AI Analysis
The package exhibits low risks in terms of network usage, shell execution, obfuscation, and credential handling. However, the metadata risk score is elevated due to the maintainer's new or inactive account and lack of author details.
- Metadata risk due to new/inactive maintainer account
- Lack of detailed author information
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires external services.
- Shell: No shell execution patterns detected, indicating no immediate risk of command injection or unauthorized system access.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
- Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
- Metadata: The maintainer has a new or inactive account and lacks author details, raising some suspicion but not conclusive evidence of malice.
Package Quality Overall: Medium (7.0/10)
Test suite present — 7 test file(s) found
7 test file(s) detected (e.g. mcurses.py)
Some documentation present
Documentation URL: "documentation" -> https://austin-tui.readthedocs.ioDetailed PyPI description (10206 chars)
No contributing guide or governance files found
Development Status classifier >= Beta
Partial type annotation coverage
158 type-annotated function signatures detected in source
Active multi-contributor project
7 unique contributor(s) across 59 commits in P403n1x87/austin-tuiActive community — 5 or more distinct contributors
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 P403n1x87/austin-tui appears legitimate
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
Create a real-time system monitoring tool using the Python package 'austin-tui'. This tool will allow users to monitor their system's CPU usage, memory usage, running processes, and network activity in a terminal interface similar to the Unix utility 'top'. The application should provide an intuitive way to navigate through different monitoring views and filter out specific processes based on user-defined criteria such as process name, PID, or resource consumption thresholds. Steps to develop this application: 1. Install the 'austin-tui' package and familiarize yourself with its core functionalities. 2. Design the main menu that allows users to switch between various monitoring screens (CPU, Memory, Processes, Network). 3. Implement the real-time data fetching logic using 'austin-tui' to display live updates of system metrics. 4. Add filtering options for each screen to enable users to focus on specific aspects of system performance. 5. Integrate keybindings for navigation and interaction within the application. 6. Test the application thoroughly under different system loads to ensure responsiveness and accuracy. 7. Document the setup process and how to use the tool effectively. Suggested Features: - Ability to sort processes by CPU or memory usage. - Option to highlight processes that exceed predefined thresholds. - Support for multiple sorting criteria on the same screen. - Customizable refresh interval for smoother performance under heavy load. - Detailed process information view including open files, threads, and environment variables. The 'austin-tui' package is utilized primarily for rendering the user interface and managing the display of real-time system data. It provides the necessary tools to create a dynamic and responsive terminal interface that updates continuously based on system events and statistics.
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