aio-azure-clients-toolbox

v1.4.1 suspicious
5.0
Medium Risk

Async Azure Clients Mulligan Python projects

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has low risks in terms of network, shell, obfuscation, and credential handling. However, its low maintenance and engagement indicate potential issues, making it suspicious.

  • Low maintenance and engagement
  • Potential supply-chain attack
Per-check LLM notes
  • Network: Low risk; no network calls detected, but typical Azure client packages may perform API requests.
  • Shell: Very low risk; no shell execution detected and unexpected for a utility package.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of malicious credential theft.
  • Metadata: The package shows low maintenance and engagement signs, raising some suspicion but not strong evidence of malice.

📦 Package Quality Overall: Medium (6.2/10)

✦ High Test Suite 9.0

Test suite present — 7 test file(s) found

  • Test runner config found: pyproject.toml
  • Test runner config found: conftest.py
  • 7 test file(s) detected (e.g. test_azure_blobs.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://mulliganfunding.github.io/aio-azure-clients-toolbox
  • Detailed PyPI description (6121 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

  • 66 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 4 unique contributor(s) across 35 commits in MulliganFunding/aio-azure-clients-toolbox
  • Small but multi-author team (3–4 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: mulliganfunding.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ 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 aio-azure-clients-toolbox 
Create a fully-functional mini-application that leverages the 'aio-azure-clients-toolbox' package to interact with Azure services asynchronously. This application will serve as a versatile tool for managing various Azure resources, such as Azure Blob Storage, Azure Queue Storage, and Azure Table Storage. The app should provide a user-friendly interface for performing common tasks related to these services, ensuring efficient and smooth interaction with Azure from a Python environment.

**Steps to Build the Application:**
1. **Setup Environment**: Install necessary packages including 'aio-azure-clients-toolbox', 'aiohttp', and 'async-timeout'. Ensure you have your Azure credentials (connection strings or access keys) ready.
2. **Design the User Interface**: Create a simple command-line interface (CLI) using Python's built-in modules or a more advanced graphical user interface (GUI) using libraries like PyQt or Tkinter. The UI should allow users to select which Azure service they wish to manage.
3. **Implement Core Functionality**: Utilize 'aio-azure-clients-toolbox' to implement core functionalities such as uploading files to Blob Storage, creating/deleting queues in Queue Storage, and inserting/retrieving entities from Table Storage. Ensure all operations are asynchronous to take full advantage of the package's capabilities.
4. **Add Additional Features**: Consider adding features like automatic error handling, progress bars for file uploads/downloads, and support for multiple Azure accounts.
5. **Testing and Documentation**: Thoroughly test each feature to ensure reliability and efficiency. Document your code and provide a README file explaining how to install, configure, and use the application.

**Suggested Features**:
- Support for multiple Azure accounts
- Real-time progress updates during long-running operations
- Comprehensive error messages for troubleshooting
- GUI options for easier management
- Command-line arguments for automation purposes

By following these steps and utilizing the 'aio-azure-clients-toolbox' package effectively, you'll create a powerful and flexible tool for managing Azure resources asynchronously.

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