🤖 AI Analysis

Final verdict: SAFE

The package SmartMDAO has a moderate risk score due to potential shell execution risks, but there are no indications of malicious activities. It is recommended to verify its usage context.

Moderate shell risk due to potential for executing arbitrary code.
Low maintenance and metadata quality concerns.

Per-check LLM notes

Network: No network calls were detected, which is normal and poses no immediate risk.
Shell: Detection of shell execution suggests potential for executing arbitrary code, which could be risky if not properly controlled or documented.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows low maintenance and metadata quality, but there are no clear signs of malicious intent.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

xed earlier process = subprocess.run( ["uv", "run", str(script)], capture

✓ 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

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

Author name is missing or very short
Author "" 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 SmartMDAO

Create a mini-application that demonstrates the power of the 'SmartMDAO' package by building a simple Multi-Disciplinary Analysis and Optimization (MDAO) system for designing a basic aircraft wing. Your application should allow users to input various parameters such as wing span, airfoil shape, material type, and desired lift coefficient. Using these inputs, the application will perform an analysis to optimize the wing design for minimal drag while achieving the specified lift coefficient.

Steps to follow:
1. Define the problem domain: Identify key variables affecting wing performance, such as wing span, airfoil geometry, and material properties.
2. Implement the SmartMDAO framework: Integrate SmartMDAO into your project to handle the complex interdependencies between different aspects of wing design.
3. Set up optimization objectives: Define the goal of minimizing drag while maintaining the target lift coefficient.
4. Design the interface: Create a user-friendly interface where users can input their preferences and see the optimized results.
5. Perform simulations: Use the integrated analysis tools provided by SmartMDAO to run simulations based on user inputs.
6. Display results: Present the optimized wing design parameters and visualizations of the simulation outcomes to the user.

Suggested Features:
- Interactive sliders and input fields for adjusting design parameters.
- Real-time feedback showing changes in drag and lift coefficients.
- Visualization of the wing design before and after optimization.
- Export options for saving the optimized design parameters.

How to Utilize SmartMDAO:
- Leverage SmartMDAO's modular structure to connect different components of the wing design process seamlessly.
- Employ SmartMDAO's optimization algorithms to automate the search for the best design configuration.
- Take advantage of SmartMDAO's extensibility to incorporate additional analysis modules if needed.