🤖 AI Analysis

Final verdict: SAFE

The package appears to be safe with no detected obfuscation, shell execution, or credential risks. However, it has a moderate metadata and network risk due to the author's limited activity and the package's network calls.

moderate metadata risk
network calls detected

Per-check LLM notes

Network: The use of urllib.request.urlopen suggests the package makes network calls, which could be for legitimate purposes like fetching remote resources.
Shell: No shell execution patterns detected.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The author has only one package and lacks PyPI classifiers, indicating low effort or newness.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

try: with urllib.request.urlopen(url, timeout=10) as response: file_t

✓ 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

Repository davidlab20/TFG appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Author "David Díaz" appears to have only 1 package on PyPI (new or inactive account)
Package has no PyPI classifiers (low effort / metadata quality)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with aframexr

Develop a fully-functional mini-application called 'VR Data Explorer' using the Python package 'aframexr'. This application will allow users to explore and interact with datasets in a virtual reality environment, making it easier to visualize complex data structures and relationships. The app should include the following features:

1. **Data Import**: Users should be able to import various types of datasets (CSV, JSON, etc.) into the VR environment.
2. **Visualization Options**: Provide different visualization methods such as scatter plots, bar charts, and 3D graphs. Each method should be customizable based on user preferences.
3. **Interactive Exploration**: Enable users to interact with the visualizations directly within VR (e.g., zoom, rotate, filter data).
4. **Customizable Themes**: Allow users to choose from predefined themes or create their own color schemes and backgrounds.
5. **Export Functionality**: Users should be able to export their VR experience as a static scene or a video.
6. **User Interface**: Implement a simple UI in VR to manage dataset imports, visualization options, and theme selections.

The 'aframexr' package will be utilized extensively for rendering the data visualizations in VR. It will handle the creation and manipulation of A-Frame components necessary for displaying the data in a visually appealing and interactive manner. Additionally, 'aframexr' will facilitate the integration of VR controls and interactions within the application.