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Explore the blog →Run a full fingerprint test inside your browser and see whether your profile reads as a real human or gives itself away as spoofed, automated, or leaking your real IP.
Runs automatically when the page loads.Collecting signals…
Every signal read from this browser, the way an anti-fraud script would read it.
| Signal | Value |
|---|
Stored locally in your browser. Re-run to watch your fingerprint drift.
No runs yet.
Anonymized verdicts from recent visitors. No IPs or User-Agents stored.
The tool reads your User-Agent, platform, languages, timezone, screen and color depth, device pixel ratio, CPU cores, device memory, plugins, canvas hash, WebGL vendor and renderer, and WebRTC STUN candidates. It uses the same browser APIs an anti-fraud script reads.
It runs four leak checks against each other: does your UA OS match navigator.platform, does your timezone match your IP geo, does WebRTC expose a local IP behind your proxy, and is your canvas or WebGL spoofed or falling back to a software renderer. It also scans for automation tells.
You get a verdict of CONSISTENT, LEAKY, or DETECTED, a believability score from 0 to 100, per-check pass/fail rows, and a rarity estimate of how many other profiles share your exact fingerprint.
A timezone that disagrees with your IP, or a UA that claims Windows while navigator.platform says Mac, is exactly what anti-fraud systems flag. The checker surfaces these contradictions before a platform does.
It gathers your WebRTC STUN candidates and flags a local-IP leak behind a proxy, the most common reason a clean-looking anti-detect profile still gets tied to your real network.
navigator.webdriver=true, a HeadlessChrome User-Agent, a missing window.chrome object, zero plugins with zero mimeTypes, or unavailable WebGL each give a browser away. The tool reports precisely which one fired.
Rather than dumping raw attributes, it scores the profile 0 to 100 and returns a plain CONSISTENT, LEAKY, or DETECTED call, so you know at a glance whether it is ready or still leaking.
Once enough samples exist, it estimates how rare your fingerprint is as 1 in N. A profile that is a statistical outlier draws attention just as fast as an obvious spoof.
Everything runs client-side. The tool keeps only hashes and the verdict, never your raw IP or User-Agent tied to an identity, so testing a profile leaves no record of it.
A browser fingerprint is the set of signals a website reads to identify your device without a cookie: User-Agent, platform, timezone, screen geometry, hardware concurrency, canvas and WebGL rendering, and more. Anti-fraud systems do not just collect these signals, they cross-check them. A fingerprint can be perfectly unique and still get you blocked, because what trips detection is contradiction, not uniqueness.
A leak is any signal that betrays the real environment behind a spoofed one. WebRTC exposing your home IP while your proxy claims another country. A timezone of America/New_York behind a German residential IP. A User-Agent claiming Windows while navigator.platform reports MacIntel. WebGL reporting your real GPU while the rest of the profile pretends to be a different machine. Modern detection stacks weigh dozens of these in parallel.
Automation adds a second category of tells: navigator.webdriver set to true, a User-Agent still carrying HeadlessChrome, a missing window.chrome object, zero plugins and zero mimeTypes, or WebGL that will not initialize. Anti-detect browsers like Multilogin, GoLogin, AdsPower, Dolphin Anty, and Incogniton exist to paper over these signals, but patch quality varies widely between tools and configs.
This checker runs the same internal-consistency and automation checks a well-tuned detection stack runs, then tells you in plain language which signals agree, which contradict, and whether the profile reads as a real human.
Configure your proxy and browser profile first, then run the checker from inside that exact session. Re-run after every fix until the verdict reads CONSISTENT.
Launch your anti-detect browser profile or automated session with its proxy already connected, then navigate to this tool inside that profile. The fingerprint is read from the session you load it in, so testing from your normal browser tells you nothing about the profile.
The tool collects all signals and runs the four leak checks and automation tells automatically. No input, no account, no download. Results appear in seconds.
Start with the verdict and believability score. CONSISTENT means signals agree. LEAKY means a real-environment signal is bleeding through. DETECTED means an automation tell fired. Then scan the per-check rows to see exactly which one failed.
