OP here.

I built this because I recently caught myself almost pasting a block of logs containing AWS keys into Claude.

The Problem: I need the reasoning capabilities of cloud models (GPT/Claude/Gemini), but I can't trust myself not to accidentally leak PII or secrets.

The Solution: A Chrome extension that acts as a local middleware. It intercepts the prompt and runs a local BERT model (via a Python FastAPI backend) to scrub names, emails, and keys before the request leaves the browser.

A few notes up front (to set expectations clearly):

Everything runs 100% locally. Regex detection happens in the extension itself. Advanced detection (NER) uses a small transformer model running on localhost via FastAPI.

No data is ever sent to a server. You can verify this in the code + DevTools network panel.

This is an early prototype. There will be rough edges. I’m looking for feedback on UX, detection quality, and whether the local-agent approach makes sense.

Tech Stack: Manifest V3 Chrome Extension Python FastAPI (Localhost) HuggingFace dslim/bert-base-NER Roadmap / Request for Feedback: Right now, the Python backend adds some friction. I received feedback on Reddit yesterday suggesting I port the inference to transformer.js to run entirely in-browser via WASM.

I decided to ship v1 with the Python backend for stability, but I'm actively looking into the ONNX/WASM route for v2 to remove the local server dependency. If anyone has experience running NER models via transformer.js in a Service Worker, I’d love to hear about the performance vs native Python.

Repo is MIT licensed.

Very open to ideas suggestions or alternative approaches.

Very neat, but recently I've tried my best to reduce my extension usage across all apps (browsers/ide).

I do something similar locally by manually specifying all the things I want scrubbed/replaced and having keyboard maestro run a script on my system keyboard whenever doing a paste operation that's mapped to `hyperkey + v`. The plus side of this is that the paste is instant. The latency introduced by even the littlest of inference is enough friction to make you want to ditch the process entirely.

Another plus of the non-extension solution is that it's application agnostic.

I'd like to see this as a Windsurf plugin.

This should be a native feature of the native chat apps for all major LLM providers. There’s no reason why PII can’t be masked from the API endpoint and then replaced again when the LLM responds. “Mary Smith” becomes “Samantha Robertson” and then back to “Mary Smith” on responses from the LLM. A small local model (such as the BERT model in this project) detects the PII.

Something like this would greatly increase end user confidence. PII in the input could be highlighted so the user knows what is being hidden from the LLM.

Any plans to make the extension perform a replacement of whatever’s flagged with dummy data? Knowing I have sensitive data is usually not a problem, but constantly needing to replace or remove it is, particularly with larger token counts

Maybe you should fix your logging to not output secrets in plaintext? Every single modern logging utility has this ability.

This is a great idea of using a BERT model for DLP at the door. Have you thought integrating this into semantic router as an option leaving the look-ahead ? Maybe a smaller code base ?

Neat!

There's also:

- https://github.com/superagent-ai/superagent

- https://github.com/superagent-ai/vibekit

I wonder if this would have been useful https://github.com/microsoft/presidio - its heavy but looks really good. There is a lite version..

How do you prevent these models from reading secrets in your repos locally?

It’s one thing for the ENVs to be user pasted but typically you’re also giving the bots access to your file system to interrogate and understand them right? Does this also block that access for ENVs by detecting them and doing granular permissions?

Neat - I built something similar - https://github.com/deepanwadhwa/zink?tab=readme-ov-file#3-sh...

This is pretty cool. I barely use the web UIs for LLMs anymore. Any way you could make a wrapper for Claude Code/Cursor/Gemini CLI? Ideally it works like github push protection in GH advanced security.

Curious about how much latency this adds (per input token)? Obviously depends on your computer, but it's it ~10s or ~1s?

Also, how does this deal with inquiries when piece of PII is important to the task itself? I assume you just have to turn it off?

It wasn’t very clear in the video, does it trigger on paste event or when the page is activated?

There are a lot of websites that scans the clipboard to improve user experience, but also pose a great risk to users privacy.

Could this run at the network level (like TripMode)? So it would catch usage from web based apps but also the ChatGPT app, Codex CLI etc?

Anything like this for Claude Code/calls to OpenRouter?

Develop a pihole style adblock

Really good idea!

LLMs don't need your secret tokens (but MCP servers hand them over anyway): https://00f.net/2025/06/16/leaky-mcp-servers/

Encrypting sensitive data can be more useful than blocking entire requests, as LLMs can reason about that data even without seeing it in plain text.

The ipcrypt-pfx and uricrypt prefix-preserving schemes have been designed for that purpose.

can i have this between my machine and git please.. Like its twice now I've commmited .env* and totally passed me by (usually because its to a private repo..) then later on we/someone clears down the files.. and forgets to rewrite git history before pushing live.. it should never have got there in the first place.. (I wish github did a scan before making a repo public..)