ado-search

v1.12.2 suspicious
4.0
Medium Risk

Sync and search Azure DevOps work items and wiki pages for AI agents

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low individual risks but the maintainer's new or inactive account and lack of community engagement raise concerns about its legitimacy and maintenance.

  • Metadata risk due to a new or inactive maintainer account and low community engagement.
  • No significant individual risks detected.
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires internet access to function properly.
  • Shell: No shell execution patterns detected, indicating the package does not execute external commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has a new or inactive account, and the repository lacks community engagement.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ 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

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Samuel Hurley" 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 ado-search
Develop a mini-application named 'DevOpsInsight' using Python that integrates the 'ado-search' package to sync and search Azure DevOps work items and wiki pages. This application will serve as a powerful tool for DevOps teams to enhance their productivity by providing quick access to relevant information.

### Key Features:
1. **Work Item Synchronization**: Automatically fetches and syncs all work items from specified Azure DevOps projects into a local database or cache. This includes basic details like title, description, state, and type of each work item.
2. **Wiki Page Indexing**: Crawls through Azure DevOps wiki pages, indexing content for efficient searching. The indexed data should include page titles, contents, and any associated tags or metadata.
3. **Unified Search Interface**: Provides a user-friendly interface where users can search across both work items and wiki pages simultaneously. Results should be ranked based on relevance and displayed with concise summaries.
4. **Customizable Filters**: Allows users to apply filters such as project name, work item type, status, or specific keywords when searching.
5. **Integration with AI Agents**: Incorporates AI capabilities to provide intelligent recommendations based on the search queries. For example, suggesting related articles or work items based on user behavior.
6. **Security and Privacy**: Ensures that only authorized users have access to the synced data by implementing authentication mechanisms.

### Steps to Implement:
1. **Setup Environment**: Install necessary Python packages including 'ado-search'. Configure Azure DevOps credentials securely.
2. **Data Fetching**: Use 'ado-search' to fetch work items and wiki pages from Azure DevOps. Store this data locally in a structured format.
3. **Indexing Mechanism**: Develop an indexing system that processes fetched data, preparing it for fast querying.
4. **Search Engine Development**: Create a robust search engine capable of handling complex queries and returning accurate results.
5. **UI/UX Design**: Design a clean, intuitive user interface that allows seamless interaction with the search functionality.
6. **Testing & Deployment**: Thoroughly test the application under various scenarios to ensure reliability and performance. Deploy the application in a secure environment accessible to team members.
7. **Documentation & Support**: Provide comprehensive documentation and support resources for easy adoption and usage.

### Utilizing 'ado-search':
- Leverage 'ado-search' for its ability to efficiently sync and search through Azure DevOps resources.
- Customize the package's functionalities to fit the specific needs of your application, such as filtering or sorting results.
- Explore additional features provided by 'ado-search' to enrich the application's capabilities further.

💬 Discussion Feed

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