10 Browser Fingerprinting Tools for Testing

A browser fingerprint isn't a score. It's a stack of signals that answer different questions about the same session. Browser APIs expose Canvas, WebGL, WebGPU, fonts, audio, screen geometry, locale, and navigator properties. Automation tests inspect webdriver behavior, permissions, plugins, iframes, and timing. Network measurements examine IP, WebRTC, TLS, HTTP/2, and sometimes JA3 or JA4 characteristics.

That distinction matters because a browser can pass one test while contradicting itself elsewhere. A user agent may claim Windows while WebGL reveals another environment. The main thread may return one value while a worker or iframe returns another. A timezone can disagree with the exit IP, and a JavaScript-level patch won't necessarily change the underlying network stack.

The browser fingerprinting tools below are organized by diagnostic job, not by a feature checklist. They help with device identity, privacy exposure, browser-side consistency, automation detection, network leaks, and production identification. Clearcote is the comparison point for engine-level controls, seeded repeatability, and plain-English coherence checks, not a universal replacement for every diagnostic.

Table of Contents

• 1. Clearcote Labs
  • Where Clearcote fits
• 2. Fingerprint
  • What it reveals
• 3. FingerprintJS
  • Good for experiments, not certification
• 4. AmIUnique
  • Use the result as population context
• 5. EFF Cover Your Tracks
  • A good first privacy conversation
• 6. CreepJS
  • Read contradictions, not just scores
• 7. BrowserLeaks
  • Use it to isolate the failing layer
• 8. PixelScan
  • Don't confuse a visual scan with production behavior
• 9. SannySoft Bot Detection Test
  • What SannySoft cannot see
• 10. Device Info
  • A practical disclosure snapshot
• Top 10 Browser Fingerprinting Tools, Feature Comparison
• Choose the Test That Answers Your Question

1. Clearcote Labs

Clearcote Labs tests browser identity at the engine level instead of adding JavaScript patches after Chromium has exposed its behavior. It is an open-source, de-Googled Chromium fork with controls in browser-engine paths, allowing comparisons across the main thread, workers, and iframes.

Its identity controls cover Canvas, WebGL, WebGPU, AudioContext, fonts, locale, WebRTC, user-agent client hints, TLS, and HTTP/2 behavior. Seeded identities make tests repeatable, while captured device profiles provide realistic personas for QA and research. The diagnostic value comes from checking whether one claimed device stays coherent across browser realms and protocol layers.

Practical rule: A passing Canvas result does not prove that the browser has a consistent identity. Compare surrounding signals and repeat the same profile across separate sessions.

Clearcote works with Playwright and Puppeteer and provides SDKs for Python, Node.js, and .NET. Teams can run it locally on Windows or Linux, in Docker, through CDP, or with an MCP server for tools such as Claude Desktop, Cursor, and Cline. The Profile Manager and persistent identities reduce setup work for repeatable QA cases.

Where Clearcote fits

The open build is reproducible, checksummed, and GPG-signed under a BSD-3 license. A licensed build is free for one concurrent browser with a qualifying GitHub sign-in. Pro is listed at $49 per month or $441 per year, with a 30-day option at $49. Hosted browsers include residential IPs and geo matching, with advertised traffic billing of approximately €1 per GB and prepaid sessions from €5. Verify current terms before planning a fleet.

The trade-off is source visibility. The licensed build includes unpublished work, so it cannot be reproduced from public source in the same way as the open build. macOS support is not currently available, and higher concurrency requires Pro or hosted traffic billing.

Clearcote fits testing that requires repeatable, engine-level identity coherence. It does not replace a focused privacy audit, bot test, or production identification service. A result that passes one of those tools can still conflict with values exposed in another browser realm or network layer, which is why coherence checks should be interpreted across the full session.

2. Fingerprint

Fingerprint is designed for the opposite side of the problem. Instead of helping a team shape or inspect a browser identity, it provides application-level device identification for fraud prevention, account security, and bot-risk workflows.

Its JavaScript and native SDKs collect signals and send them to a hosted identification service. The resulting records can include stable device IDs, confidence information, event histories, risk indicators, bot signals, webhooks, and dashboard views. That makes Fingerprint suitable for a product team deciding whether a login, account action, or transaction resembles activity from a known device.

