azure-mgmt-storagecache

v3.0.1 safe
4.0
Medium Risk

Microsoft Azure Storagecache Management Client Library for Python

🤖 AI Analysis

Final verdict: SAFE

The package appears to be legitimate with low risks across most categories. The primary concern is the use of eval(), which increases the obfuscation risk but does not conclusively indicate malicious intent.

  • Eval usage suggests potential for code injection.
  • Incomplete author metadata.
Per-check LLM notes
  • Network: No network calls detected, which is normal for a package focused on local management operations.
  • Shell: No shell execution patterns detected, indicating the package does not execute external commands.
  • Obfuscation: The use of eval() for decoding suggests potential for code injection and obfuscation.
  • Credentials: No clear signs of credential harvesting patterns detected.
  • Metadata: The author information is incomplete, suggesting potential unreliability, but there are no other red flags.

📦 Package Quality Overall: Medium (7.0/10)

✦ High Test Suite 9.0

Test suite present — 6 test file(s) found

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

Some documentation present

  • Detailed PyPI description (9530 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
  • 319 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__) # 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-storagecache 
Develop a Python-based monitoring tool for Azure Storage Cache resources. This tool will allow users to manage and monitor their storage cache instances within their Azure environment, providing insights into performance metrics and enabling them to perform common management tasks such as creating, updating, and deleting caches. The application should include the following core functionalities:

1. **Authentication**: Implement Azure Active Directory authentication to securely connect to Azure services.
2. **Resource Management**: Enable users to create, update, delete, and list Azure Storage Cache resources.
3. **Performance Monitoring**: Provide real-time and historical performance data for each cache instance, including read/write operations, latency, and throughput.
4. **Alerts & Notifications**: Allow users to set up alerts based on specific performance thresholds and receive notifications via email or SMS when these thresholds are breached.
5. **Dashboard**: Develop a simple web dashboard using Flask to display all monitored caches and their current status.
6. **Configuration Management**: Offer a feature to configure cache settings like size, location, and caching policies.

The 'azure-mgmt-storagecache' package will be central to implementing the resource management and performance monitoring features. Specifically, you'll use it to interact with Azure's Storage Cache API endpoints, fetching and manipulating cache resources programmatically. Additionally, integrate Azure Monitor APIs to gather performance metrics and implement alerting mechanisms through Azure Event Grid or Service Bus.

💬 Discussion Feed

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