Address the specific failure: route or disable WebRTC for an IP leak, align your profile timezone to your IP geo for a timezone mismatch, or match your UA to your platform for an OS mismatch. Reload the tool in the same profile and confirm the check now passes.
Once your verdict is clean, glance at the rarity estimate. A fingerprint that is far too unique is its own kind of tell. Aim for a profile that is internally consistent and not a statistical outlier.
CONSISTENT means your signals agree and no automation tells fired, so the profile reads as a plausible real device. LEAKY means a real-environment signal is bleeding through a spoof, such as a WebRTC IP leak or a timezone that does not match your IP geo. DETECTED means an automation flag fired, like navigator.webdriver=true or a HeadlessChrome UA. The 0-to-100 believability score quantifies how natural the profile looks overall.
Yes. It collects your WebRTC STUN candidates and flags a local-IP leak, the most common way an otherwise clean profile still exposes your real network behind a proxy. If WebRTC is leaking, the leak check fails and the verdict reflects it.
It checks navigator.webdriver=true, a HeadlessChrome User-Agent, a missing window.chrome object, zero plugins combined with zero mimeTypes, and WebGL being unavailable. Any one of these signals an automated rather than human-driven browser, and the tool reports which ones fired.
Yes. Open the tool inside the profile you want to test with its proxy connected, and it reads whatever fingerprint that profile presents. It is built to audit these anti-detect browsers and tell you whether the spoof holds together or leaks. Re-run it after each change to confirm fixes.
It estimates how many other profiles share your exact fingerprint, shown as 1 in N once enough samples have been collected. A fingerprint that is too unique stands out to fraud systems as much as an obvious spoof, so the goal is a profile that is both internally consistent and not a statistical outlier.
No. Everything runs in your browser, and the tool keeps only hashes and the verdict, never your raw IP or User-Agent tied to an identity. Testing a profile does not create another identifiable record of it.
Different checkers weight different signals. This one focuses on internal consistency, comparing UA against platform, timezone against IP geo, and WebGL against the claimed device, plus automation tells. A profile can have individually plausible attributes and still fail because two of them contradict each other, which is exactly what real anti-fraud stacks catch.
Yes. Load the tool from inside your automated session and it reports automation tells like navigator.webdriver, a HeadlessChrome UA, missing window.chrome, empty plugin and mimeType lists, and unavailable WebGL. It is a fast way for scraping and automation engineers to see which signal gives a headless browser away.
The verdict you see here is also a plain HTTP endpoint. Collect the fingerprint signals in the browser,
POST them as JSON, and get back the verdict, score,
per-check leaks, automation tells, and rarity. No key required (rate limited to 200 requests per day per IP).
curl -X POST https://seojuice.com/tools/browser-fingerprint/analyze/ \
-H "Content-Type: application/json" \
-d '{
"user_agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) ...",
"platform": "Win32",
"timezone": "America/New_York",
"languages": ["en-US", "en"],
"screen_resolution": "1920x1080",
"webgl_vendor": "Google Inc.",
"webgl_renderer": "ANGLE (NVIDIA ...)",
"canvas_hash": "data:image/png;base64,...",
"webrtc_candidates": ["192.168.1.10"]
}'{
"fingerprint_hash": "cceed609b318...",
"verdict": "LEAKY",
"verdict_word": "LEAKY",
"score": 79,
"leaks": [
{ "check": "ua_platform_mismatch", "status": "passed", "detail": "UA and platform agree." },
{ "check": "webrtc_ip_leak", "status": "fired", "detail": "Real IP(s) leaked behind proxy: ..." }
],
"tells": ["navigator.webdriver=true"],
"rarity": { "count": 2, "total": 1840, "one_in": 920, "enough_data": true }
}
Only hashes and the verdict are persisted. Your raw IP and User-Agent are never stored against an identity.
verdict is one of CONSISTENT,
LEAKY, or DETECTED.