The evidence it provides is operational rather than explanatory. You can use it to connect events and feed a risk decision, but it won't give you the same low-level debugging experience as CreepJS or BrowserLeaks. It also won't tell you whether your own Playwright profile has matching values in an iframe and worker unless you build that test around the application flow.

What it reveals

Fingerprint has mature integration paths and documentation, which reduces the work required to add device recognition to an authentication or fraud system. The hosted model is also useful when your team doesn't want to maintain collection infrastructure, event pipelines, and analysis dashboards.

The costs and constraints are different from an open diagnostic page. It's a paid SaaS product, its backend is closed source, and teams handling sensitive identity data may need to review data residency, retention, and compliance requirements. A stable ID also shouldn't be interpreted as proof that every underlying signal is truthful. It represents the provider's identification output, not an independent audit of browser coherence.

For a lower-level explanation of the signals involved, compare the platform's output with this browser fingerprint documentation. Use Fingerprint when the job is production identification inside your application, not when the job is proving that a browser persona is internally consistent.

3. FingerprintJS

FingerprintJS is the accessible starting point for teams that want to calculate a browser fingerprint in the client without adopting a hosted identification service. The open-source JavaScript library gathers common browser signals and returns a hash, making it useful for demonstrations, learning, research, and internal proofs of concept.

That simplicity is its main strength. Engineers can inspect the code, run a trial quickly, and see how changes to browser settings affect the resulting value. It gives a concrete way to understand the relationship between exposed attributes and an identifier, rather than treating fingerprinting as a mysterious vendor score.

The evidence stops at the client-side collection layer. A hash can show that two observations differ, but it doesn't automatically establish that the underlying device changed, that a user is fraudulent, or that the identifier will remain linkable over time. Persistence, evasion, storage, server-side correlation, and changing browser populations all require additional engineering.

Good for experiments, not certification

FingerprintJS is MIT-licensed and inspectable, which makes it a practical choice for a classroom exercise or a small internal tool. It isn't a drop-in equivalent to the commercial Fingerprint service's broader production capabilities, and teams shouldn't assume that a freely computed hash offers the same stability or accuracy.

It also won't solve contradictions for you. If a profile claims one locale in JavaScript but sends another language header, the library may collect both values without deciding whether the combination is plausible. For that reason, pair it with a deeper consistency test and document which signals your experiment includes.

A useful companion is this anatomy of a browser fingerprint, especially when you need to explain why a client-side identifier is only one diagnostic view. Choose FingerprintJS when you need inspectable collection and fast experimentation, not a complete anti-fraud decision system.

4. AmIUnique

AmIUnique is built around a research question: how distinctive does this browser appear compared with a public corpus? It captures browser attributes and presents an estimate of uniqueness, along with explanations of which properties contribute to the result.

That makes it valuable for privacy research and education. A reader can see that uniqueness is assembled from a combination of attributes rather than one magic identifier. A researcher can compare configurations and investigate whether a font set, screen geometry, locale, or rendering behavior makes a browser stand out.

The most important interpretation rule is that uniqueness isn't the same as linkability. A browser may look unusual in a population without being reliably recognized across changing sessions. Conversely, a less unique configuration can still be connected through account activity, IP history, storage, or other signals that this test doesn't measure.

Use the result as population context

AmIUnique offers open-source SDKs and public developer documentation, so it works well as a measurement resource rather than a production fraud product. It won't replace a commercial device-identification service, and it doesn't attempt to give an automation verdict comparable to SannySoft.

Its historical value also needs careful handling. Browser populations change, privacy protections evolve, and the attributes available to a page aren't fixed. A result should therefore be treated as a snapshot of how the current browser appears to the service, not as a permanent statement about the device.

Run it before and after a privacy setting change, then compare the individual attributes instead of chasing a lower uniqueness label. If your question is “how distinctive does this browser look?”, AmIUnique is a strong fit. If your question is “can my application recognize this returning device?”, use a production identification system and validate that workflow separately.

