Dev

Fake Domain & URL Generator

A fake domain and URL generator is an essential tool for developers who need realistic web addresses without pointing to live sites. Whether you're seeding a test database, populating a UI mockup with believable link text, or writing fixtures for a URL parser, hardcoding example.com everywhere produces flat, unconvincing data that rarely catches edge cases. This generator produces varied, plausible-looking URLs across multiple formats so your test data actually resembles production traffic. The tool supports four output types: bare domains, full page paths, versioned REST API endpoints, and image asset URLs complete with dimension query parameters. You can pin the TLD to a specific extension like .io or .co, or leave it on mixed mode to get a spread of .com, .net, .org, and country-code variants in the same batch. That variety matters when you're testing a parser or formatter that needs to handle diverse real-world URL patterns without breaking. Fake URLs generated here follow realistic naming conventions — short pronounceable domains, kebab-case slugs, and sensible API path structures like /api/v2/users rather than random character strings. This makes them useful beyond pure code testing: copy them into Figma prototypes, slide decks, or training materials where audiences need to read the URLs without being distracted by obviously placeholder text. Generate between 1 and 100 URLs at a time, copy the list directly from the output, and drop them into your seed script, JSON fixture file, or design file. Because none of the domains are guaranteed to resolve, they are safe to use in internal demos and documentation without accidentally sending users to a real third-party site.

How to Use

  1. Set the Count field to the number of URLs your test fixture or seed file requires.
  2. Choose a URL Type: pick 'full' for a mixed batch, or select domain, API endpoint, or image URL specifically.
  3. Select a TLD Preference — use 'mixed' for variety or pin to a specific extension like .io or .com.
  4. Click Generate to produce the list, then copy all results with the copy button.
  5. Paste the output directly into your seed script, fixture JSON, design file, or documentation.

Use Cases

  • •Seeding a PostgreSQL database with varied website URLs for user profiles
  • •Writing Jest or Pytest fixtures that validate URL parsing logic
  • •Filling Figma wireframe link fields with readable, realistic addresses
  • •Generating REST API endpoint examples for internal API documentation
  • •Creating realistic phishing-simulation URLs for security awareness training
  • •Populating a CMS demo environment with diverse external link targets
  • •Testing a link-shortener service with a wide range of input URL shapes
  • •Adding believable placeholder hrefs to HTML email templates before launch

Tips

  • →Use 'mixed' TLD mode when testing a URL-display component — short TLDs like .io and long ones like .museum expose truncation bugs.
  • →Generate API endpoint URLs specifically when building mock server configs; the versioned paths (/api/v2/...) map directly to common route patterns.
  • →For Figma mockups, generate 20+ URLs and paste into a bulk-rename or data plugin so every link field gets a unique value, not the same string repeated.
  • →Combine image asset URLs with a placeholder image service by stripping the fake domain and prepending a real CDN — you keep the realistic path and query string.
  • →If your parser must handle subdomains, manually prepend 'www.' or 'api.' to a few generated domains to add that variation to your fixture set.
  • →Run two batches with different TLD settings and merge them when you need a dataset that includes both familiar (.com) and less-common (.co, .io) extensions.

FAQ

Are fake generated domains safe to use in production code?

Only as placeholder or test data — never in production logic that makes real network requests. Because the domains are randomly constructed, they could theoretically be registered by someone at any time. For integration tests that fire real HTTP requests, use a local mock server or a domain you control instead.

Why not just use example.com for all test URLs?

Repeating the same domain tests only one URL shape. Real applications encounter varied TLDs, subdomain structures, path depths, and query strings. Using a batch of diverse fake URLs catches edge cases in parsers, formatters, and UI truncation logic that a single repeated domain never would.

What URL types does this generator produce?

Four types: plain domains (e.g. rapidcore.io), full page paths with kebab-case slugs, versioned REST API endpoints like /api/v2/products/42, and image asset URLs with width and height query parameters. Select a specific type or use the full setting to get a mix.

Can I get only .com domains, or only a specific TLD?

Yes. Use the TLD Preference dropdown to pin output to .com, .net, .org, .io, or .co. Leave it on mixed to get a spread of extensions in the same batch, which is more useful when testing components that need to handle various TLD lengths and formats.

Do the generated URLs use HTTP or HTTPS?

All URLs use the https:// scheme, reflecting modern web standards. If your test suite specifically needs to validate HTTP-to-HTTPS redirect logic, you can manually change the prefix on a handful of results — the domain and path portions remain valid either way.

How many fake URLs can I generate at once?

The count input accepts any number up to 100 per batch. For large database seed files, run the generator several times and concatenate the outputs, or adjust the count to the exact number your seed script expects to keep things clean.

Can I use these fake URLs in security awareness training materials?

Yes, and it's one of the better use cases. Realistic-looking but non-functional URLs are ideal for phishing-simulation exercises or training slides because trainees practice spotting suspicious domains without any risk of accidentally visiting a live malicious site.

Are the generated domain names pronounceable or just random characters?

They follow common domain naming patterns — short, vowel-containing words or compound word pairs — making them read like plausible brand names. This matters for UI mockups and documentation where random character strings would look obviously fake and distract reviewers.