Phisher.AI is an email analysis tool that helps users identify potential phishing attempts in their emails. Built with modern web technologies and AI integration, this tool provides real-time analysis (through ChatGPT, and trained ML model) of email content to detect suspicious patterns and potential threats.
- Khadim Diop
- Jaymond Baruso
- Duy Nguyen
- Framework: Next.js 14 (React)
- Styling: Tailwind CSS
- UI Components:
- Shadcn/ui (Built on Radix UI)
- Lucide Icons
- Type Safety: TypeScript
- State Management: React Hooks
- Real-time email content analysis
- Optional subject line analysis (sklearn ML)
- User-friendly interface with clear feedback
- Detailed phishing probability scores
- Comprehensive analysis results with explanations
- Node.js (v18 or higher)
- npm or yarn
# Clone the repository
git clone https://github.com/your-username/phisher-ai.git
# Navigate to the project directory
cd phisher-ai
# Install dependencies
npm install
# or
yarn install
# Start frontent development server
npm run dev
# or
yarn dev
# Set up back end
cd flask-backend
# Create a .env file
GITHUB_KEY="your api key"
# Then
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
python3 app.py
- Open your browser and navigate to
http://localhost:3000 - Paste or type your email content in the main text area
- (Optional) Add the email subject for additional analysis
- Click "Analyze Email" to get the results
phisher-ai/
├── app/
│ ├── api/
│ │ └── analyze/
│ └── page.tsx
├── components/
│ ├── ui/
│ └── email-analyzer.tsx
├── lib/
│ └── utils.ts
├── public/
└── flask-backend/
- Add support for email attachment analysis
- Implement user authentication
- Add history tracking for analyzed emails
- Integrate with email clients via plugins
- Enhance UI/UX with more interactive features
- Add support for multiple languages
- Implement batch analysis for multiple emails
Note: This is the frontend documentation. For backend documentation and API details, please refer to the backend README.