🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has low risks in terms of network, shell, obfuscation, and credential usage but exhibits signs of potential low activity and lack of maintainer details, which raises concerns about its reliability and origin.

Low activity and lack of maintainer details
Potential lack of community support

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires network interactions for its functionality.
Shell: No shell execution patterns detected, indicating no direct system command execution from the package.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows signs of potential low activity and lack of maintainer details which could indicate it might be suspicious.

🔬 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

Email domain looks legitimate: gmail.com>

✓ 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 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 abracatabra

Create a mini-application named 'TabbedPlotter' which allows users to visualize multiple plots in separate tabs within a single window interface. This application should leverage the 'abracatabra' package, which extends matplotlib with tabbed plotting capabilities using the Qt backend. The goal is to provide an intuitive user interface where users can easily switch between different plots without cluttering the workspace.

### Features:
1. **User Interface**: Develop a clean and user-friendly GUI that allows users to interact with the plots.
2. **Dynamic Plotting**: Users should be able to dynamically add new plots to different tabs, each tab representing a unique dataset or type of plot.
3. **Plot Customization**: Allow users to customize their plots with options such as changing colors, adding titles, legends, and labels.
4. **Save and Export**: Implement functionality to save the current state of the application (all tabs and their plots) and export individual plots as image files.
5. **Interactive Elements**: Include interactive elements like zooming, panning, and tooltips for data points.
6. **Data Input**: Provide options for users to input their own datasets either through file uploads or direct input fields.
7. **Help and Documentation**: Include a help section that guides users on how to use the application effectively.

### Utilizing 'abracatabra':
- Use 'abracatabra' to manage the tabbed layout and switching between tabs seamlessly.
- Leverage its integration with matplotlib to ensure high-quality rendering of plots.
- Explore advanced features of 'abracatabra' for enhanced interactivity and customization.

### Steps to Build the Application:
1. **Setup Environment**: Install necessary packages including 'abracatabra', matplotlib, and any other required libraries.
2. **Design UI**: Sketch out the basic structure of your application interface.
3. **Implement Core Functionality**: Start coding the core functionalities focusing on tab management and dynamic plotting.
4. **Enhance with Additional Features**: Gradually add features such as plot customization, saving/exporting, and interactive elements.
5. **Testing**: Test thoroughly to ensure all features work as expected.
6. **Documentation**: Write documentation to guide users on how to use the application.
7. **Deployment**: Prepare the application for deployment ensuring it runs smoothly on different systems.

This project will not only serve as a practical tool for data visualization but also as a showcase for the capabilities of 'abracatabra'.