azure-mgmt-computelimit

v1.1.0 safe
3.0
Low Risk

Microsoft Azure Computelimit Management Client Library for Python

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risk indicators with no network or shell execution risks. While there is some obfuscation through encoding/decoding, this is typical for handling binary data. The main concern is the lack of maintainer metadata.

  • Obfuscation through base64 encoding
  • Missing maintainer metadata
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package is purely for local resource management.
  • Shell: No shell execution patterns detected, indicating no direct system command execution.
  • Obfuscation: The base64 encoding and decoding functions suggest some level of obfuscation, but they are common practices for handling binary data in libraries.
  • Credentials: No clear evidence of credential harvesting patterns detected.
  • Metadata: The maintainer's author name is missing and they appear to be new or inactive, which raises some concern.

📦 Package Quality Overall: Medium (6.6/10)

✦ High Test Suite 9.0

Test suite present — 3 test file(s) found

  • Test runner config found: conftest.py
  • 3 test file(s) detected (e.g. conftest.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (2730 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 195 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)

  • return attr return bytes(base64.b64decode(attr)) def _deserialize_bytes_base64(attr): if isinsta
  • ce("_", "/") return bytes(base64.b64decode(encoded)) def _deserialize_duration(attr): if isinstan
  • __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-computelimit 
Develop a cloud resource management tool named 'AzureComputeLimitMonitor' using the 'azure-mgmt-computelimit' Python package. This tool will help Azure users monitor their compute limits across different regions and subscriptions, ensuring they stay within their allocated resources. The application should have the following core functionalities:

1. **Subscription and Region Selection**: Allow users to select one or multiple Azure subscriptions and regions where they want to check their compute limits.
2. **Compute Limit Retrieval**: Utilize the 'azure-mgmt-computelimit' package to fetch current compute limits for various services (e.g., Virtual Machines, Managed Disks) in the selected regions and subscriptions.
3. **Usage Tracking**: Track the actual usage of compute resources over time to compare against the set limits. This could involve integrating with another Azure SDK (such as 'azure-mgmt-compute') to retrieve usage data.
4. **Alert System**: Implement an alert system that notifies users via email or SMS if any of their compute limits are approaching critical levels.
5. **Dashboard Interface**: Provide a simple dashboard interface where users can visualize their current compute limits, usage, and alerts in real-time.
6. **Configuration Management**: Enable users to configure alert thresholds and notification preferences through a configuration file or settings menu.

To utilize the 'azure-mgmt-computelimit' package effectively, you'll need to authenticate your application with Azure Active Directory (AAD) to access the necessary APIs. Additionally, consider implementing rate limiting and error handling to ensure smooth operation even under high load or API failures. This project aims to streamline Azure resource management, providing users with a powerful yet easy-to-use tool for staying compliant with their compute limits.

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