AI-Based Phishing Email Detector

🧠 Inspiration “Phishing attacks are increasing day by day, and many users are not able to identify fake emails. This inspired me to build a simple and intelligent system that can help users detect phishing emails and protect their personal information.” ⚙️ What it does “My project is an AI-Based Phishing Email Detector that analyzes email details and identifies whether the email is phishing or legitimate. It uses machine learning and domain validation techniques to detect suspicious patterns and fake domains.” 🏗️ How I built it “I built this project using Python and Flask for the backend, and HTML, CSS for the frontend. A regression-based machine learning model was trained and saved using a pickle file. The frontend collects user input, sends it to the backend, and displays the prediction result.” 🚧 Challenges I ran into “I faced challenges like lack of real dataset, improving model accuracy, and connecting frontend with backend. Handling domain validation and detecting typo domains was also challenging.” 🏆 Accomplishments that I'm proud of “I am proud that I successfully built a complete working system with frontend, backend, and machine learning integration. The project can detect phishing emails and provide results quickly.” 📚 What I learned “I learned how to integrate machine learning models with web applications, how Flask works, and how to handle real-world problems like phishing detection.” 🔮 What's next for Phishing Detector “In the future, I plan to improve accuracy using deep learning models, use real-world datasets, and add real-time email scanning features.”

Built With

• css
• flask
• html
• ml
• python