AI Analysis
Final verdict: SAFE
The package shows no signs of malicious activity based on the provided analysis notes. The metadata risk score is slightly elevated due to the author having only one package, but this alone does not indicate any malicious intent.
- No network calls detected
- No shell execution patterns found
- No obfuscation or credential harvesting patterns observed
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package's functionality requires external communications.
- Shell: No shell execution patterns detected, indicating no immediate signs of malicious activities.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
- Credentials: No credential harvesting patterns detected, suggesting no risk of secret theft.
- Metadata: The author has only one package, suggesting it may be a new or less active account, but no other red flags are present.
Package Quality Overall: Low (3.8/10)
○ 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://alkahest-cas.github.io/alkahest/Detailed PyPI description (28223 chars)
○ Low
Contributing Guide
4.0
No contributing guide or governance files found
Development Status classifier >= Beta
○ Low
Type Annotations
1.0
No type annotations detected
No type annotations, py.typed marker, or stub files detected
◈ Medium
Multiple Contributors
6.0
Limited contributor diversity
2 unique contributor(s) across 100 commits in alkahest-cas/alkahestTwo distinct contributors found
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
Repository alkahest-cas/alkahest appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Alkahest Contributors" 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 alkahest
Create a mini-application named 'AlgebraSolver' that leverages the Alkahest package to solve complex algebraic equations and provide visual representations of their solutions. This application should allow users to input various types of algebraic equations (linear, quadratic, polynomial, etc.) and receive both numerical solutions and graphical plots of these equations. Here are the key steps and features to implement: 1. **User Interface**: Design a simple yet intuitive UI where users can input their equations. Support for LaTeX-like syntax for equation entry would be ideal. 2. **Equation Parsing**: Utilize Alkahest’s capabilities to parse and interpret the entered equations. Ensure robust error handling for invalid inputs. 3. **Solution Calculation**: Use Alkahest to compute the solutions for the entered equations. Implement functionality to handle different types of equations (linear, quadratic, polynomial, etc.). 4. **Graphical Representation**: Integrate a plotting library like Matplotlib to visually represent the solutions. Provide options to customize the plot (e.g., line color, axis labels). 5. **Solution Display**: Display the solutions numerically and graphically on the UI. Allow users to save the graphs as image files. 6. **Advanced Features**: Optionally, include features such as solving systems of equations, finding roots using numerical methods, and integrating differential equations. 7. **Documentation**: Write comprehensive documentation explaining how to use AlgebraSolver, including examples of valid inputs and expected outputs. Ensure that the application is well-structured, modular, and adheres to good coding practices. Utilize Alkahest’s core functionalities to demonstrate its power and flexibility in handling complex algebraic computations.