🤖 AI Analysis

Final verdict: SAFE

The package is deemed safe with a moderate network risk that requires further investigation, but no other significant risks were identified.

Moderate network risk requiring further investigation
No shell execution, obfuscation, or credential harvesting detected

Per-check LLM notes

Network: The observed network call pattern may be part of legitimate functionality, such as checking for updates or fetching remote resources, but requires further investigation to confirm its purpose and destination.
Shell: No shell execution patterns were detected, indicating low risk in this aspect.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The maintainer has only one package, suggesting they may be new or less active, but no other red flags were found.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

is available.""" conn = http.client.HTTPConnection(host, port) try: conn.request("GET", "/")

✓ 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

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository kb-/Dash_tooltip appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "kb-" 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 Dash_tooltip

Create a user-friendly dashboard application using Python's Dash framework that incorporates tooltips for enhanced interactivity. This mini-app will serve as a tool for data visualization and exploration, allowing users to hover over specific elements on the dashboard to reveal additional information without leaving the current view. The application should include the following key components and functionalities:

1. **Data Visualization**: Implement at least two different types of charts (e.g., line chart and bar chart) to display sample datasets. These datasets could include historical stock prices or simple sales data.
2. **Tooltips Integration**: Use the 'Dash_tooltip' package to add tooltips to various elements within the dashboard. For instance, tooltips could appear when hovering over points on a line chart, bars in a bar chart, or even specific sections of the layout.
3. **Interactive Features**: Allow users to interact with the dashboard in meaningful ways. This could involve filtering data based on certain criteria, toggling between different datasets, or adjusting chart parameters dynamically.
4. **Customization Options**: Provide users with customization options such as choosing color schemes, changing chart types, or setting time intervals for time-series data.
5. **Responsive Design**: Ensure the dashboard is responsive, meaning it adjusts its layout and content based on the screen size of the device being used.
6. **Documentation and Comments**: Include thorough documentation within your code explaining how each component works, especially regarding the integration of 'Dash_tooltip'. Additionally, provide a README file that explains how to run the application and any dependencies required.

The goal of this project is not only to demonstrate proficiency in using the Dash framework but also to showcase the practical benefits of integrating tooltips for better user experience and engagement. By completing this task, you'll gain valuable insights into building dynamic web applications that leverage modern web technologies and Python libraries.