Redactify - Advanced PII Anonymization Platform

Redactify is a comprehensive solution for detecting and anonymizing personally identifiable information (PII) in text documents. The application combines a modern React frontend with a powerful Python Flask backend to provide an intuitive and effective PII redaction service.

PS : Still figuring out a way to host server for free. (There are some memory constraints on service providers like render)

🔍 Overview

Redactify helps organizations comply with data privacy regulations by identifying and removing sensitive information from text. The platform uses a sophisticated multi-method detection approach combining machine learning models, rule-based patterns, and Microsoft's Presidio Analyzer to achieve high accuracy PII detection.

Project Architecture

redactify/
├── client/          # React frontend application
│   ├── public/
│   ├── src/
│   ├── .env
│   └── package.json
│
├── server/          # Flask backend API
│   ├── server.py    # Main API entry point
│   ├── .env
│   └── requirements.txt
│
└── README.md        # This file

✨ Key Features

Detection Capabilities

• Multi-Method Detection: Combines machine learning (Hugging Face NER), rule-based patterns (regex), and Presidio Analyzer
• 13+ PII Types: Identifies personal names, organizations, locations, email addresses, phone numbers, credit cards, SSNs, IP addresses, URLs, dates, passwords, API keys, and roll numbers
• Customizable Confidence Thresholds: Configure detection sensitivity based on your needs

Anonymization Options

• Full Redaction: Replace PII with categorized placeholders (e.g., [PERSON-611732])
• Partial Redaction: Preserve some characters while masking others for better context retention
• Selective Anonymization: Enable/disable specific PII types for targeted redaction

User Experience

• Intuitive Interface: Clean, responsive design works across devices
• Real-time Feedback: Toast notifications provide operation status
• Animated UI: Smooth transitions make interaction pleasant
• Performance Optimizations: Concurrent processing for faster results

🛠 Technologies Used

Frontend (Client)

• React 18.2.0
• Framer Motion (animations)
• React Icons
• SweetAlert2 (notifications)
• CSS3 with custom styling

Backend (Server)

• Python 3.9+
• Flask web framework
• Microsoft Presidio Analyzer
• Hugging Face Transformers (BERT NER model)
• Regular expressions for pattern matching
• Thread pool for concurrent processing

🚀 Installation & Setup

Prerequisites

• Node.js (v16+)
• Python (v3.9+)
• npm or yarn
• pip

Clone the Repository

git clone https://github.com/rushilpatel21/Redactify.git
cd Redactify

Backend Setup

# Navigate to server directory
cd server

# Create and activate a virtual environment
python -m venv venv
source venv/bin/activate   # On Windows, use `venv\Scripts\activate`

# Install dependencies
pip install -r requirements.txt

# Run the server
python server.py   # Runs on http://localhost:8000 by default

Frontend Setup

# Navigate to client directory
cd client

# Install dependencies
npm install

# Create .env file
echo "VITE_BACKEND_BASE_URL='http://localhost:8000'" > .env

# Start development server
npm run dev   # Access at http://localhost:5173 by default

🔧 Environment Configuration

Backend

The server uses environment variables for configuration:

• PORT: Server port (default: 8000)
• CONFIDENCE_THRESHOLD: Detection confidence threshold (default: 0.6)

Frontend

The client uses a .env file for configuration:

• VITE_BACKEND_BASE_URL: Backend API URL (default: 'http://localhost:8000')

📝 API Documentation

Anonymize Endpoint

POST /anonymize

Request Format

{
  "text": "The input text containing PII to anonymize",
  "options": {
    "PERSON": true,
    "ORGANIZATION": true,
    "LOCATION": true,
    "EMAIL_ADDRESS": true,
    "PHONE_NUMBER": true,
    "CREDIT_CARD": true,
    "SSN": true,
    "IP_ADDRESS": true,
    "URL": true,
    "DATE_TIME": true,
    "PASSWORD": true,
    "API_KEY": true,
    "ROLL_NUMBER": true
  },
  "full_redaction": true
}

Response Format

Success:

{
  "anonymized_text": "The redacted text with PII anonymized"
}

Error:

{
  "error": "Description of the error that occurred"
}

📋 Usage Examples

Example 1: Full Redaction

Input:

This agreement is made between Generic & Associates (email: john.doe@example.com, phone: 555-123-4567) and Mr. John Smith (SSN: 123-45-6789).

Output:

This agreement is made between [ORGANIZATION-0458a5] (email: [EMAIL_ADDRESS-8eb1b5], phone: [PHONE_NUMBER-ca71de]) and Mr. [PERSON-611732] (SSN: [SSN-1e8748]).

Example 2: Partial Redaction

Input:

Please contact John Smith at john.smith@example.com or 555-123-4567.

Output:

Please contact Jo*****ith at jo****ith@*******.com or 55*******567.

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