🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits low activity and lacks necessary metadata, raising concerns about its legitimacy and development effort.

Low activity and lack of classifiers
Description is unclear or non-existent

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires network functionality.
Shell: No shell execution patterns detected, indicating no immediate signs of malicious shell command execution.
Metadata: Low activity and lack of classifiers suggest low effort, but no clear malicious indicators.

🔬 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

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Author "Adel Miski" 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 aems

Create a Python-based educational tool named 'AEMS Explorer' that leverages the 'aems' package to provide interactive learning experiences for numerical methods commonly used in engineering and mathematics. This tool should allow users to input specific parameters and initial conditions for various numerical problems, and then visualize the solutions using graphical representations. Here’s a step-by-step guide on how to develop this application:

1. **Setup Project**: Initialize a new Python project and install the 'aems' package.
2. **Design User Interface**: Develop a simple but user-friendly interface where users can select different numerical methods (e.g., Euler's method, Runge-Kutta methods, etc.) and input their parameters.
3. **Implement Numerical Methods**: Utilize the 'aems' package to implement the selected numerical methods. Ensure that the application supports at least three different methods.
4. **Graphical Visualization**: Integrate a plotting library like Matplotlib or Plotly to display the results of the numerical methods visually. Users should be able to see both the solution curves and error analysis if applicable.
5. **Educational Resources**: Include brief descriptions and examples of each numerical method within the application to help users understand the underlying concepts better.
6. **Interactive Examples**: Provide pre-defined examples for users to explore without needing to input any parameters manually.
7. **Save & Share Results**: Allow users to save their computational results and graphs as image files or share them via email or social media.

By following these steps, you will create a comprehensive educational tool that not only solves numerical problems but also enhances understanding through visualization and interactive learning.