🤖 AI Analysis

Final verdict: SAFE

The package aesthetica v1.1.2 appears safe with no network calls, shell executions, obfuscations, or credential risks detected. While there is some concern about metadata and potential use of shell commands, these do not strongly indicate malicious intent.

No network calls detected.
No obfuscation or credential harvesting.

Per-check LLM notes

Network: No network calls detected, which is normal and not indicative of malicious activity.
Shell: Shell execution may be used to gather system information, but without context on the package's purpose, it could potentially be a red flag for data collection or other actions not intended by the user.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The maintainer has only one package and lacks PyPI classifiers, suggesting low effort or inexperience.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 4.0

Found 2 shell execution pattern(s)

command result = subprocess.run(command, capture_output=True, text=True) # Prin
try: displays_text = subprocess.check_output( ['system_profiler', 'SPDisplaysDataType'],

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

✓ 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 "Florian Raths" 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 aesthetica

Create a Python-based mini-app that allows users to generate unique, generative plotter art designs. The app should provide an interactive interface where users can select from different styles, colors, and patterns. Utilize the 'aesthetica' package to handle the generation of the artwork based on user inputs. Here are the steps and features you should include:

1. **User Interface**: Develop a simple yet appealing GUI using a library like Tkinter or PyQt. This interface will allow users to input their preferences.
2. **Style Selection**: Offer at least three distinct styles such as Abstract, Geometric, and Organic. Users should be able to choose one of these styles.
3. **Color Palette**: Provide options for users to pick a color palette from predefined sets or let them customize their own.
4. **Pattern Customization**: Allow users to adjust parameters related to the pattern, such as density, complexity, and symmetry.
5. **Preview Feature**: Implement a preview window within the GUI that updates in real-time as users change settings.
6. **Export Functionality**: Once satisfied, users should have the option to export their design as a vector file (SVG format) or a high-resolution image (PNG).
7. **Integration with Aesthetica**: Use the 'aesthetica' package to process the user inputs and generate the artwork. Ensure that the package is properly installed via pip before running the app.
8. **Documentation**: Include comments in your code explaining how each part of the app works, especially how 'aesthetica' functions are called and customized.
9. **Testing**: Test the application thoroughly to ensure all features work as expected and that the generated art looks as intended.

This project aims to showcase the capabilities of the 'aesthetica' package while providing a fun and engaging experience for users interested in generative art.