Remove PII from text before it leaves your machine
Every day, millions of prompts go into AI assistants carrying things the model never needed: customer emails in a support log, phone numbers in a crash report, API keys in a config snippet, salary figures in a "summarize this doc" request. Once pasted, that data is on someone else's servers — subject to their retention, their training settings, their breach risk. PII redaction is the habit of stripping the sensitive parts out first, and this tool makes it a 30-second step: paste, review the highlights, copy the clean version.
What counts as PII in pasted text?
Personally identifiable information isn't just names. In the text people actually paste into AI tools, the leakiest items are contact details (emails, phone numbers), ID numbers (Aadhaar, PAN, GSTIN), payment-adjacent data (UPI IDs, card numbers), network details (IP addresses, internal hostnames), and secrets (API keys, tokens, passwords in config). This scrubber detects all of them with pattern matching tuned for India — +91 mobiles, Aadhaar, PAN, UPI VPAs, Razorpay keys — alongside the global formats.
How the scrubber works
- Paste. Detection runs as you type — entirely in your browser's JavaScript. Nothing is sent anywhere.
- Review. Every finding is highlighted in the preview. Click a highlight to keep that specific value (a public support email, say); click a type chip to toggle a whole category. Add person names and company names as custom terms — patterns can't find those, and any tool that claims otherwise is guessing.
- Choose your replacement. Labeled tokens (
[EMAIL_1], [PHONE_2]) keep the text readable and consistent — the same value always maps to the same token, so the AI can still follow "the customer with EMAIL_1 called twice". Black bars (████) are for text that must survive public exposure, since tokens are reversible while the tab is open.
- Copy and paste into your AI tool. The model gets the full context — the error shape, the log structure, the clause wording — without the identities.
- Restore (optional). Paste the AI's reply back and tokens swap to real values locally. The map lives only in page memory and dies on reload.
Checksum validation: fewer false alarms
Dumb pattern matching flags every 12-digit number as "Aadhaar" and every 16-digit run as a "card" — which trains users to ignore the tool. This scrubber validates Aadhaar numbers with the Verhoeff checksum and card numbers with the Luhn check, and checks PAN's holder-type letter and GSTIN's structure, so random digit strings are left alone. Fewer highlights, each one worth your attention.
Real-world use cases
Sanitize logs before ChatGPT. Paste the stack trace, keep the error, lose the emails, IPs, and Bearer tokens riding along in the headers. Client work under NDA. Analysts and freelancers can get AI help on a contract or dataset with names, amounts, and IDs tokenized. Stack Overflow questions. Scrub the config snippet before posting — leaked AWS keys get harvested by bots within minutes. Support tickets. Agents can share conversation exports internally without spreading customer PII. HR and hiring. Redact resumes or salary slips before circulating for a second opinion.
What this tool will not do
It won't find names, addresses, or company names reliably — no regex can, and the page says so instead of pretending. It won't make text legally compliant (GDPR/HIPAA de-identification depends on process, not just patterns). And labeled tokens are not encryption: anyone with the tab open can restore them, so use black bars for anything that must be public-safe. The review step is the safety net — treat it as mandatory.
The bottom line
The cheapest privacy incident is the one where the sensitive data never left your device. Scrub first, paste second — make it muscle memory.