5. EFF Cover Your Tracks

EFF Cover Your Tracks, formerly Panopticlick, turns a complicated privacy audit into a report that non-specialists can read. It explains what tracking protection the browser provides and whether the fingerprint appears unique, nearly unique, or randomized within the test's model.

Its value is communication. A privacy team can use the report to show how headers and JavaScript-accessible signals contribute to exposure without asking every stakeholder to interpret raw Canvas, WebGL, or permission data. The Electronic Frontier Foundation's earlier foundational work measured at least 18.1 bits of entropy in browser fingerprints and estimated that a randomly selected browser would match only 1 in 286,777 others in that sample, while 94.2% of browsers with Flash or Java were unique. Those historical findings are documented in the ACM study on browser fingerprinting, and they should be read as evidence from a particular sample, not a universal current rate.

Cover Your Tracks doesn't inspect every tracking method. It isn't a synthetic bot detector, a TLS laboratory, or a production identity API. A browser can receive a reassuring privacy result and still expose a contradiction that a fraud system notices.

A good first privacy conversation

Use the report to establish a baseline, then move to lower-level tools when you need to understand a specific leak. It works particularly well for comparing ordinary browser settings, privacy extensions, and hardened configurations from a user's perspective.

The result also shouldn't be confused with anonymity. Reducing fingerprint uniqueness can make a browser blend into a larger population, but it doesn't remove account identifiers, network information, or behavioral signals. That distinction keeps the tool useful without overstating what it proves.

For an engine-level comparison, see this Cover Your Tracks fingerprint test guide. Choose EFF's test when the diagnostic job is human-readable privacy exposure, not automation certification.

6. CreepJS

CreepJS is the tool to reach for when a simple pass or fail isn't enough. Its test page examines a broad collection of browser attributes, including Canvas, WebGL, audio, fonts, internationalization, storage, permissions, timing, and other exposed behavior. It also attempts to identify signals that appear to be lying or inconsistent.

That depth makes CreepJS useful for testing anti-fingerprinting setups and browser profiles. A user-agent change that looks fine in a basic check may sit beside a conflicting platform value, an unusual renderer, or a permission response that doesn't fit the claimed environment. CreepJS helps expose those relationships, although it still observes the browser from page JavaScript and can't certify what a server sees before the page loads.

The output can be overwhelming. Treat each finding as a lead, not a verdict. A “lie” indicator may mean that a value differs from another exposed value, not that the browser is automatically blocked by every production system.

Read contradictions, not just scores

CreepJS is especially helpful when you record a baseline, change one configuration, and rerun the test. Keep the profile, browser version, network route, and permissions controlled so you can identify which change caused the difference. Then compare the result with BrowserLeaks for focused network and protocol checks.

Independent benchmark data illustrates why this layered reading matters. In a 2024 anti-detect browser evaluation, CreepJS and BrowserScan results ranged from 139/260 for Incogniton to 223/260 for GoLogin, while a real Mac scored 226/260. The benchmark assessed cross-signal coherence across Canvas, WebGL, AudioContext, WebRTC, fonts, screen geometry, navigator properties, and other markers, rather than measuring one field. See the browser fingerprinting benchmark explanation for the stated scope and limitations.

CreepJS is best for deep browser-side diagnosis. It isn't a production identity provider, and a high result doesn't prove that TLS, IP reputation, or behavioral analysis will agree.

7. BrowserLeaks

BrowserLeaks is a toolbox rather than a single opinion. It offers focused checks for IP and DNS exposure, WebRTC, Canvas, WebGL, audio, fonts, locale, timezone, and TLS fingerprint utilities such as JA3 and JA4.

That structure is useful during debugging. Instead of receiving one aggregate label, you can isolate the layer that changed. If WebRTC reveals a route you didn't expect, the WebRTC test is more actionable than a general privacy score. If the browser's timezone and language don't fit the intended network location, the locale and timezone pages show the mismatch directly.

The same granularity creates work. BrowserLeaks doesn't make the final judgment for you, and its utilitarian interface assumes that you understand what each field means. A clean JavaScript result won't prove that the transport connection resembles the claimed browser, while a distinctive TLS result won't tell you whether the page's Canvas and font values are coherent.

