🛡️ PhishGuard - Intelligent Phishing Website Detection

⚠️ Stay ahead of phishing attacks with real-time AI-powered detection.

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📌 Overview

PhishGuard is a lightweight, intelligent phishing detection web app that uses machine learning to classify websites as either Safe or Phishing. With an intuitive user interface and a robust backend model, it empowers users to identify potential threats in real-time by simply submitting a URL.

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✨ Features

• 🔍 URL-based phishing detection
• 📈 Uses 88 handcrafted features for precise classification
• 🧠 Built on a Random Forest Classifier with 93.44% accuracy
• 💡 Clean and responsive web interface
• ⚡ Instant predictions with animation effects for better UX
• 📱 Mobile-friendly layout

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🧠 How It Works

1. Users input a URL via the homepage.
2. The system extracts a comprehensive set of 88 features from the URL.
3. These features are passed to a pre-trained Random Forest model.
4. The result is displayed on-screen, indicating if the URL is:
   • ✅ Legitimate
   • ❌ Phishing

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🔬 Tech Stack

Backend

• Python
• Flask
• Scikit-learn
• Joblib (for model serialization)

Frontend

• HTML5, CSS3, JavaScript
• Responsive design with animated elements

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📊 Model Performance

Model	Accuracy
✅ Random Forest	93.44%
Decision Tree	89.28%
AdaBoost Classifier	88.41%

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🚀 Getting Started

🔄 Clone the Repository

git clone https://github.com/Deeksha-R-Kunder/Webpage-Phishing-detection.git
cd Webpage-Phishing-detection

⚙️ Set Up Environment

Make sure Python 3.8+ is installed.

Install the required packages:

pip install -r requirements.txt

▶️ Run the Application

python app.py

Now visit http://127.0.0.1:5000 in your browser to start detecting phishing websites.

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👩‍💻 Authors

• Chinmayee Bhat
• Deeksha R Kunder

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