azdo-daily

v1.7.3 suspicious
4.0
Medium Risk

Azure DevOps daily task automation with AI task breakdown

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has a moderate risk score due to its network activities with external APIs and the lack of detailed maintainer information.

  • Moderate network risk due to external API calls
  • Incomplete maintainer metadata
Per-check LLM notes
  • Network: The presence of network calls to external APIs suggests potential unauthorized data transmission.
  • Shell: No shell execution patterns detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity related to code obfuscation.
  • Credentials: No credential harvesting patterns detected, suggesting that the package does not engage in secret or credential theft.
  • Metadata: The maintainer's author name is missing and they appear to be new or inactive, which raises some suspicion but not enough to conclusively determine malice.

📦 Package Quality Overall: Medium (5.0/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • 2 test file(s) detected (e.g. test_azdo_hours.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (7391 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

  • 24 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 5.0

Limited contributor diversity

  • 1 unique contributor(s) across 100 commits in MrShakila/Azdo-Daily
  • Single author but highly active (100 commits)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

  • story into tasks.""" r = requests.post( "https://api.anthropic.com/v1/messages", he
  • session with PAT.""" s = requests.Session() s.auth = ("", cfg["pat"]) return s def wit_base(
✓ Code Obfuscation

No obfuscation patterns detected

✓ 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: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository MrShakila/Azdo-Daily 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 azdo-daily 
Create a Python-based mini-application called 'DailyDevOpsHelper' that leverages the 'azdo-daily' package to automate daily tasks in Azure DevOps projects. This application should be designed to streamline the workflow of developers and project managers by providing an easy-to-use interface for managing tasks, tracking progress, and integrating AI-driven task breakdowns.

Step 1: Set up the project environment. Ensure you have Python installed and create a virtual environment for your project. Install the 'azdo-daily' package along with any other necessary dependencies.

Step 2: Design the main functionalities of the application. These include:
- Authenticating users with their Azure DevOps credentials
- Fetching daily tasks assigned to the user from Azure DevOps
- Breaking down complex tasks into simpler sub-tasks using AI capabilities provided by 'azdo-daily'
- Allowing users to update task statuses directly within the application
- Providing analytics on task completion rates and time spent on tasks

Step 3: Implement the authentication mechanism. Use OAuth 2.0 for secure authentication and ensure that user data is handled according to privacy standards.

Step 4: Utilize the 'azdo-daily' package to interact with Azure DevOps APIs. This includes fetching task data, breaking down tasks, and updating task statuses.

Step 5: Develop a simple yet effective UI for the application. Consider building a command-line interface (CLI) or a basic web interface using Flask or Django.

Step 6: Test the application thoroughly. Make sure all functionalities work as expected and that the application is robust against common errors.

Step 7: Document the project. Write clear documentation explaining how to set up and use the application, including setup instructions, API usage examples, and troubleshooting tips.

Suggested Features:
- Integration with popular calendar applications for automatic task scheduling
- Customizable notifications for task updates and deadlines
- Support for multiple Azure DevOps organizations and projects
- Export options for task reports and analytics

The goal is to create a tool that not only simplifies daily task management but also enhances productivity through intelligent task breakdown and analysis.

💬 Discussion Feed

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