A network-consistent browser can still be browser-inconsistent, and a browser-consistent session can still leak through its network path.

Use it to isolate the failing layer

Start with the network tests when a session is routed through a proxy or hosted browser. Check the visible IP, DNS behavior, WebRTC candidates, timezone, and language. Then inspect browser-side values and compare the TLS result with the browser version you intend to present.

Browser fingerprinting has become common enough that isolated testing can miss real exposure. A large-scale study identified 117,012 distinct fingerprinting URLs, with 8% of reached links classified as browser fingerprinting and 92% classified as non-fingerprinting, according to the ICIMP fingerprinting analysis. The figures describe the study's reached links, not every page on the web, but they support testing against real production sites rather than relying only on a synthetic page.

BrowserLeaks is the right choice for focused leak and protocol diagnosis. It won't replace a browser-wide coherence analysis or a production risk engine.

8. PixelScan

PixelScan is a fast visual sanity check for browser profiles and anti-detection configurations. It examines Canvas, WebGL, headers, and related signals, then highlights irregular relationships that may deserve investigation.

Its speed is the main practical benefit. An engineer can load a profile, review the scan, make a configuration change, and repeat the test without building a collection harness. It has also become a familiar reference point in stealth and bot-detection discussions, and its bounty program encourages reports of new detection proofs of concept.

The scan is deliberately more compact than CreepJS. That makes it easier to use during iteration, but terse findings often need a second test to explain the cause. A flagged profile isn't automatically invalid, and a clean result isn't proof that a stricter system will accept it.

Don't confuse a visual scan with production behavior

PixelScan is useful for catching obvious mismatches between declared and observed attributes. It can reveal that a profile's Canvas, WebGL, or headers don't form a convincing combination, particularly after a partial spoof or browser configuration change.

Its evidence stops at the signals the page can collect and the heuristics the service chooses to apply. It doesn't provide the same application-level device identity as Fingerprint, and public information about paid tiers or APIs is limited. Use it as a quick regression test, then confirm important findings in CreepJS, BrowserLeaks, SannySoft, or an authorized production-like environment.

The strongest workflow is comparative. Run the same profile with the same network route before and after a change, save the output, and investigate only the fields that moved. PixelScan is best for rapid profile triage, not for declaring a browser invisible or universally trusted.

9. SannySoft Bot Detection Test

SannySoft Bot Detection Test answers a narrower question than most tools in this list: does this browser expose familiar automation and headless indicators? Its client-side page presents pass or fail checks for webdriver, plugins and MIME types, permissions behavior, Chrome objects, iframe behavior, and related DOM signals.

That makes it a useful smoke test for Playwright, Puppeteer, and similar automation setups. It requires no account, loads quickly, and gives an engineer an immediate view of whether basic stealth changes altered the obvious markers. It also works well in CI as an early diagnostic, provided the team treats the result as a test fixture rather than a security boundary.

What SannySoft cannot see

SannySoft is client-side. It doesn't score IP or ASN risk, inspect the full network path, or model how a production anti-fraud system correlates sessions over time. It also doesn't prove that a browser's locale, GPU, WebRTC, TLS, and HTTP/2 characteristics agree with one another.

A clean table therefore means only that the tested page didn't flag those particular checks. A failed check doesn't explain whether the cause is a browser launch mode, a missing plugin, a permission implementation, or a deeper engine mismatch. Pair the page with CreepJS for browser-side contradictions and BrowserLeaks for network and protocol evidence.

Use SannySoft when you need a fast automation smoke test before authorized QA against your own application. Security testing teams can also consult AskYourQA security testing for broader testing context, but no diagnostic page should be treated as a substitute for testing the actual controls in the system you own.

10. Device Info

Device Info puts a large set of browser disclosures on one page. It can show the user agent and UA-CH values, WebGL renderer, GPU information, CPU cores, memory, timezone, locale, media devices, and other attributes that pages may be able to observe.

This is particularly useful when someone has spoofed only one layer. Changing the user agent can create the appearance of a different operating system, but WebGL, GPU, screen geometry, language, or media-device behavior may still expose the underlying environment. Device Info makes those gaps visible without requiring a specialist to move through many separate test pages.

