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Text Anonymiser

Finds emails, phone numbers, card numbers and IDs in free text and masks or pseudonymises them.

Finds email addresses, phone numbers, card numbers, 주민등록번호, business registration numbers and IP addresses in a block of text and masks, redacts or pseudonymises them. The two most dangerous are checksum-verified, so a 16-digit order number is left alone and a real card is not.

🔒 Runs entirely in your browserprivacymaskpiiredact

Text

Nothing is uploaded. The scan runs in this tab, which is the only reason it is safe to paste this kind of text anywhere.

How to replace what it finds

Mode

010-****-5678 — still recognisable to its owner

Anonymised

6 replacements made.

Read the result before you share it.

This is pattern matching. It finds things shaped like an address, a card or a 주민등록번호 — and the two most dangerous of those are checksum-verified, so a 16-digit order number is not masked and a real card is. It cannot find a name, a street address written out in words, or an account number that looks like an invoice reference. Nothing here is a guarantee that the text is now safe to publish.

What was found

Email address

1

Korean resident number (주민등록번호)

1

Payment card number

1

Korean phone number

1

Korean business registration number (사업자등록번호)

1

IP address

1

  • line 3Email addressmi********@example.co.kr
  • line 4Korean phone number010-****-5678
  • line 5Korean resident number (주민등록번호)900101-1******
  • line 6Payment card number****-****-****-1111
  • line 8IP address192.168.x.x
  • line 9Korean business registration number (사업자등록번호)***-**-*****

How to use it

  1. Paste the text

    A support ticket, a log, a spreadsheet column. Nothing is uploaded — the scan runs in this tab, which is the only reason it is safe to paste this kind of text anywhere.

  2. Choose how to replace what it finds

    Masking keeps the value recognisable to its owner (010-****-5678). Redacting replaces it with a label. Pseudonymising gives each distinct value a stable stand-in, so you can still tell two mentions of the same person apart from two people.

  3. Turn off the detectors you do not want

    Each detector shows how many it found. Turning IP addresses off, for instance, keeps a log readable while still removing the personal data.

  4. Read the result before you share it

    The findings list says what was replaced and where. This step is not optional — the tool cannot find everything, and only you know what else is in there.

Common questions

Does this make the text safe to publish?

No, and nothing here claims that. This is pattern matching: it finds things shaped like an address, a card or a 주민등록번호. It cannot find a name, a street address written out in words, or an account number that looks like an invoice reference.

Why was one 16-digit number masked and another not?

Card numbers are Luhn-verified, so a number of the same length that fails the checksum is treated as an order reference and left alone. 주민등록번호 and 사업자등록번호 are checksum-verified the same way.

Can I undo the pseudonyms later?

Only if you copy the mapping now. It is kept in this tab and stored nowhere, so closing the page loses it — which is the same property that makes it safe.

A phone number was missed

Phone numbers have no checksum, so the detector matches on shape — and an unusual format, spaces in odd places, or an international prefix can fall outside it. Check the result rather than trusting the count.

Feed it from

Next

These accept what this tool produces, so the result can go straight in.