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Fake Data Generator

Generate fake person data: name, email, phone, address, city, country, job, company, credit card, IP, user-agent, UUID. Locale ID/EN. Batch 1-50. Export JSON/CSV. 100% offline.

Offline ReadyPrivate
Open Tool
18 KBsize
Jun 2026updated

About this tool

Generate realistic-looking fake records for testing, demos, and database seeding. Each record can include any combination of: name, email, phone, address, city, country, job, company, credit card (Luhn-valid), IP, user-agent, UUID, age, gender, username, date of birth. The locale switch toggles between Indonesian and US data pools β€” Jakarta addresses and Indonesian names vs. New York and English names. Batch up to 50 records at a time. The 13 default fields cover most testing needs, but you can toggle individual fields on/off and the choice persists in localStorage. Credit card numbers pass the Luhn check (they are not real cards β€” do not use them for transactions). IPv4 addresses fall in the documentation ranges. User agents cover Chrome, Safari, Firefox, and mobile. Export to JSON, CSV, or copy directly to the clipboard. Everything runs in the browser β€” no Faker.js CDN, no network calls.

Details

Category
developer
Version
1.0.0
Size
18 KB
Updated
Jun 2026

Frequently Asked Questions

Is the generated data realistic?

Names, addresses, cities, jobs, and companies are drawn from real-world pools filtered to plausible values. Indonesian records use Indonesian names, +62 phone numbers, postal codes, and street names; English records use US names, +1 phone numbers, US state abbreviations, and zip codes. The data is realistic enough for screenshots, demos, and design mockups, but no individual record corresponds to a real person β€” every value is randomly assembled from its pool.

Are the credit card numbers real?

No. The card numbers pass the Luhn check (the mod-10 algorithm used to validate card numbers at point-of-entry), so they will pass naive front-end validation in test apps, but they are explicitly not real cards. The numbers are randomly generated from common BIN prefixes (Visa, Mastercard, Amex, Discover). Using them for actual transactions is fraud β€” and they will be declined because the issuing bank does not have them. They are safe for seeding test databases and testing payment form validation.

Is the data privacy-safe?

Yes β€” nothing is sent anywhere. All generation runs in the browser using Math.random() and the crypto API. The data is not stored, logged, or transmitted. Records are kept in memory only and disappear when you refresh the page. There is no analytics, no telemetry, no server round-trip. You can generate fake data containing internal test emails or fake PII without it ever leaving your device.

Can I get more than 50 records at once?

The cap is 50 per click to keep the UI responsive on phones and avoid accidental giant runs. If you need 1,000 records for database seeding, click Generate a few times in a row, copy the JSON each time, and concatenate. For larger jobs, paste the JSON output into a script and replicate. The export is just plain JSON or CSV β€” no proprietary format.

What is the difference between ID and EN locale?

The ID pool uses Indonesian first and last names, Indonesian cities (Jakarta, Surabaya, Bandung, Medan, Yogyakarta, etc.), Indonesian provinces, +62 phone numbers, and Indonesian-style addresses. The EN pool uses US English names, US cities, US state abbreviations, +1 phone numbers, and US-style addresses. Both pools draw company and job titles from their own cultural context. Switch the locale dropdown before generating to fill the next batch with the desired set.

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