PhishGuard AI

Detect phishing emails instantly using AI-powered cybersecurity analysis.

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🛡️ PhishGuard AI

Inspiration

Phishing attacks are one of the most common cybersecurity threats today. Many users unknowingly click malicious links and share sensitive information because phishing emails often look legitimate. Our team wanted to build a smart and user-friendly solution that helps people identify phishing emails easily and improve cybersecurity awareness.

This inspired us to create PhishGuard AI, an AI-powered phishing detection and cybersecurity awareness platform.

What it does

PhishGuard AI analyzes suspicious emails and detects phishing behavior using multiple cybersecurity techniques.

Key Features

  • 📧 Email phishing detection
  • 📂 Drag-and-drop .EML email file analysis
  • 🔗 URL threat scanning using VirusTotal API
  • 🤖 AI-generated phishing explanations
  • 📊 Threat analytics dashboard
  • 🗂️ Scan history storage using SQLite
  • 📄 Downloadable PDF threat reports
  • 🚨 Live phishing simulation for cybersecurity awareness
  • 🌙 Dark mode user interface

The system generates a phishing risk score and classifies emails as:

  • ✅ Safe
  • ⚠️ Suspicious
  • 🚨 Dangerous

How we built it

We developed the project using:

  • Python Flask for backend development
  • HTML, CSS, JavaScript for frontend design
  • SQLite for storing scan history
  • VirusTotal API for real-time URL threat intelligence
  • Chart.js for dashboard analytics
  • ReportLab for PDF report generation

The application analyzes suspicious keywords, email headers, phishing URLs, and spoofing indicators to calculate the overall phishing risk.

Challenges we ran into

During development, we faced several challenges:

  • Parsing .EML email files correctly
  • Detecting phishing indicators accurately
  • Integrating VirusTotal API responses
  • Managing scan history using SQLite
  • Designing an attractive and responsive frontend
  • Creating realistic phishing simulations for awareness training

We solved these challenges through testing, debugging, and improving the phishing detection logic step by step.

Accomplishments that we're proud of

We are proud that we successfully built a fully functional cybersecurity project with multiple advanced features.

Some of our major accomplishments include:

  • Successfully integrating real-time threat intelligence
  • Building AI-generated phishing explanations
  • Creating downloadable cybersecurity reports
  • Implementing phishing simulation pages
  • Developing a professional analytics dashboard
  • Making the application beginner-friendly and interactive

What we learned

Through this project, we improved our knowledge in:

  • Cybersecurity fundamentals
  • Phishing attack detection
  • Python Flask development
  • Threat intelligence APIs
  • SQLite database management
  • Frontend UI/UX design
  • API integration and debugging

We also learned how to work as a team and present a real-world cybersecurity solution.

What's next for PhishGuard AI

In the future, we plan to add:

  • Machine Learning-based phishing detection
  • Browser extension support
  • Real-time email inbox scanning
  • Advanced AI threat analysis
  • Cloud deployment
  • Multi-language support
  • User authentication and admin dashboard

Our goal is to make PhishGuard AI a practical cybersecurity tool that helps users stay safe from phishing attacks.

Team Name

🛡️ PhishGuardians

Team Members

  • SIVANI S CYS
  • TEJAASHREE T S CYS
  • SANTHINI S CSE

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