🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows minimal direct risks but has unusual metadata suggesting low maintainer activity and a lack of transparency, which could be indicative of potential supply-chain issues.

Low maintainer activity
Lack of GitHub repository

Per-check LLM notes

Network: No network calls detected, which is normal if the package does not require external communications.
Shell: No shell execution patterns detected, indicating no immediate signs of executing system commands.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
Metadata: The maintainer has only one package and lacks a GitHub repository, which may indicate lower activity or experience.

🔬 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

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "AndiEcker" 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 ae-system

Create a Python-based system monitoring utility named 'SysWatch'. This tool will utilize the 'ae-system' package to provide detailed insights into the system's performance metrics such as CPU usage, memory consumption, disk space, and network traffic. SysWatch should have both a command-line interface (CLI) and a simple web interface for real-time monitoring. Here’s a detailed breakdown of the requirements and steps to build this utility:

1. **System Requirements**: Ensure your environment has Python installed and the 'ae-system' package. If not available, install it via pip.
2. **Core Functionality**:
- Utilize 'ae-system' to gather system metrics at regular intervals (e.g., every minute).
- Display these metrics in a user-friendly format through the CLI.
3. **Features**:
- **CLI Interface**: Implement commands like `syswatch start`, `syswatch stop`, and `syswatch status`.
- **Web Interface**: Develop a basic web server using Flask or Django that updates every minute with the latest system metrics.
- **Alerting**: Integrate alert notifications when specific thresholds are exceeded (e.g., CPU usage over 80%).
4. **Implementation Steps**:
- Initialize a new Python project and set up virtual environments.
- Install necessary packages including 'ae-system', Flask/Django, and any other dependencies.
- Write functions to fetch system metrics using 'ae-system' methods.
- Create the CLI using argparse or similar libraries.
- Design the web interface templates and integrate them with the Flask/Django backend.
- Implement logic for periodic metric fetching and updating the web interface.
- Add alerting functionality based on predefined thresholds.
5. **Testing**: Thoroughly test the application to ensure all features work as expected under various conditions.
6. **Documentation**: Provide clear instructions on how to install, configure, and use SysWatch.

This project aims to leverage 'ae-system' for its powerful system helper capabilities, offering a comprehensive solution for system administrators and developers looking for an easy-to-use monitoring tool.