Its limitation is equally clear. It doesn't produce an aggregate uniqueness or trackability score, and it isn't focused on automation indicators in the way SannySoft is. It also doesn't tell you how a server will combine these values with IP reputation, TLS, session history, or behavior.

A practical disclosure snapshot

Use Device Info at the beginning of a test, after changing a profile, and after changing the network route. Record the values that should remain stable, then identify fields that move unexpectedly. Pay special attention to the relationship between user agent, UA-CH, platform, renderer, timezone, language, and media capabilities.

Treat “true” OS or engine hints cautiously. They can expose gaps in a spoofing setup, but no single field should be promoted to ground truth in every browser and operating system. The page is most valuable as a quick disclosure inventory, especially before a deeper CreepJS or BrowserLeaks investigation.

Top 10 Browser Fingerprinting Tools, Feature Comparison

Choose the Test That Answers Your Question

Start with the diagnostic job, not the tool's popularity. If you need to see what a browser exposes, use Device Info for a broad inventory and BrowserLeaks for focused IP, DNS, WebRTC, locale, timezone, and TLS checks. Those tools show the ingredients, but they won't decide whether the complete identity is plausible.

For contradictions and automation indicators, use CreepJS, PixelScan, and SannySoft together. CreepJS gives the deepest browser-side view, including lie and consistency signals. PixelScan is faster for profile triage and repeated comparisons. SannySoft is a focused smoke test for familiar headless and automation markers. A pass on SannySoft doesn't validate the network layer, and a clean PixelScan result doesn't prove that workers and iframes agree.

Interpretation rule: A result is evidence about the layer it measures. It isn't a certificate for the entire browser identity.

AmIUnique and Cover Your Tracks serve privacy and uniqueness questions. AmIUnique helps explain how distinctive a browser appears within a research corpus. Cover Your Tracks gives a more approachable account of tracking protection and fingerprint exposure. Neither should be used as a production fraud verdict, and neither removes the need to consider accounts, network information, storage, or behavior.

Use Fingerprint when the goal is application-level identification. It can support account security, fraud workflows, event analysis, and risk decisions. Use FingerprintJS when you need an open-source client-side implementation for learning, internal experiments, or a proof of concept. Neither tool, by itself, proves that an automated browser profile is coherent across every realm and protocol.

Evaluate Clearcote when the requirement is repeatable, engine-level identity control for authorized QA, research, or lawful automation. Its seeded identities, captured profiles, Playwright and Puppeteer integrations, CDP and Docker options, and coherence-focused testing address a problem that page-level patches often leave unresolved. The right comparison is not whether Clearcote produces the most attractive score. It's whether the same claimed persona remains consistent when the test moves from the main thread to workers and iframes, from JavaScript to WebRTC, and from browser APIs to TLS and HTTP/2.

Rerun every test after a meaningful change. Keep the browser version, profile seed, permissions, extensions, viewport, and network route documented. Compare main-thread values with workers and iframes, check locale and WebRTC against the intended exit location, and inspect protocol signals separately from page JavaScript. Production sites can activate fingerprinting only after authentication or user interaction, so crawl-only testing can miss exposure. A 2025 user study of 30 participants over 10 weeks found that crawlers missed 45% of fingerprinting websites encountered during real browsing because they couldn't access protected pages, bypass bot detection, or trigger interaction-dependent scripts, as reported in this real-world fingerprinting measurement study.

Finally, don't rely only on source-code detection. A 2025 study found that translating real JavaScript fingerprinting scripts into WebAssembly-obfuscated variants caused academic detectors using source features to lose up to 33 percentage points of recall, while browser extensions and built-in protections remained effective because API interception didn't depend on the script language, according to this analysis of obfuscated fingerprinting. That difference reinforces the central lesson: test the signals and the browser behavior, not just the script text.

Clearcote Labs provides an open-source, de-Googled Chromium fork with engine-level fingerprint and identity controls, seeded profiles, Playwright and Puppeteer SDKs, Docker and CDP support, and hosted browser options with residential IPs. If you need repeatable browser personas and cross-realm coherence checks for authorized QA, research, or automation, visit Clearcote Labs to evaluate the browser and integration options.