and a potentially inactive account
  • Observed obfuscation patterns, though likely benign, could be indicative of non-standard practices
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require internet access.
  • Shell: No shell execution patterns detected, indicating no direct system command execution from the package.
  • Obfuscation: The observed pattern is likely a standard practice for extending module search paths and not indicative of malicious activity.
  • Credentials: No suspicious patterns related to credential harvesting were detected.
  • Metadata: The package shows some red flags such as an author with missing details and a new/inactive account, but there are no clear signs of typosquatting or other malicious activities.

📦 Package Quality Overall: Medium (5.4/10)

○ 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 (12396 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
  • 239 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-datashare 
Create a mini-application named 'DataShareExplorer' using Python and the 'azure-mgmt-datashare' library. This application will serve as a command-line interface (CLI) tool for managing data shares within Azure. The goal is to provide users with a simple yet powerful way to create, manage, and delete data shares, as well as to list and manage shared datasets within these data shares.

### Core Features:
1. **Authentication:** Implement authentication using Azure credentials stored in environment variables or a configuration file. Ensure that the application securely handles these credentials.
2. **Data Share Management:** Allow users to create, list, and delete data shares. Each operation should include appropriate validation checks and error handling.
3. **Shared Dataset Management:** Provide functionality to list all shared datasets within a specified data share. Additionally, enable users to create and delete shared datasets.
4. **Logging:** Integrate logging to track operations performed by the application. Log levels should include debug, info, warning, and error.
5. **Help and Usage Information:** Implement help and usage information for each command to assist new users in understanding how to use the CLI effectively.

### Additional Suggested Features:
- **Configuration File Support:** Allow users to configure default settings such as subscription ID, tenant ID, client ID, and client secret via a configuration file.
- **Interactive Mode:** Offer an interactive mode where users can perform actions without needing to specify every parameter manually.
- **Progress Indicators:** Display progress indicators for long-running operations like dataset creation or deletion.
- **Error Handling Enhancements:** Improve error messages to provide more context about failures and suggest possible solutions.

### Utilization of 'azure-mgmt-datashare':
- Use the 'azure-mgmt-datashare' library to interact with Azure's Data Share service. This includes creating clients, performing CRUD operations on data shares and shared datasets, and handling responses from the service.
- Leverage the library's asynchronous capabilities to handle operations that may take longer, ensuring the CLI remains responsive during execution.

### Deliverables:
- A fully functional Python CLI tool named 'DataShareExplorer'.
- Comprehensive documentation detailing how to install and use the application.
- Example configurations and scripts demonstrating various use cases.
- Unit tests covering all major functionalities of the application.

This project will not only enhance your skills in working with Azure services but also provide a valuable tool for anyone managing data shares in Azure.

💬 Discussion Feed

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