User Agent Parser
Parse and analyze user agent strings to extract browser, OS, and device information
User Agent Parser
Parse and analyze user agent strings to extract browser, OS, and device information
About User Agent Parser
Parse and analyze user agent strings to extract detailed information about browsers, operating systems, devices, and rendering engines. Our user agent parser provides comprehensive analysis for web analytics, device detection, bot identification, and browser compatibility testing across desktop, mobile, and automated systems.
- Browser identification and version detection
- Operating system and platform analysis
- Device type and model recognition
- Engine detection (WebKit, Blink, Gecko, etc.)
- Bot and crawler identification
How to Use User Agent Parser
- Input User Agent - Paste a user agent string from browser developer tools or logs
- Parse Information - Extract browser, OS, device, and engine details
- Analyze Results - Review comprehensive breakdown of detected components
- Export Data - Use parsed information for analytics and compatibility testing
- Batch Processing - Parse multiple user agents for statistical analysis
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Frequently Asked Questions
What is a user agent string?
A user agent string is an HTTP header that web browsers and other applications send to identify themselves to web servers. It contains information about the browser name, version, operating system, device type, and rendering engine.
How do I find my user agent string?
You can find your user agent string by opening browser developer tools (F12), going to Console tab, and typing 'navigator.userAgent'. You can also visit websites that display your user agent or check server logs for incoming requests.
Why do user agents sometimes show incorrect information?
User agents can be misleading due to historical compatibility reasons, browser spoofing, or custom modifications. Many browsers include legacy browser names for compatibility, and some applications intentionally modify their user agent strings.
How can I detect mobile vs desktop devices?
User agent parsing can identify device types by analyzing specific patterns like 'Mobile', 'Tablet', 'Android', 'iPhone', 'iPad', etc. However, for production use, consider combining user agent detection with feature detection and responsive design principles.
Can user agent parsing identify bots and crawlers?
Yes, many bots and crawlers have distinctive user agent patterns like 'Googlebot', 'Bingbot', 'facebookexternalhit', etc. However, sophisticated bots may disguise themselves as regular browsers, so additional detection methods may be needed.
Understanding User Agent Components
User agent strings contain multiple components that provide different types of information. Understanding these components helps in accurate parsing and analysis.
Typical Components:
Common Patterns by Platform:
| Platform | Key Indicators | Example Pattern |
|---|---|---|
| Windows | Windows NT, WOW64 | Windows NT 10.0; Win64; x64 |
| macOS | Macintosh, Mac OS X | Macintosh; Intel Mac OS X 10_15_7 |
| iOS | iPhone, iPad, iOS | iPhone; CPU iPhone OS 14_6 |
| Android | Android, Mobile | Android 11; SM-G991B |
| Linux | Linux, X11, Ubuntu | X11; Linux x86_64 |
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Common Use Cases
Web Analytics:
- Visitor browser statistics
- Device type distribution
- Operating system analytics
- Mobile vs desktop traffic
- Browser compatibility tracking
- Feature support analysis
- User behavior segmentation
- Performance optimization insights
Development and Security:
- Bot and crawler detection
- Responsive design testing
- Cross-browser compatibility
- Feature detection fallbacks
- Security threat analysis
- API access control
- Content delivery optimization
- A/B testing segmentation
Browser and Engine Detection
Modern browser detection requires understanding the relationship between browsers, engines, and the historical evolution of user agent strings.
Major Browsers:
- Chrome: Uses Blink engine (formerly WebKit)
- Firefox: Uses Gecko engine
- Safari: Uses WebKit engine
- Edge: Uses Blink engine (Chromium-based)
- Opera: Uses Blink engine (Chromium-based)
- Internet Explorer: Uses Trident engine
Mobile Browsers:
- Chrome Mobile: Android default browser
- Safari Mobile: iOS default browser
- Samsung Internet: Samsung devices
- Firefox Mobile: Cross-platform mobile
- Opera Mobile: Lightweight mobile browser
- WebView: In-app browser component
Detection Challenges:
- • Spoofing: Browsers may pretend to be other browsers
- • Compatibility: Legacy names included for website compatibility
- • Evolution: User agent strings change over time
- • Customization: Users and apps can modify user agent strings
Implementation Guide
Implementing user agent parsing in applications requires careful consideration of accuracy, performance, and maintenance as user agent patterns evolve.
JavaScript Example:
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