NaaVRE-catalogue-jupyterlab

v0.2.0 suspicious
4.0
Medium Risk

NaaVRE assets catalogue frontend on Jupyter Lab

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate risk due to obfuscation techniques and the lack of detailed metadata, which could indicate an attempt to conceal its true purpose.

  • Obfuscation risk: 6/10
  • Metadata risk: 3/10
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external resources.
  • Shell: No shell execution patterns detected, indicating no immediate signs of malicious activity.
  • Obfuscation: The use of obfuscation techniques such as encoding setup functions can be indicative of attempts to hide code behavior, potentially malicious.
  • Credentials: No clear patterns for harvesting credentials or secrets were detected.
  • Metadata: The maintainer has a new or inactive account and lacks a proper author name, raising some suspicion but not definitive evidence of malice.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

  • __import__("setuptools").setup() try: from ._version import __version__ except
✓ 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: lifewatch.eu>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository NaaVRE/NaaVRE-catalogue-jupyterlab 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 NaaVRE-catalogue-jupyterlab 
Your task is to create a comprehensive, user-friendly asset management tool within JupyterLab using the 'NaaVRE-catalogue-jupyterlab' package. This tool will allow users to browse, search, and manage various assets such as datasets, models, and documents from a centralized catalogue. Your goal is to design an application that not only integrates seamlessly with JupyterLab but also provides advanced functionalities like filtering, sorting, and exporting asset information.

### Step-by-Step Guide:
1. **Setup Environment**: Begin by setting up your development environment with Python and JupyterLab installed. Ensure you have the 'NaaVRE-catalogue-jupyterlab' package installed and properly configured within your JupyterLab instance.
2. **Asset Catalogue Integration**: Utilize 'NaaVRE-catalogue-jupyterlab' to fetch and display a list of all available assets in the catalogue. Each asset should include details such as name, type, description, and last updated date.
3. **Search Functionality**: Implement a search bar that allows users to find specific assets based on keywords. The search should dynamically update the displayed assets based on user input.
4. **Advanced Filtering & Sorting**: Provide options for users to filter assets by type (e.g., dataset, model) and sort them by relevance, name, or date. These filters should be dynamic and responsive to user selections.
5. **Detailed View**: For each asset, provide a link or button that opens a detailed view containing more information about the asset, including any associated metadata.
6. **Export Functionality**: Allow users to export the list of assets into different formats (CSV, JSON) directly from the application. This feature should be accessible via a menu option or button.
7. **User Interface Enhancements**: Design the UI to be intuitive and user-friendly. Consider adding visual elements like icons for different asset types and ensure the layout is responsive across different screen sizes.
8. **Testing & Documentation**: Thoroughly test your application to ensure all features work correctly and document the setup process and usage instructions clearly.

### Suggested Features:
- Integration with external storage systems for direct access to assets.
- Support for versioning of assets, showing historical changes.
- Customizable views where users can add their own fields or columns.
- Real-time updates to reflect changes made to the catalogue.

By completing this project, you'll not only demonstrate proficiency in working with JupyterLab extensions but also showcase your ability to develop robust and user-centric applications.