Foreign Identity Generator

📖 What this does

Signing up for an overseas service, seeding a test database, or putting together a demo often means you need a batch of foreign personal details that look believable. Making them up by hand goes wrong quickly: the city ends up in the wrong state, the postcode belongs to somewhere else entirely, the phone area code points at another region, and the card number fails even a basic Luhn check. This tool generates between one and twenty plausible profiles at a time, filling in eighteen fields at once: name, gender, date of birth, age, occupation, street address, city, state or province, postcode, country, international dialling code, landline, mobile, email, national ID or tax number, card number, expiry date and CVV. Coverage spans 50 countries and regions with 736 real cities. Everything is computed inside your browser and nothing is sent anywhere.

✨ Features

• Up to twenty rows per run, with all eighteen fields produced together rather than piece by piece.
• 50 countries and regions and 736 cities, each city record carrying its real state or province code, a postcode range and its own area codes.
• Generation picks the city first and derives everything else from it, so the address, the postcode and both phone numbers always describe the same place. A New York street never comes with a Los Angeles dialling code.
• Identification numbers follow the check-digit rule each country actually publishes. Canadian SINs, Brazilian CPFs, Swedish personal numbers, South African IDs and every card number pass Luhn. Indian Aadhaar uses Verhoeff. German tax IDs use ISO 7064. Italian fiscal codes, French NIR, Japanese My Number and Korean RRN each use their own national algorithm, and US SSNs steer clear of the ranges the authorities never issue.
• Card numbers start from genuine issuer BIN prefixes and clear the Luhn check, with an expiry date and CVV supplied, yet they map to no real account anywhere.
• Output can be copied as plain text or exported as CSV, and name order flips automatically for countries such as Japan and Korea where the family name comes first.

🛠 How to use it

1. Pick a target country from the dropdown, or leave it unset if you would rather each row came from a different country.
2. Choose a gender: male, female, or random, and set how many records you want: 1, 5, 10 or 20.
3. Tick the fields you need. All are selected by default, so you can drop the card fields when you only want basic contact details.
4. Press Generate. Results appear as a table, one person per row.
5. Use Copy to grab the plain text version, or Export CSV to download the table as a file.

⚠️ Before you use the output

• Everything here is fictional. It is meant for software testing, filling in forms, interface demos and teaching. Do not use it for any real transaction, registration, identity check or fraud.
• House numbers are random. Street names come from common local road names in the right language, but the number in front of them does not belong to a real dwelling, so do not treat an address as a physical location.
• The numbers are well-formed, not real. They satisfy whichever checksum applies, but no bank or government system will recognise them, and they cannot pass a real identity verification.
• Postcodes fall inside genuine city ranges. The range matches what that city actually uses, though the specific code drawn from it is random, just like the house number.
• The tool runs entirely offline. It calls no remote service and keeps working with the network unplugged. Data stays on the page you are looking at and disappears on reload, with nothing retained.