Replace personal data with realistic fake data

Fake names, streets and postcodes are chosen for this language. Choose it yourself for short texts, and for Bosnian or Montenegrin, which cannot be told apart automatically.

• NamesPeople’s names after greetings, titles and labels, then every other mention, including other grammatical cases
• Street addressesStreets with house numbers and P.O. boxes
• Postcodes and citiesPostcode followed by a town, e.g. 1000 Ljubljana or D-10115 Berlin
• Phone numbersLocal and international numbers; the country code is kept
• E-mail addressesReplaced with addresses at example.com
• IBANsBank accounts in IBAN format; only numbers with a valid checksum
• Personal ID and tax numbersEMŠO/JMBG, OIB, Slovenian tax number, Steuer-ID, Austrian and German social security numbers, VAT IDs
• Payment cardsCard numbers with a valid Luhn checksum
• Dates of birthDates after words like born, rojen, rođen, рођен or geboren
• Customer, contract and document numbersNumbers after labels such as customer no., passport, pogodba št., broj računa
• PINs, passwords and usernamesValues after labels such as PIN, CVV, password, geslo, lozinka
• IP addressesIPv4 and IPv6
• US Social Security numbersFormat 123-45-6789

A value you exclude can still be caught by a more general detector. For example, a labelled card number may be replaced as a document number.

One person per line, first name first. Names are found automatically only after cues such as “Dear”, “gospod” or “Lep pozdrav”; names listed here are replaced everywhere, including other grammatical cases (Janeza, Janezu). Up to 200 names.

Leave empty and every request gets different fake values. Enter the same key to get the same fake values every time, so separate texts stay consistent. Anyone who knows the key gets the same results, so use a long random key and never a password you use elsewhere.