Fake Data Generator

Can the email addresses reach a real person?

No. Every address ends in example.com, example.org or example.net, which are domains reserved for documentation and testing, so they should not belong to any real mailbox. The part before the @ is the first name, a dot, the surname and a number from 1 to 99, for example michael.moore57@example.com. If your app validates domains against a deny-list or checks MX records, example.com will fail that check.

Are the phone numbers real?

US numbers use the 555-01xx block, which North American numbering reserves for fictional use, with a random area code. The UK (+44 7xxx xxxxxx), Australian (+61 4xx xxx xxx) and Indian (+91 7xxx xxxxxx) numbers are simply random digits in a plausible shape. They are not taken from any reserved fictional range, so one could coincide with a working number. Do not dial or text them.

Why do the cities, regions and postcodes not match each other?

Each part is picked independently. A US record can come out as "New York, OH 31139" and a UK one as "Sheffield, Wales SE15 7EF". The street, city, region and postal code are all random draws from separate short lists, so the combination will not pass a check that compares them with each other, such as a postcode-to-city lookup.

How many records can I generate, and how varied is the data?

Between 1 and 5 per run; larger numbers are cut to 5, and an empty or invalid entry gives 1. Names come from just 15 male first names, 15 female first names and 15 surnames, so there are only 450 possible name pairs and repeats appear quickly. For bulk or seeded data use a library such as Faker in your own code.

Do the other locales use local names?

No. The locale setting changes the email domain pool, phone prefix and format, city list, region list and postcode shape. The first names and surnames are the same common English-language list for United States, United Kingdom, Australia and India, so an Indian-locale record may read "Susan Moore".

What fields are included, and what is missing?

Full profile gives name, email, phone, address, date of birth and gender. Contact gives name, email and phone, and Name gives just the name. Date of birth is a random year from 1960 to 2002 with a day between 1 and 28, written YYYY-MM-DD. There are no national ID numbers, passwords, payment cards, job titles or avatars.

Is the output random enough to be unpredictable?

It is generated with Math.random, which suits sample data but is not a cryptographic source. Never use the output as passwords, tokens or any value that must be unguessable. Results are not seeded, so you cannot regenerate the same record later; copy what you need.