🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has low risk for common attack vectors like network calls or shell execution but shows some red flags in metadata, particularly with non-HTTPS links and an author with limited package history.

Suspicious non-HTTPS links in metadata
Author with minimal package history

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external services.
Shell: No shell execution detected, indicating no direct system command execution from the package.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
Credentials: No credential harvesting patterns detected, indicating secure handling of secrets.
Metadata: Suspicious non-HTTPS links and an author with minimal package history suggest 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: columbia.edu>

⚠ Suspicious Page Links score 6.0

Found 3 suspicious link(s) on the package page

Non-HTTPS external link: http://www.rtatmocn.com/disort/
Non-HTTPS external link: http://opg.optica.org/ao/abstract.cfm?URI=ao-27-12-2502.
Non-HTTPS external link: http://www.rtatmocn.com/disort/.

✓ Git Repository History

Repository LDEO-CREW/Pythonic-DISORT appears legitimate

⚠ 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 PythonicDISORT

Create a mini-application called 'AtmosphericRadiationVisualizer' that utilizes the PythonicDISORT package to solve and visualize the radiative transfer equation in a one-dimensional atmosphere. This application will allow users to input parameters such as atmospheric layers, scattering properties, and solar zenith angle to simulate and visualize the radiative flux distribution within the atmosphere. The application should include the following features:

1. User Interface: A simple GUI built using Tkinter or a web-based interface using Flask, allowing users to input necessary parameters.
2. Parameter Input: Users should be able to specify the number of layers in the atmosphere, each layer's optical depth, albedo, and single-scattering albedo. Additionally, they can set the solar zenith angle and other relevant boundary conditions.
3. Simulation Engine: Utilize PythonicDISORT to calculate the radiative fluxes within each layer based on the user inputs. Ensure the application handles multi-layer scenarios accurately.
4. Visualization: Display the results graphically, showing the radiative flux at different altitudes and angles. Include options to save these visualizations as image files.
5. Documentation: Provide clear documentation explaining how to install PythonicDISORT, run the application, and interpret the results.
6. Customization: Allow advanced users to customize the solver settings within PythonicDISORT, such as the number of ordinates used in the discrete ordinate method.
7. Example Scenarios: Preload the application with example scenarios, such as clear sky, cloudy sky, and aerosol-laden atmospheres, to demonstrate its capabilities.