AI Analysis
The package shows no immediate signs of malicious intent such as network calls or shell executions. However, the incomplete maintainer information and missing repository raise concerns about its provenance and maintenance.
- Incomplete maintainer information
- Missing repository
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 activity.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The repository is not found and the maintainer information is incomplete, raising concerns but not conclusive evidence of malice.
Package Quality Overall: Low (2.0/10)
No test suite detected
No test files or test-runner configuration detected
Some documentation present
Detailed PyPI description (3507 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
No type annotations detected
No type annotations, py.typed marker, or stub files detected
Could not retrieve contributor data from GitHub
GitHub API error: 404
Heuristic Checks
No suspicious network call patterns found
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: gmail.com
All external links appear legitimate
Repository not found (deleted or private)
Repository not found (deleted or private)
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Develop a fully-functional mini-app that integrates the 'authbox-menu' Python package to dynamically generate user interfaces based on database tables. This app will serve as a versatile tool for managing various types of data, allowing users to interact directly with the database through a menu-driven interface. Step 1: Set up the Project - Initialize a new Python project. - Install the 'authbox-menu' package along with necessary dependencies such as a database connector (e.g., SQLAlchemy for SQLite). Step 2: Define Database Schema - Create a simple SQLite database with multiple tables (e.g., Users, Products, Orders). - Each table should have at least three columns: ID, Name, and Description. Step 3: Implement Dynamic Menu Generation - Use 'authbox-menu' to automatically generate a main menu from the database schema. - Each menu item should correspond to a specific table in the database. Step 4: Develop CRUD Operations - For each table, implement basic CRUD (Create, Read, Update, Delete) operations through sub-menus. - Ensure that these operations are linked back to the database. Step 5: Enhance User Experience - Add error handling to manage invalid inputs or database errors gracefully. - Introduce a help command to guide users through the available commands. - Implement a logout feature to exit the app cleanly. Suggested Features: - Support for multiple database connections (e.g., MySQL, PostgreSQL). - Ability to customize the generated menus (e.g., adding descriptions, changing order). - Integration with external APIs for additional functionality (e.g., sending notifications). - Logging of user actions for auditing purposes. How 'authbox-menu' is Utilized: - The package simplifies the creation of dynamic menus by abstracting away the complexity of manually defining each menu option. - It reads the structure of your database tables and generates corresponding menu items, which you can then extend with custom logic for performing database operations. - This allows for rapid development and easy maintenance of the application, as changes to the database schema are automatically reflected in the user interface.
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