AI Analysis
Final verdict: SUSPICIOUS
The package has low risks for common threats such as network calls, shell execution, and credential harvesting. However, the maintainer's inactivity and lack of community engagement raise concerns about its legitimacy and maintenance.
- Maintainer seems new or inactive
- Repository lacks community engagement
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires external services.
- Shell: No shell executions detected, indicating the package does not execute commands on the host system.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer seems new or inactive, and the repository lacks community engagement.
Package Quality Overall: Low (3.8/10)
◈ Medium
Test Suite
6.0
Partial test coverage signals detected
Test runner config found: pyproject.toml
◈ Medium
Documentation
5.0
Some documentation present
Brief PyPI description (746 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
◈ Medium
Multiple Contributors
5.0
Limited contributor diversity
1 unique contributor(s) across 37 commits in sudo-pali/Aura_CLISingle author but highly active (37 commits)
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: protonmail.com
Suspicious Page Links
All external links appear legitimate
Git Repository History
score 2.5
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forks
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "pali" 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 aura-farming-cli
Create a Python-based mini-application named 'AuraGuard' that leverages the 'aura-farming-cli' package to monitor and enhance users' aura levels. This application will serve as a fun and interactive tool for individuals interested in maintaining positive energy. Here’s a step-by-step guide on what the application should do and how it utilizes the 'aura-farming-cli' package:
1. **Application Initialization**: Upon launching the application, users should be greeted with an introductory message explaining the purpose of 'AuraGuard' and a brief overview of what aura means in the context of the application.
2. **Aura Check**: Integrate the 'aura-farming-cli' package to allow users to check their current aura level. This feature should simulate a real-time aura check based on the user's interaction with the application.
3. **Interactive Aura Enhancement**: If the aura level is detected as negative ('W'), the application should provide playful suggestions and activities to help users enhance their aura. For example, it could suggest meditation exercises, listening to uplifting music, or engaging in positive conversations.
4. **Easter Egg Discovery**: Implement an Easter egg within the application related to the absence of pressing the 'Enter' key during the aura check process. If the user doesn't press 'Enter', they should receive a humorous and insightful message about the importance of engagement and participation.
5. **Logging and History**: Keep a log of the user's aura checks and enhancements. Users should be able to view their history and track their progress over time.
6. **User Interface**: Design a simple yet appealing command-line interface for the application. Ensure that all commands and options are clearly documented and easily accessible.
7. **Customization Options**: Allow users to customize their experience by setting preferences such as preferred methods of aura enhancement and notification settings for low aura levels.
The application should be developed using Python and the 'aura-farming-cli' package to ensure seamless integration of aura-related functionalities. Additionally, consider adding unit tests to verify the correctness of the application's core features.
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