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

[MyrinNew]

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:


john.doe@example.com


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


AKIAIOSFODNN7EXAMPLE `


→ Blocked immediately as AWS Access Key.


Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiIxM jM0NTY3ODkwIiwibmFtZSI6IkpvaG4gRG9lIiwiaWF0IjoxNTE 2MjM5MDIyfQ.SflKxwRJSMeKKF2QT4fwpMeJf36POk6yJV_adQ ssw5c


→ 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/...y-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.




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