Trawler Extension Phishing Website Detection Using Machine Learning

Abstract

1. Introduction

This literaly detect Phishing websites using Machine Learning and automaticaly warn it to user.

2. Objective

Phishing Website detection with Machine Learning. This include flask server, chrome extension and machine learning for phishing website detection.

This project demonstrates how Jupyter Notebook can be applied to a real-world Cybersecurity & Ethical Hacking problem.

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Python 3.8 or later with Jupyter Notebook / JupyterLab (or Google Colab)
• pip for dependencies
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/Hansajith98/Trawler-Extension-Phishing-Website-Detection-Using-Machine-Learning.git
cd Trawler-Extension-Phishing-Website-Detection-Using-Machine-Learning

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Add logging and alert notifications (email / Telegram)
• Write a threat model document for the tool
• Package it with Docker for safe lab testing

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. Which threat or attack does this project defend against?
2. What detection or protection technique is used and what are its limits?
3. How are false positives and false negatives handled?
4. Which cryptographic algorithms or security standards are involved?
5. What legal and ethical rules apply when testing a tool like this?

9. Source Code & License

This project is developed by Hansajith98 and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.