🤖 AI Analysis

Final verdict: SAFE

The package is deemed safe with minimal risks observed. It does not engage in network calls, shell executions, or any form of obfuscation that could indicate malicious behavior.

No network calls detected
No shell executions detected

Per-check LLM notes

Network: No network calls detected, which is normal unless the package's functionality requires external API interactions.
Shell: No shell executions detected, indicating the package does not execute system commands, which is typical for most Python packages.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows signs of low maintainer activity and poor metadata quality, but lacks clear indicators of malicious intent.

🔬 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: ajanuary.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

Author name is missing or very short
Author "" 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 afidgen

Create a mini-application named 'HumanReadableIDGenerator' that leverages the 'afidgen' package to generate unique, human-readable IDs for various entities such as users, products, and transactions. The application should be built using Python and should include a command-line interface (CLI) for easy interaction.

Step-by-Step Instructions:
1. Install the 'afidgen' package via pip.
2. Define classes for User, Product, and Transaction within your application, each requiring a unique ID.
3. Implement a function to generate IDs using the 'afidgen' package, ensuring that these IDs are both unique and readable.
4. Develop a CLI where users can input details about a new entity (User, Product, or Transaction) and receive a generated ID back.
5. Add functionality to save all generated IDs along with their corresponding entity details into a local SQLite database for future reference.
6. Include a feature to retrieve an entity's information based on its unique ID from the database.
7. Ensure your application handles errors gracefully, providing clear feedback to the user when necessary.
8. Document your code thoroughly, explaining how each part of the application works and how 'afidgen' is integrated into the process.

Suggested Features:
- A configuration file to customize the ID generation parameters.
- Support for different types of entities beyond just Users, Products, and Transactions.
- An option to export all stored IDs and entity details to a CSV file for backup purposes.
- Implementation of a simple REST API for remote access to the ID generation and retrieval functionalities.

How 'afidgen' is Utilized:
- Use 'afidgen' to create IDs that balance between being concise and readable, which is crucial for human interaction and ease of use.
- Leverage the package's capabilities to ensure that the generated IDs are unique across all entities.
- Incorporate 'afidgen' functions to validate and format IDs before storing them in the database.