azure-mgmt-dataprotection

v2.0.1 safe
3.0
Low Risk

Microsoft Azure Dataprotection Management Client Library for Python

🤖 AI Analysis

Final verdict: SAFE

The package shows low risk indicators across all categories except metadata, where there is some concern about the maintainer's profile. However, these concerns alone do not indicate malicious activity.

  • Low network and shell execution risks.
  • Base64 decoding observed but deemed legitimate.
  • No signs of credential harvesting.
Per-check LLM notes
  • Network: No network calls detected, which is normal for a package that does not require real-time interaction with Azure services during installation.
  • Shell: No shell execution patterns detected, indicating the package does not execute external commands that could pose a risk.
  • Obfuscation: The observed patterns likely represent legitimate base64 decoding operations for deserialization rather than obfuscation.
  • Credentials: No suspicious patterns indicating credential harvesting were detected.
  • Metadata: The maintainer has an incomplete profile and seems to be new or inactive, raising some concerns but not definitive evidence of malicious intent.

📦 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 (13622 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

  • 82 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 10.0

Found 6 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
  • _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-dataprotection 
Create a Python-based mini-application named 'AzureBackupManager' that leverages the 'azure-mgmt-dataprotection' package to manage backup policies and recovery points for Azure resources. This application will serve as a user-friendly tool for IT administrators to automate and monitor their data protection strategies.

Step 1: Set Up Your Environment
- Ensure you have Python installed on your machine.
- Install the necessary packages including azure-mgmt-dataprotection, azure-identity, and any other dependencies.

Step 2: Authentication and Connection
- Implement authentication using Azure Active Directory credentials to connect to the Azure service.
- Use the azure-identity library to handle the authentication process seamlessly.

Step 3: Define Core Functions
- Create functions to list all existing backup policies within a specified subscription.
- Develop a function to create new backup policies based on predefined templates or custom configurations.
- Include functionality to modify or delete existing backup policies.

Step 4: Backup and Recovery Operations
- Integrate features to trigger backups according to the defined policies.
- Provide options to restore data from specific recovery points.

Step 5: Monitoring and Alerts
- Implement logging and alerting mechanisms to notify users about policy compliance issues, failed backups, or successful restores.
- Utilize Azure Monitor or similar services to track the health of backup operations.

Suggested Features:
- A graphical user interface (GUI) built with PyQt or Tkinter for ease of use.
- Integration with Azure DevOps for continuous integration and deployment.
- Support for multiple tenants and subscriptions.
- Detailed reporting capabilities showing the status of backups and recovery points over time.

Utilization of 'azure-mgmt-dataprotection':
- Use the package's APIs to interact with Azure Data Protection resources programmatically.
- Leverage the SDK's methods to create, read, update, and delete backup policies.
- Employ the package's functionalities to schedule and manage backup operations.

By completing this project, you'll gain hands-on experience with Azure's data protection services and the powerful capabilities offered by the azure-mgmt-dataprotection package.

💬 Discussion Feed

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