I Built an Open-Source Privacy Firewall for ChatGPT (Runs 100% Locally)

Every developer I know uses ChatGPT or Claude daily. And every CISO in every company is terrified about it — specifically of getting a compliance violation or customer data breach notification.

Not because AI is bad — but because it's too easy to leak sensitive data without realizing it:

• Customer emails
• API keys
• Logs with tokens
• Stack traces with secrets
• HR info
• Employee names / internal IDs

We’ve all pasted something into ChatGPT and thought:

“Wait… should I really be sending this?”

Hence, I built PrivacyFirewall — an open-source, local-first privacy shield that blocks sensitive data before it is sent to any AI tool.

👉 GitHub: https://github.com/privacyshield-ai/privacy-firewall

Here is a screenshot of the block modal & the warning banner

🚨 The Problem: AI Prompts Are the New Data Leakage Vector

Traditional DLP tools were built for email, file uploads, and network traffic.

They don't protect AI prompts.

When you paste something into ChatGPT:

1. It instantly leaves your browser

2. Goes to a third-party server

3. And becomes part of your company's risk surface

Most leaks today aren't malicious; they're accidental.

• Developers paste logs

• Support teams paste customer messages

• HR pastes resumes

• Engineers paste configs

Once it's pasted, it's gone.

PrivacyFirewall acts before the send button, giving you a chance to stop mistakes. The data never leaves your computer.

🔒 What PrivacyFirewall Does

• ✔ Blocks risky paste events (emails, API keys, credit card patterns, tokens)

• ✔ Warns as you type when text looks sensitive

• ✔ Optional AI mode using a tiny local transformer (NER)

• ✔ Zero cloud calls — everything is offline

• ✔ Chrome extension + optional local FastAPI agent

• ✔ Open source under MIT

This is not cloud DLP.This is zero-trust, on-device protection.

Why Local Matters

• ✅ Compliance-friendly - No data leaves your machine

• ✅ Zero latency - Instant scanning, no network calls

• ✅ Works offline - On flights, VPNs, air-gapped systems

• ✅ No subscription costs - Run it forever, free

🧠 How It Works

PrivacyFirewall has two layers:

1. Browser Mode (no setup needed)

Works immediately after loading the Chrome extension.

Detects:

• Email addresses

• Phone numbers

• JWT tokens

• AWS keys

• Private key blocks

• Credit card patterns

• IP addresses

• Hash/API keys

This mode requires:

• ❌ no Python

• ❌ no downloads

• ❌ no models

• ❌ no server

Just load the extension and you get instant protection.

2. Advanced Mode (local LLM)

If you enable the optional backend (a FastAPI server running at 127.0.0.1:8765), PrivacyFirewall uses:

• dslim/bert-base-NER (local transformer)

• No internet connection

• Local inference using Hugging Face

This catches:

• People's names

• Organizations

• Locations

• Contextual clues a regex can't detect

If the engine goes offline, PrivacyFirewall automatically falls back to Lite Mode — so you're always protected.

🖥️ Demo

Try pasting any of these into ChatGPT:

[email protected]

→ You'll see a "Email Detected" modal.

AKIAIOSFODNN7EXAMPLE `

→ Blocked immediately as AWS Access Key.

Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiIxMjM0NTY3ODkwIiwibmFtZSI6IkpvaG4gRG9lIiwiaWF0IjoxNTE2MjM5MDIyfQ.SflKxwRJSMeKKF2QT4fwpMeJf36POk6yJV_adQssw5c

→ Caught as JWT token.

Meeting notes from Sarah Thompson at HR…

→ In Advanced Mode, the local transformer flags PERSON and warns you.

This all happens locally inside your browser.

🚀 Quickstart

1. Install the Chrome Extension (Lite Mode)

git clone https://github.com/privacyshield-ai/privacy-firewall.git
cd privacy-firewall


Load src/extension as an unpacked extension in Chrome.

2. (Optional) Run the Local AI Engine


cd src/engine
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
uvicorn main:app --host 127.0.0.1 --port 8765


Open ChatGPT → paste something sensitive → get warned.

📖 Full instructions in the repo.

🏗️ Tech Stack

• Chrome Manifest V3

• Content scripts + background worker

• FastAPI for the local agent

• Hugging Face transformers

• dslim/bert-base-NER for on-device NER

• Regex engine for deterministic detection

🧩 Current Focus / Roadmap

• UI settings panel in the popup

• Custom detection rules

• Support for Slack/Jira/Notion AI

• Firefox support

• Quantized models for speed (faster inference, smaller footprint)

• Packaging the agent into a small desktop app (Windows/Mac/Linux)

• Better redaction instead of blocking

If you want to help — PRs and ideas are welcome!

❓ Common Questions

Does this slow down my typing?
No! Detection runs asynchronously and doesn't block your workflow.

Can I whitelist certain patterns?
Not yet, but it's on the roadmap as "Custom detection rules."

Does it work with Claude/Gemini/other AI tools?
Yes! It monitors past events and text input across websites described in the manifest file.

🤝 Open to Feedback

I'd especially love feedback from:

• Security engineers

• AI safety folks

• Chrome extension developers

• People who accidentally pasted sensitive data into ChatGPT 👀

Try It Out 🚀

⭐ Star the repo: https://github.com/privacyshield-ai/privacy-firewall

Share your feedback in the issues
Contribute if you've got ideas

Have you ever accidentally pasted something sensitive into an AI tool?
Let me know in the comments! 👇

Thanks for reading — hope this helps make AI usage a little safer.