privylayer 0.1.3

Privacy layer for AI prompts

🔐 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 [e-mail]"

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 [e-mail]

---

🧩 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!