What is a browser fingerprint

Browser fingerprinting is a collection of unique characteristics of your device and browser settings that allows it to be identified online. It is formed from information automatically transmitted each time a site is accessed (HTTP headers and JavaScript parameters) and remains nearly unchanged even after deleting cookies or enabling private mode. Usually, a combination of parameters such as operating system, browser type and version, interface language, time zone, screen resolution, installed fonts, and extensions forms an almost unique profile for each user. In practice, although millions of people use Chrome, it’s nearly impossible to find two users with identical browser versions, plugin lists, fonts, and display settings.

Browser fingerprinting is like a fingerprint: an invisible set of parameters that remains stable between sessions. Even after clearing cookies or using private mode, the browser can still send this information to the server, making the fingerprint a powerful tracking tool. A combination of data such as operating system, language, time zone, screen resolution, installed fonts, and others creates a nearly unique profile for each user.

Key Components of a Browser Fingerprint

The most important parameters included in a browser fingerprint are:

• IP address and geolocation: The IP address is a key component of the fingerprint and acts as a unique identifier of the device. Websites use it to determine the user’s country, region, and city (like a digital mailing address). Using proxy servers allows this information to be masked.
• User-Agent: A string (textual information) sent by the web browser or another client (such as a script or application) to the server when requesting a web page. This string contains data about: the device type (e.g., computer, smartphone); the operating system (Windows, Android, iOS, etc.); and the browser or client version and name (Chrome, Firefox, Safari, curl, etc.).
• Browser language (Accept-Language) and time zone: Reflect the user’s system settings. These values are also sent to the server and can be analyzed.
• Screen resolution and color depth: The browser transmits screen resolution and display settings, which are part of the fingerprint. Even differences in color depth or screen orientation create variations.
• Installed fonts and plugins/extensions: The list of available fonts and applications in the browser (e.g., Adobe Flash, Java, PDF viewer) varies significantly between users. A combination of rare fonts or non-standard extensions makes your fingerprint even more unique.
• Canvas (Canvas fingerprinting): Many websites draw a hidden image on an HTML5 <canvas> and compare pixel content. Due to differences in graphics cards and fonts, different devices render slightly different images.
• WebGL: Similar to Canvas, WebGL renders 3D graphics. The result depends on the hardware and video card driver, creating a unique GPU “signature.”
• Audio: Browsers can generate an inaudible sound using the Web Audio API. Differences in processor audio architecture cause slight variations in the output, which is used as an audio fingerprint.
• Other characteristics: Available APIs (WebRTC IP, list of accessible media devices), network configuration, local variables (running scripts, etc.)—all contribute additional entropy to the fingerprint.

Together, these components almost certainly make each user unique: studies show that over 90–99% of browsers online have a unique fingerprint. So even millions of Chrome users usually have different parameter combinations.

Technologies and Trackers Using Fingerprinting

Special libraries and techniques are used to collect and analyze fingerprints. The most popular include:

• FingerprintJS: An open-source JavaScript library (including Fingerprint Pro) that automatically collects browser characteristics (OS, screen, fonts, hardware parameters, etc.) and forms a hash identifier – the “fingerprint ID.” It is widely used in anti-fraud and analytics systems.
• Canvas/WebGL/Audio fingerprinting: As mentioned, many websites deliberately render hidden images on Canvas or scenes on WebGL, as well as generate sound via AudioContext to measure differences in results. These techniques gather additional unique data about the device.
• Client Hints: A new HTTP header standard that allows browsers (mostly Chrome, Firefox, etc.) to send information about themselves to websites in a more controlled manner. Using headers like Accept-CH and Sec-CH-UA, sites can request detailed data (browser version, OS, screen size, etc.) in a more private format. However, these hints still provide a set of variables that can be used for fingerprinting.
• Tracking scripts: Many ad networks, analytics systems, and anti-fraud platforms embed scripts on websites that collect the mentioned data and send it to a server. For example, cross-site connections (retargeting, cloud analytics) can identify a single user across different domains using the fingerprint.

Thus, websites and trackers combine this information to create a “digital profile” of the visitor and recognize them during future visits. Combined with hashing algorithms and databases, this enables identifying users without any cookies. This approach is used not only for advertising and analytics but also for fraud prevention and avoiding multiple registrations.

Using Fingerprinting for Tracking

The collected data is used to identify and monitor users. In effect, the fingerprint becomes a persistent identifier: when the browser sends all these parameters, the server hashes them into a single code under which the user is recognized in the future. Even if you clear all cookies or visit from another site, a new visit with the same parameter set will “reveal” you as the same user.

