AI Analysis
Final verdict: SUSPICIOUS
The package shows low risk in terms of network, shell execution, and obfuscation but has a high metadata risk due to rapid commits and suspicious maintainer history, which could indicate potential tampering or malicious intent.
- High metadata risk
- Suspicious maintainer history
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require external communication.
- Shell: No shell execution patterns detected, indicating the package likely does not execute system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity related to code obfuscation.
- Credentials: No credential harvesting patterns detected, indicating low risk of malicious activity related to stealing secrets or credentials.
- Metadata: High risk due to recent rapid commits and suspicious maintainer history.
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: All 6 commits happened within 24 hours
All 6 commits happened within 24 hours
Maintainer History
score 4.0
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" 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 NX-5
Create a mini-application named 'NotchVisualizer' that leverages the NX-5 package to visually represent text input as nested squares with binary edge notches. This application should allow users to input any textual content and see it transformed into a unique graphical representation based on its topological structure. Here are the steps and features your application should include: 1. **User Input**: Design a simple UI where users can enter their text. This could be a basic web interface using Flask or a command-line interface. 2. **Text Processing**: Implement a function that processes the input text and prepares it for visualization. This includes tokenization, possibly removing stop words, and converting the text into a format suitable for NX-5. 3. **Visualization Generation**: Utilize the NX-5 package to convert the processed text into nested square representations with binary edge notches. Ensure that the output maintains the topological relationships within the text. 4. **Display Results**: Develop a feature to display these visual representations either as images saved locally or directly rendered in the UI. For web interfaces, consider integrating a library like Matplotlib or Plotly for dynamic visualization. 5. **Interactive Elements**: Add interactive elements such as zooming in/out, rotating the view of the nested squares, and toggling between different types of edge notches to enhance user engagement. 6. **Documentation and Help**: Include comprehensive documentation explaining how the application works, the significance of the binary edge notches, and how users can interpret the visual outputs. Optional Features: - **Export Functionality**: Allow users to export the generated visualizations as image files (PNG, SVG). - **Comparison Tool**: Implement a feature that allows users to input multiple texts and compare their visual representations side-by-side. - **Customization Options**: Provide options for users to customize the appearance of the nested squares, such as changing colors or adding labels. Ensure that the application is well-documented and easy to install, making use of virtual environments and pip for dependency management.