Bot detection
Browser fingerprints are a key factor in web scraping. They determine how likely you are to be detected as a bot, directly affecting your ability to crawl and extract data.
To minimize detection, our browsers are modified to replicate the fingerprints of typical internet users. This significantly reduces bot detection rates and enhances scraping performance. The objective is not to create a unique fingerprint, but to closely match common browser configurations. The more your browser resembles a normal user’s setup, the less likely it is to be flagged as a bot.
Fingerprint Scan
A bot risk score below 50 reduces your chances of being detected as a bot. We have the maximum score, completely undetectable.

You can test your bot risk score here.
How we did
Randomized browser fingerprints – each browser instance generates a fingerprint matching real-world user distributions (OS, timezone, language, hardware, GPU, etc.).
Dynamic user-agent rotation – periodic updates with valid and current user-agent strings from real browsers.
Authentic WebGL and canvas signatures – simulated GPU and rendering outputs aligned with normal variance found in human browsers.
Consistent screen and device metrics – logical screen resolution, color depth, and devicePixelRatio combinations identical to real devices.
Timezone and locale sync – IP-based timezones and locales match geolocation for coherence.
Regular data calibration – browser fingerprints benchmarked against large public datasets to match population averages.
Cookie and storage emulation – full support for session/local storage and cookies to appear as persistent, active users.
No headless signatures – masked automation indicators (navigator.webdriver, permissions API, window dimensions).
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