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⚡ REDACT V2 is a privacy-first desktop app that automatically detects and redacts PII (Personally Identifiable Information) from text, PDFs, and Word docs. Built with Electron.js & Node.js, it uses Hugging Face NER models for secure offline/online redaction with a clean UI.

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✂️ R.E.D.A.C.T V2

Restricting Exposed Data by Anonymization for Confidential Transmission

🔐 An Electron-based desktop app to redact sensitive PII from text documents and clipboard content using the Hugging Face Inference API, with a preview and restore-friendly workflow.


🚀 Features

  • 🧠 Redacts PII using Hugging Face's dslim/bert-base-NER model (NER-based)
  • ✍️ Inline editing of redacted content
  • 📋 Clipboard redaction/restoration with one click
  • 📂 Drag-and-drop file support for .txt, .pdf, .doc, .docx
  • 🔔 Popup alerts and feedback
  • 📄 Generates -REDACTED clones while preserving original format

🖼️ Preview

R.E.D.A.C.T Preview


🛠️ Installation

  1. Clone the Repository

    git clone https://github.com/KarthikBalaji-007/REDACT V2.git
    cd Freshathon
  2. Install Dependencies

    npm install
  3. Configure Hugging Face API

    • Create a .env file in the root folder
    • Add your API key like this:
      HUGGINGFACE_API_KEY=your_api_key_here
  4. Run the App

    npm start

🧑‍💻 Usage

📋 Redact Clipboard Content

Click Redact Clipboard → Detected PII is replaced with tags → Displayed in new window

♻️ Restore Clipboard Content

Click Restore Clipboard → Original content restored from mapping → Displayed in new window

📄 Redact a Document

Drag-and-drop .txt, .pdf, .doc, or .docx → Redacted version shown → Saved with -REDACTED suffix

✏️ Edit Redacted Text

Click on redacted tags to manually edit or restore


⚠️ Note on Accuracy

This app uses the dslim/bert-base-NER model from Hugging Face’s Inference API for redaction.
It offers good baseline coverage but may occasionally miss certain entities.
Always review output before sharing externally.


📁 Examples

Check the examples/ folder for sample input/output:

  • example_data.txt – Sample input text
  • example_data.txt-REDACTED.txt – Redacted version
  • example_data.pdf – Sample PDF
  • example_data.pdf-REDACTED.txt – Redacted output in plain text

📜 License

MIT License


🌟 Feel free to fork, star, and contribute to make R.E.D.A.C.T. even better!

About

⚡ REDACT V2 is a privacy-first desktop app that automatically detects and redacts PII (Personally Identifiable Information) from text, PDFs, and Word docs. Built with Electron.js & Node.js, it uses Hugging Face NER models for secure offline/online redaction with a clean UI.

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