🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risk indicators with no network calls, shell executions, or obfuscation patterns. The metadata suggests it may be from a less active maintainer, but there's no evidence of malicious intent.

Low network and shell risk
No obfuscation or credential harvesting
GPL v3 license

Per-check LLM notes

Network: No network calls detected, which is normal for a graphing library without internet functionality.
Shell: No shell executions detected, which is expected for a PyQt6-based visualization tool.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
Credentials: No credential harvesting patterns detected, suggesting no risk of secret theft.
Metadata: Low activity and lack of detail suggest potential low effort or new maintainer, but no clear signs of malice.

🔬 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: riverbankcomputing.com

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Author "Riverbank Computing Limited" 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 PyQt6-Graphs-Qt6

Develop a user-friendly stock market analysis tool using the PyQt6-Graphs-Qt6 library in Python. This tool will allow users to input stock symbols and visualize historical stock price data over time through interactive line graphs and candlestick charts. The application should also provide basic technical indicators such as moving averages and RSI (Relative Strength Index) for each stock symbol selected by the user. Additionally, the tool should include features like real-time data updates from an API (such as Alpha Vantage or Yahoo Finance), customizable chart settings, and save/export options for the generated graphs.

Steps to create the application:
1. Set up your development environment with Python and install the necessary packages including PyQt6-Graphs-Qt6.
2. Design the UI layout using PyQt6 widgets, ensuring it includes fields for entering stock symbols, buttons for fetching data, and areas for displaying graphs and indicators.
3. Implement functionality to fetch historical stock data using an external API. Ensure the fetched data is properly formatted for graphing.
4. Utilize PyQt6-Graphs-Qt6 to plot the fetched data on interactive line graphs and candlestick charts. Make sure these graphs update in real-time when new data is fetched.
5. Add features for calculating and displaying technical indicators alongside the stock price data.
6. Integrate real-time data update capabilities to keep the displayed information current.
7. Implement customization options for the graphs, such as choosing between different types of charts, adjusting color schemes, etc.
8. Finally, add functionality to save or export the generated graphs as image files or CSV data.

By following these steps and utilizing the PyQt6-Graphs-Qt6 package effectively, you'll develop a powerful yet easy-to-use tool for analyzing stock market trends.