azure-mgmt-durabletask

v1.1.0 safe
4.0
Medium Risk

Microsoft Azure Durabletask Management Client Library for Python

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risks across all categories, with no indications of malicious activities. The metadata risk is slightly elevated due to incomplete author information and possibly inactive account status.

  • No network or shell execution risks detected.
  • Obfuscation patterns are benign.
  • Credentials are handled safely.
Per-check LLM notes
  • Network: No network calls detected, which is normal for a library focused on Azure management tasks that don't require direct internet access.
  • Shell: No shell execution patterns detected, aligning with the expected behavior of a library that does not need to execute system commands.
  • Obfuscation: The detected patterns are likely part of data deserialization and path extension logic rather than malicious obfuscation.
  • Credentials: No suspicious patterns indicating credential harvesting were detected.
  • Metadata: The author's information is incomplete and the account seems new or inactive, raising some concerns but not strong evidence of malice.

📦 Package Quality Overall: Medium (6.6/10)

✦ High Test Suite 9.0

Test suite present — 5 test file(s) found

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

Some documentation present

  • Detailed PyPI description (4069 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

  • 149 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-durabletask 
Develop a fully-functional mini-application using the 'azure-mgmt-durabletask' Python package that orchestrates long-running workflows on Azure. This application will allow users to define and manage durable task functions for various tasks, such as processing large datasets, executing complex business processes, or handling other time-consuming operations.

Step 1: Set up your development environment with Python and install the required packages including 'azure-mgmt-durabletask'.

Step 2: Create an Azure account and set up an Azure Function App service where your durable task functions will run.

Step 3: Design the structure of your application to include:
- A user interface for defining and triggering workflows
- An API endpoint for starting and managing durable task functions
- Backend logic using 'azure-mgmt-durabletask' to interact with Azure Functions

Step 4: Implement the core functionalities:
- Define durable task functions in Azure Functions that perform specific tasks
- Use 'azure-mgmt-durabletask' to start and monitor these functions from your application
- Integrate error handling and logging to track the progress and status of each workflow

Suggested Features:
- Allow users to configure parameters for their workflows before execution
- Provide real-time updates about the status of running workflows
- Support for pausing and resuming workflows
- Integration with Azure Storage for persisting workflow data
- Detailed reporting and analytics on completed workflows

How 'azure-mgmt-durabletask' is utilized:
- To create and manage durable task functions within Azure Functions
- For monitoring and controlling the execution lifecycle of these functions
- To handle the orchestration of multiple tasks and ensure they complete successfully

Your goal is to demonstrate how 'azure-mgmt-durabletask' simplifies the management of complex workflows in a cloud-based environment.

💬 Discussion Feed

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