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ChatGPT VS phishing

As part of a university project at the THB IT department in Germany, I developed a Chrome extension that leverages ChatGPT to detect phishing attempts. The result is ChatGPT vs. Phishing, a tool designed to help users identify and avoid phishing scams while browsing the web. Here, I share my development journey, the challenges I faced, and the resources that aided me along the way.

Table of Contents

  1. Project Overview
  2. Learning and Utilizing ChatGPT
  3. Development Process
  4. Challenges and Solutions
  5. Conclusion
  6. References

Project Overview

ChatGPT vs. Phishing is a Chrome extension that uses OpenAI’s GPT model to analyze web content and detect phishing characteristics. This project allowed me to delve into both AI and cybersecurity, providing a practical solution to a pervasive issue.

Learning and Utilizing ChatGPT

Why ChatGPT?

ChatGPT, developed by OpenAI, is a powerful language model capable of understanding and generating human-like text. Its ability to analyze and interpret text makes it an ideal tool for detecting the subtle nuances often present in phishing attempts.

Resources for Learning About ChatGPT

  • OpenAI Documentation: The OpenAI API documentation provides comprehensive guides on how to use the GPT model, including examples and best practices.
  • OpenAI Community: The OpenAI Community Forum is a valuable resource for connecting with other developers, sharing experiences, and finding solutions to common issues.

Development Process

Initial Setup

The first step was setting up the development environment. I created a new project repository on GitHub and set up the necessary tools and dependencies for Chrome extension development and AI integration.

Chrome Extension Development

TBD

Challenges and Solutions

Understanding AI

Integrating AI into the project required a deep understanding of how language models work. Reading research papers and following AI-related blogs helped bridge the knowledge gap.

API Limitations

Using the OpenAI API comes with limitations, such as rate limits and token constraints. Efficiently managing API requests and handling errors gracefully was essential for the smooth functioning of the extension.

Conclusion

Developing ChatGPT vs. Phishing was a rewarding experience that not only enhanced my understanding of AI and cybersecurity but also contributed to the fight against phishing. I encourage anyone interested in these fields to check out the project on GitHub and contribute or use it to safeguard against phishing attempts.


References

This post is licensed under CC BY 4.0 by the author.