This is especially useful for advertisers and analysts — it enables end-to-end analytics and more precise ad targeting to specific individuals. At the same time, security and anti-tracking systems also use device fingerprinting for protection: for example, to detect suspicious activity, verify login attempts, or perform identity verification on crypto exchanges.

Most modern websites — from social networks to online stores — use fingerprints as one of their security elements. This helps identify multiple accounts created from the same device or detect inconsistencies in settings, which may indicate abuse. For example, crypto exchanges often analyze users’ anonymity levels, and if the system detects multiple accounts linked to the same fingerprint, they may be blocked.

Why This Matters for Multi-Accounting and Parsing

Multi-accounting — managing many user accounts — and data parsing often require avoiding detection. Platforms like social networks, marketplaces, or email services typically disapprove of creating multiple accounts from a single device, so they pay close attention to browser fingerprints. If multiple accounts regularly log in with the same parameters — IP address, language, screen resolution, etc. — the system identifies them as the same device and may suspect fraud. This can result in account blocks, additional checks (SMS, CAPTCHA), or even complete access bans.

That’s why marketers and SMM specialists managing multiple profiles (such as running several pages or ad accounts) try to make each account appear as a separate user. This requires fingerprint masking — each browser profile must have unique parameters. Antidetect browsers and proxies are used for such tasks. For example, specialized browsers allow changing dozens of technical characteristics (such as Canvas, WebGL, time zone), making one computer appear as many different devices. The same approach is used by arbitrageurs and ad bots — they combine proxies and virtual profiles to confuse protection systems.

Parsers face a similar issue: if a script sends many identical requests with the same fingerprints, the site easily detects it and blocks access. To remain unnoticed, proxies and modified profiles are used, distributing requests across different IP addresses and configurations.

Fingerprint Masking Techniques

To confuse trackers and reduce the risk of detection, the following methods are used:

• Antidetect browsers and virtual profiles: Specialized browsers allow the creation of completely isolated profiles. Each profile emulates a different device with its own settings — a different OS, list of fonts, extensions, etc. This essentially allows you to “switch shoes” for each account.
• Extensions and blockers: For example, Canvas Fingerprint Defender (for Chrome/Firefox) adds randomized noise to the Canvas fingerprint, replacing your real one with a random value. Other protective extensions (Privacy Badger, uBlock Origin, NoScript, etc.) block or filter scripts collecting data. Example: such tools can disable font list collection or turn off JavaScript execution — this reduces the available information, though it may break site functionality.
• Header modification: By changing headers like User-Agent, Accept-Language, or geographic data, you can spoof basic fingerprint components. There are plugins like “User-Agent Switcher” and even built-in browser features for this.
• Proxies and VPNs: Replacing your real IP with a proxy/VPN changes the “network” part of the fingerprint. This is one of the most effective ways to hide your actual location.

Each of these approaches provides a partial effect. The most effective method is combining them — for example, proxy + antidetect browser, or script blocker + different User-Agent for each profile.

The Role of Proxies in Fingerprint Formation

Proxy servers significantly affect the browser fingerprint by altering network parameters:

• IP address: Your real IP is replaced by the proxy IP. This changes your geolocation and reduces links between your sessions. Proxies literally allow you to bypass geo-blocks — the site will see the proxy IP as yours.
• Proxy type: Residential proxies appear the most natural — they look like regular users from their homes. They are much harder to distinguish from real users.
• Proxy anonymity: For additional security, it’s recommended to use high-anonymity proxies (Elite proxy).
• Geo-dependencies: It’s important to align the proxy location with other data. For example, if the browser is set to Ukrainian and Kyiv time, but the proxy is from the US — it will stand out. Therefore, proxies from the appropriate region are usually selected to match the fingerprint, minimizing detection risk.

By using proxies, you change one of the key components of a fingerprint — the IP address. Combined with an antidetect browser, this adds another level of protection. If each profile connects using a unique IP, tracking them all to a single device becomes nearly impossible.

Proper Proxy and Antidetect Browser Integration

To truly minimize tracking risks, proxies should be selected and configured together with antidetect browsers or modified environments so that all parameters match:

• Assign each virtual profile its own unique proxy. Don’t reuse the same IP for multiple accounts — otherwise, the system will easily link them.
• Select proxies based on region and device type. For example, if the profile simulates a user from Ukraine, use a Ukrainian residential proxy and set the browser language to Ukrainian. This way, “region,” “language,” and “IP address” will be consistent.
• Use static proxies (with fixed IP) for permanent accounts.

A browser’s digital fingerprint is a powerful tracking tool made up of many device parameters. To protect against tracking (especially in multi-accounting and parsing scenarios), masking methods are used: antidetect browsers, specialized extensions, and proxies. Combining these with a reliable proxy service minimizes risks and significantly increases user anonymity.

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