🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits low risks in terms of network activity, shell execution, and obfuscation. However, its lack of detailed metadata and credentials, coupled with its novelty, raises concerns about potential malicious intent or incomplete information.

Lack of detailed metadata
New package version

Per-check LLM notes

Network: No network calls suggest the package does not engage in external communications which is typical for most packages unless they require internet access for functionality.
Shell: No shell executions detected indicating the package does not execute system commands, reducing the risk of unauthorized operations.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package is new and lacks detailed metadata, which raises some suspicion but does not conclusively indicate 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: example.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

Only one version has ever been released — brand new package
Author "RiskGrid AI" 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 aegis-base

Create a fully functional web-based dashboard application using Python and the 'aegis-base' package. This application will serve as a monitoring tool for various metrics within a company, such as employee productivity, sales performance, and customer satisfaction. The goal is to provide real-time insights and historical data analysis through interactive charts and tables. Here’s how you can approach building this application:

1. **Setup Environment**: Begin by setting up your development environment with Python installed and create a virtual environment. Install necessary packages including 'aegis-base', Flask for the web framework, and Plotly for data visualization.

2. **Data Collection**: Integrate the application with existing data sources (simulated or real) to collect metrics on a regular basis. For simplicity, you can use dummy data generators or APIs to simulate real-world data streams.

3. **Utilizing 'aegis-base'**: Use 'aegis-base' to manage routing for different sections of the dashboard. Implement its router functionalities to navigate between pages showing different types of reports like daily, weekly, monthly, etc. Additionally, utilize 'aegis-base' for generating comprehensive reports based on user interactions and data filters applied.

4. **Designing the Dashboard**: Design an intuitive UI/UX with clear navigation. Include widgets for displaying key performance indicators (KPIs), dropdown menus to filter data, and buttons to download reports in PDF format.

5. **Data Visualization**: Implement Plotly to visualize collected data. Create interactive charts and graphs to display trends over time, comparisons between departments, and other relevant metrics. Ensure that users can interact with these visualizations to explore the data further.

6. **Reporting Features**: Leverage 'aegis-base' reporting utilities to generate detailed reports based on user selections. These reports should include both visual representations and textual summaries of the analyzed data.

7. **Testing and Deployment**: Thoroughly test the application for functionality, usability, and responsiveness. Once satisfied, deploy the application using services like Heroku or AWS to make it accessible online.

By following these steps, you'll develop a robust, user-friendly dashboard application that not only showcases the capabilities of 'aegis-base' but also provides valuable business intelligence.