🤖 AI Analysis

Final verdict: SAFE

The package abstract3d v0.1.0 is assessed as safe with a low risk score. The absence of network calls, shell executions, obfuscation, and credential risks significantly reduces immediate threats.

No network calls or shell executions detected.
Low metadata risk due to lack of detailed author information.

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external services.
Shell: No shell execution detected, indicating the package does not execute system commands.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package is new and lacks detailed author information, which could indicate potential risk.

🔬 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: abstractcore.ai>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository lpalbou/AbstractFramework appears legitimate

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

Only one version has ever been released — brand new package
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 abstract3d

Create a fully-functional mini-application called 'Abstract3D Viewer' that leverages the Python package 'abstract3d' to showcase AI-driven 3D visualization capabilities within the AbstractFramework ecosystem. This application should allow users to upload their own 3D models (in common formats like .obj, .stl, or .fbx), and then use the AI capabilities provided by 'abstract3d' to perform various operations on these models. Here are the steps and features your application should include:

1. **Setup and Installation**: Begin by setting up a Python environment with the necessary dependencies, including 'abstract3d'. Ensure that the application has a user-friendly interface, either through a command-line interface (CLI) or a graphical user interface (GUI).
2. **Model Upload**: Implement functionality that allows users to upload their 3D models from their local machine. Ensure that the application supports multiple file formats commonly used for 3D models.
3. **AI Processing**: Utilize 'abstract3d' to process the uploaded models. This could include operations such as model simplification, texture generation, or even more advanced tasks like automatic segmentation or object recognition within the model.
4. **Visualization**: Provide a feature to visualize the processed models. This could be done using a web-based viewer integrated into the application or through a standalone viewer application that uses 'abstract3d' for rendering.
5. **Export Options**: Allow users to export the processed models back into common 3D file formats, giving them the option to save the modified version of their original model.
6. **Documentation and User Guide**: Develop comprehensive documentation and a user guide for the application, detailing how to install it, use its features, and troubleshoot any issues that might arise.
7. **Testing and Feedback**: Include a testing phase where you validate the application’s performance with different types of 3D models. Gather feedback from early users to improve the application's usability and functionality.

Throughout the development process, focus on integrating 'abstract3d' effectively to ensure that the application showcases the package's full potential for handling 3D data with AI.