AI ENGINE ONLINE
GENERATIVE AI POWERED

Detect Phishing
Before It Strikes

Advanced NLP analysis + AI explanation engine to protect you from social engineering attacks. Paste any suspicious message below.

3.2M+
Messages Scanned
94.7%
Detection Accuracy
12ms
Avg. Response Time
$ MESSAGE ANALYSIS TERMINAL
0 chars
ATTACK SIMULATION LAB

Phishing Attack
Simulator

See how attackers craft deceptive messages. Educational tool to recognize manipulation tactics before falling victim.

SELECT ATTACK SCENARIO
🏦
Bank Account Verification
Financial phishing via spoofed bank alerts
💼
Fake Job Offer
Employment scam targeting job seekers
🔐
OTP Theft Attack
Social engineering to steal one-time passwords
📦
Parcel Delivery Scam
Fake courier notifications with malicious links
🏆
Prize / Lottery Win
Too-good-to-be-true reward phishing
🏛️
Government Impersonation
Fake tax authority or legal threat scams
PROJECT OVERVIEW

About PhishGuard AI

🎯

The Problem

Phishing attacks cost organizations billions annually. Social engineering exploits human psychology, making technical defenses insufficient. Users need awareness training, not just filters.

🧠

How AI Is Used

Rule-based NLP detects linguistic patterns, urgency triggers, and suspicious domains. Claude AI generates personalized explanations and educational simulations that adapt to each message context.

🛡

Detection Engine

Multi-layer analysis: keyword scoring, domain validation, impersonation pattern matching, sentiment analysis for urgency/fear tactics, and link structure inspection.

Tech Stack

Frontend: HTML5, CSS3, Vanilla JS with cybersecurity dashboard UI. Backend: Python Flask API. AI: Claude (claude-sonnet-4-20250514) for natural language explanation and simulation generation.

HOW TO RUN LOCALLY
# 1. Install Python dependencies
pip install flask flask-cors anthropic

# 2. Set your Anthropic API key
export ANTHROPIC_API_KEY="your_key_here"

# 3. Start the Flask backend
cd backend
python app.py

# 4. Open the frontend
open frontend/index.html
# or serve it with: python -m http.server 8080