azure-mgmt-databoxedge

v2.0.0 suspicious
4.0
Medium Risk

Microsoft Azure Data Box Edge Management Client Library for Python

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows some signs of potential obfuscation or code injection through the use of 'eval', despite being otherwise clean in terms of network, shell execution, and credential risks.

  • Unusual use of 'eval' with 'nosec' and 'pylint disable' comments
  • Single-package author might be a new or less active account
Per-check LLM notes
  • Network: No network calls detected, which is unusual but not necessarily indicative of malicious activity for a management package that may require network access to Azure services.
  • Shell: No shell execution patterns detected, which aligns with expectations for a non-executable Python package.
  • Obfuscation: The use of 'eval' with 'nosec' and 'pylint disable' comments is suspicious and could indicate obfuscation or code injection risks.
  • Credentials: No clear patterns for harvesting credentials or secrets were detected.
  • Metadata: The author has only one package, which might indicate a new or less active account, but no other suspicious activities were detected.

📦 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 (10210 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
  • 204 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 8.0

Found 4 obfuscation pattern(s)

  • _unicode(data) return eval(data_type)(data) # nosec # pylint: disable=eval-used @
  • _unicode(attr) return eval(data_type)(attr) # nosec # pylint: disable=eval-used @
  • __path__ = __import__("pkgutil").extend_path(__path__, __name__) __path__ = __import__("pkg
  • path__, __name__) __path__ = __import__("pkgutil").extend_path(__path__, __name__) # coding=utf-8 # ---------
✓ 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-databoxedge 
Create a Python-based monitoring tool for Azure Data Box Edge devices using the 'azure-mgmt-databoxedge' package. This tool will allow administrators to manage their Data Box Edge devices remotely, providing real-time status updates and alerts. Here’s a detailed breakdown of the project requirements and steps:

1. **Setup**: Begin by installing the necessary Python packages including 'azure-mgmt-databoxedge', 'azure-identity', and any other dependencies required for authentication and management operations.
2. **Authentication**: Implement a secure way to authenticate users via Azure Active Directory (AAD). Use the 'azure-identity' package to handle token acquisition and authentication processes.
3. **Device Management**: Develop functionalities to list all registered Data Box Edge devices within a specified subscription, retrieve detailed information about each device, and perform basic management tasks such as starting, stopping, and restarting the devices.
4. **Monitoring**: Integrate real-time monitoring capabilities that display key performance indicators (KPIs) like CPU usage, memory usage, storage utilization, network throughput, and device health status. These metrics should be refreshed periodically to ensure up-to-date information.
5. **Alert System**: Implement an alert system that notifies administrators via email or SMS when critical thresholds are breached. For instance, if a device's storage utilization exceeds 90%, an alert should be triggered.
6. **User Interface**: Design a simple yet effective command-line interface (CLI) for interacting with the tool. Consider adding options for advanced users to customize settings and configurations.
7. **Documentation**: Provide comprehensive documentation detailing how to set up and use the tool, including sample commands and troubleshooting tips.

The 'azure-mgmt-databoxedge' package will be central to this project, enabling you to interact with Azure Data Box Edge services programmatically. Utilize its methods for device management, data retrieval, and configuration settings to build out the core functionalities of your monitoring tool.

💬 Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!