🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has a moderate risk score due to potential misuse indicated by suspicious git repository activity and maintainer history, despite showing no direct signs of malicious behavior such as network calls or credential harvesting.

Metadata risk due to suspicious git repository activity and maintainer history.
No network calls, shell executions, or obfuscations detected.

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires internet access for its functionality.
Shell: No shell execution patterns 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, suggesting secure handling of sensitive information.
Metadata: The package shows signs of potential misuse due to suspicious git repository activity and maintainer history.

📦 Package Quality Overall: Low (2.2/10)

○ Low Test Suite 1.0

No test suite detected

No test files or test-runner configuration detected

◈ Medium Documentation 5.0

Some documentation present

Detailed PyPI description (1511 chars)

○ Low Contributing Guide 2.0

No contributing guide or governance files found

No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found

○ Low Type Annotations 1.0

No type annotations detected

No type annotations, py.typed marker, or stub files detected

○ Low Multiple Contributors 2.0

Single-author or unverifiable project

1 unique contributor(s) across 3 commits in youseiushida/akari-sat
Single author with few commits — possibly a personal or throwaway project

🔬 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 score 5.0

Git history flags: Single contributor with only 3 commit(s) — possibly throwaway account

Single contributor with only 3 commit(s) — possibly throwaway account
All 3 commits happened within 24 hours

⚠ 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 akari-sat

Create a Python-based puzzle game app called 'AkariSolver' that leverages the 'akari-sat' library to solve Akari puzzles using SAT solvers. An Akari puzzle, also known as 'Light Up', involves placing light bulbs on a grid so that every white square is illuminated while adhering to specific rules. Your task is to develop a user-friendly application that allows users to input their own Akari puzzles or generate random ones, and then solve them efficiently.

The app should include:
- A clean graphical interface for easy puzzle entry and display of solutions.
- An option to load predefined puzzles from a file or database.
- A feature to automatically generate random puzzles based on user-defined parameters such as size and complexity.
- A solver module that uses the 'akari-sat' package to find solutions to the entered or generated puzzles.
- A visual feedback system that highlights the correct placement of bulbs and indicates unsolvable areas.

In detail, the steps for building this application are:
1. Set up the basic structure of your Python project including necessary imports and initialization.
2. Implement the graphical user interface using a framework like PyQt or Tkinter to allow for easy interaction.
3. Integrate the 'akari-sat' library into your project to handle the logic of solving puzzles.
4. Develop functions for loading, generating, and displaying puzzles within the GUI.
5. Create a solver function that takes a puzzle as input, uses 'akari-sat' to solve it, and returns the solution.
6. Add a visual feedback system that updates the UI to reflect the solved state of the puzzle.
7. Test the application thoroughly with various puzzles to ensure reliability and accuracy.
8. Optimize the performance of the solver and improve the user experience based on feedback.
9. Document your code and provide instructions for other developers to contribute or use the app.