SceneModels

v0.0.1 suspicious
5.0
Medium Risk

Model tools for SceneAPI

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risks in terms of direct threats like network calls or shell executions, but the metadata suggests it might be newly created with limited activity, which raises suspicion about its authenticity and purpose.

  • Low activity and recent creation of the repository
  • Single contributor and new author
Per-check LLM notes
  • Network: No network calls suggest the package is not attempting to communicate externally.
  • Shell: No shell executions indicate the package does not attempt to run arbitrary commands on the host system.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The repository's recent creation, low activity, single contributor, and new author 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

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 10.0

Git history flags: Repository created very recently: 5 day(s) ago (2026-06-01T05:15:02Z)

  • Repository created very recently: 5 day(s) ago (2026-06-01T05:15:02Z)
  • Repository has zero stars and zero forks
  • Very few commits: 1 total
  • Single contributor with only 1 commit(s) — possibly throwaway account
⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • Author "SceneAPI" 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 SceneModels 
Create a fully-functional mini-app that utilizes the 'SceneModels' Python package to manage and analyze scenes from various sources. This app will serve as a versatile tool for users to visualize, manipulate, and derive insights from scene data. Here’s a detailed plan on how to approach this project:

1. **Project Setup**: Start by setting up your Python environment. Ensure you have the latest version of 'SceneModels' installed using pip.

2. **Application Design**: Design your application to support multiple functionalities such as importing scenes from different formats (JSON, XML), exporting scenes to different formats, and visualizing scenes.

3. **Scene Importing & Exporting**: Implement a feature that allows users to import scenes from supported file formats into the application. Use 'SceneModels' to parse these files efficiently. Additionally, provide an option for users to export their scenes back into various formats for further use or sharing.

4. **Scene Visualization**: Utilize 'SceneModels' to render scenes in a user-friendly interface. This could include 2D or 3D visualization depending on the complexity and detail of the scenes. Consider adding interactive elements like zoom, pan, and rotate capabilities.

5. **Scene Analysis Tools**: Develop tools within the application that allow users to analyze their scenes. This could involve metrics like object count, area coverage, or even more complex analysis based on the specific needs of the scenes being analyzed. Use 'SceneModels' to handle the computational aspects of this analysis.

6. **User Interface**: Design a clean, intuitive UI that makes it easy for users to navigate through their scenes and utilize the features provided by the application. Consider using modern web technologies like React or Vue.js for the frontend, coupled with Flask or Django for the backend.

7. **Testing & Documentation**: Thoroughly test the application to ensure all features work as expected. Document each feature clearly, providing examples and tutorials on how to use the application effectively.

8. **Deployment**: Once testing is complete and documentation is finalized, deploy the application on a cloud platform like AWS or Heroku so that it can be accessed by a wider audience.

This project aims to showcase the power and flexibility of 'SceneModels' while providing a practical tool for users working with scene data.