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Privacy layer for AI prompts

Project description

🔐 PrivyLayer

Privacy layer for AI systems — protect sensitive data before it reaches AI.


🚀 Overview

PrivyLayer is a lightweight Python library that acts as a security layer between user input and AI models.

It detects sensitive information (PII), replaces it with secure placeholders, and restores it after the AI response — ensuring zero data exposure.


⚡ Why PrivyLayer?

Modern AI systems process user input directly, which may include:

  • 📱 Phone numbers
  • 📧 Emails
  • 🪪 Aadhaar / PAN
  • 🏦 Bank details

This creates a privacy risk.

👉 PrivyLayer solves this by introducing a reversible masking system.


🧠 How It Works

User Input
   ↓
PrivyLayer (detect + mask)
   ↓
AI Model
   ↓
PrivyLayer (restore)
   ↓
Final Output

✨ Features

  • 🔍 Detects sensitive data using regex patterns
  • 🔁 Reversible masking (no data loss)
  • 🧠 Smart tokenization system
  • ⚡ Fast and lightweight
  • 🇮🇳 India-specific PII support
  • 🔒 No data stored globally

📦 Installation

pip install privylayer

🛠️ Usage

🔐 Protect (Mask data)

from privylayer import protect

text = "My phone is 9876543210 and email is test@gmail.com"

mask , context , seen = main.find_p(text)

print(mask)

Output:

My phone is ⟦PII_PHONE_x1⟧ and email is ⟦PII_EMAIL_x2⟧

🔓 Restore (Unmask data)

from privylayer import restore

original = restore(masked, context)

print(original)

Output:

My phone is 9876543210 and email is test@gmail.com

🧩 Supported Data Types

  • 📱 Phone numbers (India)
  • 📧 Email addresses
  • 🪪 Aadhaar numbers
  • 🧾 PAN numbers
  • 🏦 IFSC codes

🔐 Token Format

PrivyLayer replaces sensitive data with structured tokens:

⟦PII_TYPE_ID⟧

Example:

⟦PII_PHONE_x1⟧
⟦PII_EMAIL_x2⟧

⚠️ Limitations

  • Regex-based detection (may not detect names accurately)
  • Does not validate Aadhaar checksum (yet)
  • Context must be preserved for restoration

🚀 Roadmap

  • AI-based name detection
  • Risk scoring system
  • Browser extension
  • API gateway version
  • Encryption-based token vault

🤝 Contributing

Contributions are welcome!

  • Fork the repo
  • Create a feature branch
  • Submit a pull request

📄 License

MIT License


👨‍💻 Author

Built by Nithish 🚀

[Nithish's Portfolio] (https://nithishprogrammer.github.io/Nithish)

[Nithish's Github] (https://github.com/NithishProgrammer)


🌟 Vision

Making AI safe for everyone by protecting sensitive data at the source.


⭐ If you like this project, consider giving it a star!

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