🔮 Website: PhishAI.co
Phishing is one of the most dangerous and deceptive cyber threats today. Attackers use emails, websites, and messages to trick individuals into revealing sensitive information like passwords, banking details, and personal data. The consequences? Financial losses, identity theft, and corporate data breaches.
Introducing PhishAI – an AI-driven, interactive phishing detection and training platform that helps individuals and businesses identify, analyze, and defend against phishing attacks.
📌 90% of data breaches are caused by phishing.
📌 Social engineering attacks are becoming more sophisticated.
📌 Employees and individuals lack proper phishing awareness training.
✅ AI-Powered Phishing Detection: Uses AWS Bedrock, Amazon Polly, and SageMaker to analyze emails and links in real-time.
✅ Real-World Phishing Training: Interactive scenarios that simulate phishing emails, calls, and websites.
✅ Gamified Learning Experience: Score points, level up, and become a phishing expert!
✅ Enterprise-Grade Security Training: Helps businesses train employees and reduce cybersecurity risks.
📦 PhishAI
├── 📜 LICENSE
├── 📜 README.md
├── 🏢 app
│ ├── 🛠️ handlers
│ │ ├── scenario_handler.py # Handles different phishing training scenarios
│ │ └── user_response_handler.py # Processes user responses in training sessions
│ ├── 🏗️ lambda
│ │ ├── main.py # AWS Lambda function for processing phishing detections
│ │ └── requirements.txt # Dependencies for Lambda
│ └── 🛠️ utils
│ ├── bedrock_client.py # AWS Bedrock API integration for AI analysis
│ ├── polly_client.py # AWS Polly for voice-based phishing training
│ └── sagemaker_client.py # AWS SageMaker for ML-powered phishing detection
├── 📖 docs
│ ├── 🖼️ architecture_diagram.png # System architecture overview
│ ├── 📜 design_decisions.md # Explanation of tech stack and decisions
│ └── 🚀 roadmap.md # Future improvements and features
├── 🌐 frontend
│ ├── 📜 README.md # Frontend documentation
│ ├── 📜 eslint.config.js # Linter configuration
│ ├── 📜 index.html # Main entry point for the frontend
│ ├── 📜 package.json # Frontend dependencies
│ ├── 🎨 postcss.config.js # CSS processing setup
│ ├── 🖼️ public/
│ │ ├── favicon1.png # App favicon
│ │ ├── images/
│ │ │ └── facebook-logo.png # Example phishing email logo
│ │ └── vite.svg # Vite logo for UI
│ ├── 🖌️ src/
│ │ ├── 🖥️ App.jsx # Main React component
│ │ ├── 🖼️ assets/
│ │ │ └── react.svg # React logo asset
│ │ ├── 🛠️ components/
│ │ │ ├── 🔐 AuthForm.jsx # Authentication form (future feature)
│ │ │ ├── ✉️ ContactForm.jsx # Contact support form
│ │ │ ├── 📧 ScenarioDisplay.jsx # Displays phishing training scenarios
│ │ │ └── 🛠️ ui/
│ │ │ ├── 🚨 alert.jsx # Custom alert component
│ │ │ └── 📝 card.jsx # Reusable UI card component
│ │ ├── ⚙️ config/
│ │ │ └── 📜 scenarios.js # Phishing training scenarios
│ │ ├── 🎨 index.css # Global CSS styles
│ │ └── 🚀 main.jsx # React app entry point
│ ├── 🎨 tailwind.config.js # Tailwind CSS configuration
│ └── 🛠️ vite.config.js # Vite build configuration
├── ☁️ infrastructure
│ ├── 📦 lambda_package.zip # Packaged Lambda function for AWS
│ ├── 📜 main.tf # Terraform infrastructure definition
│ ├── 📜 outputs.tf # Terraform output variables
│ ├── 📜 providers.tf # Terraform provider configurations
│ ├── 📜 terraform.tfstate # Terraform state file
│ └── 📜 variables.tf # Terraform variables
├── 🤖 models
│ └── 🧠 model_configs/
│ └── stable_diffusion_config.json # AI model configuration
├── 📜 package-lock.json # Dependency lockfile
├── 🎭 scenarios
│ └── 📜 prompts/
│ ├── 📜 Lvl 1 scam.txt # Beginner phishing scenario
│ ├── 📜 Lvl 2 RealEmail.txt # Legitimate email scenario
│ ├── 📜 Lvl 3 scam2.txt # Intermediate phishing scenario
│ ├── 📜 Lvl 4 ScamEmail.txt # Advanced phishing scenario
│ ├── 📜 Lvl 5 RealEmail.txt # Another legitimate email example
│ └── 📜 scam_call2.txt # Phone call phishing script
└── 🛠️ test
│ ├── 🔍 integration/
│ │ └── 🧪 test_api_calls.py # Tests for API calls
│ └── 🧪 unit/
│ └── 🧪 test_scenario_logic.py # Tests for phishing scenario logic
1️⃣ Real-Time Phishing Detection
🔹 Uses AWS Bedrock to analyze emails & URLs for phishing indicators.
🔹 Flags suspicious content, bad links, and social engineering tactics.
2️⃣ AI-Powered Phishing Simulations
🔹 Provides interactive email & call-based phishing scenarios.
🔹 Uses AWS Polly to generate realistic voice phishing attacks.
3️⃣ Machine Learning-Based Threat Analysis
🔹 Uses AWS SageMaker for advanced phishing detection models.
🔹 Learns from user behavior to improve security awareness.
4️⃣ Gamified Training Experience
🔹 Users earn points & progress through levels to become cybersecurity experts!
🔹 Features real-world phishing examples to test your skills.
✔️ Multi-Language Support 🌍
✔️ AI Chatbot for Phishing Queries 🤖
✔️ Integration with Security Awareness Platforms 🔐
Phishing attacks are constantly evolving – but with PhishAI, you and your team can stay one step ahead. Whether you’re an individual, business, or security professional, PhishAI empowers you with the tools needed to identify, prevent, and educate against phishing threats.
🔹 Ready to start your AI-driven security training? Contact us today! 📩
📧 Email (not set up yet): support@phishai.co
📞 Phone (not set up yet): +1-800-PHISH-AI
🌐 Website: PhishAI.co
🔗 LinkedIn (not set up yet): linkedin.com/company/PHISHAI