AI PhishGuard

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  AI PhishGuard – Smart Protection Against Phishing Attacks

💡 Inspiration

Phishing attacks are increasing rapidly and affect students, professionals, and small businesses the most. Many users cannot easily identify fake links, emails, or scam messages. We wanted to build a simple yet powerful AI-based solution that helps anyone quickly check whether a message or link is safe or dangerous.

🚀 What it does

AI PhishGuard analyzes user-provided text or URLs and detects whether it is phishing or safe.

Key Features:

🔍 Detects phishing links and scam messages

🤖 AI-based text analysis

⚡ Real-time result using Flask backend

🌐 Simple, clean web interface

🛡️ Helps users stay safe online

🛠️ How we built it

Frontend: HTML, CSS, JavaScript

Backend: Python, Flask

AI Logic: Rule-based + ML-ready structure

API Handling: Flask-CORS

Architecture: Frontend ↔ Flask API ↔ AI Detection Logic

The frontend sends user input to the Flask backend, which processes the data and returns a phishing detection result.

⚠️ Challenges we ran into

Connecting frontend with backend APIs

Handling CORS issues between browser and Flask

Dependency errors during setup

Designing a simple yet professional UI under time pressure

🏆 Accomplishments that we're proud of

Successfully built a working AI-based phishing detector

Created a fully functional backend + frontend integration

Solved real-world cybersecurity problems

Built a hackathon-ready project within limited time

📚 What we learned

Flask backend development and API handling

Frontend–backend communication

Debugging dependency and server issues

Importance of cybersecurity awareness

🔮 What's next for AI PhishGuard

🚀 Deploying on cloud (Render / Vercel + Railway)

📧 Email scanning support

🔗 Browser extension

🧠 Advanced ML model integration

📱 Mobile app version

Built With

• concept)
• css
• flask
• flask-cors
• html
• javascript
• learning
• machine
• python