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Application Banner

1Guard-ai functions as a robust backend system integrated with a macOS Safari plugin, designed to analyze the security level of shopping websites accessed by users. Using the Flask framework in Python, the backend receives domain and user IP data from the Safari plugin via HTTPS requests. It leverages Scrapy for comprehensive website scraping and analysis, inspecting crucial aspects such as the presence of an imprint and the quality of the content's language. The system employs MongoDB for efficient data storage, offering quick access to previously scanned domains and their corresponding security scores. With a focus on scalability, the backend architecture is organized into distinct modules, including an API, a controller, an AI module, a website scanning module, and a database manager, facilitating streamlined data handling and processing. The application integrates various security features such as TLS certificate usage and rate limiting to ensure secure and optimized operations.



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Contents

 

Features

  • Monitoring: Continuously monitors visited websites and protects against fraud and scam.
  • Feedback: Allows users to give feedback on websites and their security scores.
  • Discrete: Operates in the safari menu, minimizing interruptions.
  • Customizable: Allows users to configure various settings.
  • Lightweight: Designed to consume minimal system resources for optimal performance.
  • Privacy: Only transmits the URL without path or parameters.
  • Open Source: Provides transparency and allows community contributions for continuous development.

 

Screenshots

TODO

 

Why should you care?

A few reasons to use this plugin:

TODO  

Installation

TODO  

Usage

 

Development

As an open-source project, I strive for transparency and collaboration in my development process. I greatly appreciate any contributions members of our community can provide. Whether you are fixing bugs, proposing features, improving documentation, or spreading awareness - your involvement strengthens the project. Please review the code of conduct to understand how we work together respectfully.

 

Roadmap

Now Next Later
Unit tests Linux and Windows support CI/CD
Code quality Auto update Website/Docs/Wiki
Cross browser support Translations Code sign (Apple)

 

Contributors

Thank you so much for giving feedback, implementing features and improving the code and project!

 

Credits

TODO

Many more credits are in the acknowledgments file.

 

License

Provided under the terms of the GNU GPL3 License © Lennart Haack 2023.

See LICENSE file for details. For the licenses of used third party libraries and software, please refer to the ACKNOWLEDGMENTS file.

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Semester's Project - System and Software Engineering 1 - AI

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