AI Analysis
Final verdict: SAFE
The package shows minimal risk indicators with no network calls, shell executions, or obfuscation. The metadata risk is slightly elevated due to incomplete author information and a single maintained package, but this alone does not suggest a supply-chain attack.
- Low network, shell, and obfuscation risks
- Metadata risk due to incomplete author details and single maintained package
Per-check LLM notes
- Network: No network calls detected, which is normal for most Python packages unless they require external services.
- Shell: No shell execution patterns detected, indicating the package does not execute system commands which reduces potential risks.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The author information is incomplete and the maintainer has only one package, which may indicate a less experienced or potentially suspicious account.
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
Email domain looks legitimate: gmail.com>
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository python-useful-helpers/advanced-descriptors appears legitimate
Maintainer History
score 4.0
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" 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 advanced-descriptors
Create a Python-based mini-application called 'MagicAttributes' which leverages the 'advanced-descriptors' package to manage complex object attributes in a more sophisticated way than traditional getters and setters. This application should serve as a demonstration of how descriptors can be used to add functionality to class attributes, such as validation, logging, and lazy loading. Step-by-Step Guide: 1. Define a class named `Person` that has several attributes such as `name`, `age`, and `email`. These attributes should be managed using descriptors from the 'advanced-descriptors' package. 2. Implement a descriptor named `ValidatedAttribute` that ensures the values assigned to attributes like `name` and `email` meet certain criteria (e.g., name must not be empty, email must follow a standard format). 3. Develop a descriptor called `LazyLoadedAttribute` for the `age` attribute. This descriptor should only calculate and return the age when it is first accessed, simulating a lazy loading scenario where computation-intensive tasks are deferred until necessary. 4. Integrate a descriptor known as `LoggingAttribute` into the `email` attribute to log every change made to it, providing a history of modifications. 5. Write a simple command-line interface for the `Person` class where users can create instances, modify their attributes, and view logs or calculated values. 6. Ensure your application includes proper error handling and user-friendly messages for invalid inputs or operations. 7. Document your code thoroughly, explaining how each descriptor works and why it was chosen for specific attributes. 8. Test your application by creating multiple `Person` objects, modifying their attributes, and verifying that all descriptors function as intended. Suggested Features: - Allow users to specify custom validation rules for any attribute. - Implement a descriptor that automatically saves changes to a file or database. - Add support for different types of lazy loading strategies (e.g., caching results). - Enhance logging capabilities to include timestamps and user IDs. How 'advanced-descriptors' Package is Utilized: - Use the 'advanced-descriptors' package to define and utilize descriptors within your classes, showcasing its ability to handle complex attribute behaviors. This will demonstrate how descriptors can encapsulate business logic related to attribute management, making your code cleaner and more maintainable.