Ruby is a programming language best known for Ruby on Rails, but also used for Sinatra, Discourse, Redmine and Jekyll-built sites. AIWebsiteDetector reports Ruby from Server banners of Ruby application servers (Phusion Passenger, Puma, Unicorn, Thin, WEBrick), an `X-Powered-By` value naming Ruby or Passenger, a versioned generator tag of a known Ruby application, and from a detected Ruby on Rails site. Behind a proxy that rewrites these headers, Ruby sites show nothing.
Detect Ruby Websites — Free Tool
Enter any URL to check if it was built with Ruby. Instant results, no account required.
How we detect Ruby — see our methodology: AI Influence Score calculation, evidence tiers, and fingerprint signal types.
How to Detect Ruby Websites
HTTP Headers
2 patterns
1. Check the Page Source
Open the website in your browser, right-click, and select "View Page Source". Search for ruby-specific patterns in the HTML.
4. Use AI Website Detector (Easiest)
Our automated scanner checks all these signals at once and gives you an instant confidence score. Just enter any URL above.
Frequently Asked Questions
Is this website built with Ruby?
You can detect if any website was built with Ruby by using our free scanner above. Just enter the URL and we'll analyze HTML patterns, JavaScript files, CDN domains, and HTTP headers to determine if Ruby was used — with a confidence score.
How to detect if a website was built with Ruby?
There are several ways to detect Ruby: (1) View the page source and look for Ruby-specific class names or script URLs, (2) Check the Network tab in DevTools for requests to Ruby CDN domains, (3) Use our free tool — we check 2 detection signals automatically.
What websites are built with Ruby?
Ruby is used by thousands of websites worldwide. Our scanner has detected many Ruby-built sites across different industries. You can scan any URL to check if it uses Ruby.
How accurate is the Ruby detection?
Our Ruby detection engine checks 2 unique fingerprint signals, achieving high confidence results. We score each match and return a confidence percentage so you know how certain the detection is.
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Detection Info
- Category
- Backend Framework
- Signals Used
- 2 patterns
- Accuracy
- High
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