🤖 AI Analysis

Final verdict: SAFE

The package shows low risk across all categories except for metadata, where it has non-HTTPS links and lacks author details, suggesting potential unreliability but no clear signs of malicious activity or supply-chain attack.

Low risk in network, shell, and obfuscation categories
Metadata issues with non-HTTPS links and missing 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 no direct system command execution.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
Metadata: The package has non-HTTPS links and lacks author details, indicating potential unreliability but not necessarily malicious intent.

📦 Package Quality Overall: Low (4.6/10)

○ Low Test Suite 1.0

No test suite detected

No test files or test-runner configuration detected

◈ Medium Documentation 7.0

Some documentation present

Documentation URL: "documentation" -> https://anuga.readthedocs.io
Detailed PyPI description (6324 chars)

○ Low Contributing Guide 2.0

No contributing guide or governance files found

No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found

◈ Medium Type Annotations 5.0

Partial type annotation coverage

Type checker (mypy / pyright / pytype) referenced in project

✦ High Multiple Contributors 8.0

Active multi-contributor project

3 unique contributor(s) across 100 commits in anuga-community/anuga_core
Small but multi-author team (3–4 contributors)

🔬 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: anu.edu.au>

⚠ Suspicious Page Links score 4.0

Found 2 suspicious link(s) on the package page

Non-HTTPS external link: http://anuga.anu.edu.au
Non-HTTPS external link: http://anuga.anu.edu.au:

✓ Git Repository History

Repository anuga-community/anuga_core 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 anuga

Develop a mini-application using the 'anuga' Python package to simulate flood scenarios in a selected coastal city. Your application should allow users to input various parameters such as rainfall intensity, duration, and coastal elevation data. The goal is to visualize the potential flood extent and depth over time under different conditions.

Key Features:
1. User-friendly interface for inputting city-specific data (e.g., topography, bathymetry).
2. Interactive sliders or input fields to adjust rainfall intensity and duration.
3. Visualization of flood extent and water depth at different times during the simulation.
4. Save and export simulation results as images or videos.
5. Comparative analysis tool allowing users to run multiple simulations side-by-side to understand the impact of varying parameters.

How to Utilize 'anuga':
- Use 'anuga' for setting up the computational domain based on user-provided topographic and bathymetric data.
- Implement 'anuga' flow solver to model the propagation of floodwaters across the domain.
- Leverage 'anuga' visualization tools to display the simulation results dynamically.

The application will serve as an educational tool for urban planners, environmental scientists, and policymakers to better understand and prepare for flood risks.