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Are There Legitimate Uses for Browser Fingerprinting?

Edward Tsinovoi
Cybersecurity
March 12, 2025

Yes, there are legitimate uses for browser fingerprinting. While it's often associated with invasive tracking, browser fingerprinting serves important purposes in fraud prevention, security enhancement, bot detection, and improving user experience when implemented ethically and transparently.

Legitimate Uses:

  • Security
  • Fraud prevention
  • Authentication
  • Fair-use enforcement

Unlike cookies, which users can clear or block, browser fingerprints are harder to evade, making them useful for security applications.

1. Fraud Prevention & Account Security

Fraudsters often attempt to bypass traditional security mechanisms using stolen credentials, session hijacking, or automated scripts. Browser fingerprinting helps identify suspicious login behavior, detect account takeovers, and prevent fraud by looking at device and browser consistency.

Account Takeover Detection (ATO)

When you log into a bank or e-commerce site, it records a fingerprint of your device and browser. If someone logs in with your username and password but their fingerprint differs significantly from past logins, the system flags it as an account takeover attempt.

What the system checks for:

  • Is the browser the same? (Chrome 120 vs. Safari 17)
  • Is the OS the same? (Windows 11 vs. macOS Ventura)
  • Has the screen resolution changed? (1920x1080 vs. 1366x768)
  • Are the installed fonts different?
  • Is the WebGL fingerprint different? (indicating a new GPU or virtual machine)

Session Hijacking Protection

Attackers steal authentication cookies to bypass login credentials, but browser fingerprinting helps counter this. If a session suddenly moves to a different fingerprint (e.g., new device, altered browser settings), the system can:

  • Invalidate the session (force logout).
  • Ask for 2FA verification (e.g., email, SMS).
  • Display an anomaly warning to the user (like Gmail does when it detects unusual activity).

Example: A hacker steals session cookies using a man-in-the-middle attack and logs into your email account. If the hacker’s fingerprint is completely different from your usual one, the service can block access or request a password re-entry.

Preventing Credential Stuffing

  • Attackers use databases of leaked username-password pairs to log into multiple accounts (e.g., using automated tools like Sentry MBA or OpenBullet).
  • Since these bot-driven attacks often use headless browsers, their fingerprints are often incomplete or generic.
  • A website can block requests from browsers with missing fingerprinting elements, helping prevent credential stuffing attacks.

2. Payment & Transaction Fraud Prevention

Browser fingerprinting is a core part of fraud prevention in e-commerce, banking, and fintech services.

Detecting Stolen Credit Cards

Credit card fraud detection systems track fingerprint consistency across transactions.

Fraud detection pattern:

  1. User logs in with a consistent fingerprint and makes multiple purchases.
  2. A new fingerprint (different browser, device, or OS) attempts a high-value transaction.
  3. The system triggers an extra verification step or blocks the transaction.

This is useful because fraudsters often buy stolen credit cards in bulk and attempt transactions from devices different from the cardholder's usual setup.

Detecting Chargeback Fraud

Some users make purchases, then file chargebacks, falsely claiming they never made the purchase.

How fingerprinting prevents this:

  • A user buys something from Device A (recorded fingerprint).
  • Later, they file a chargeback claiming they never made the purchase.
  • The fingerprint data proves the transaction was made from the same browser and system the user regularly uses.

Many businesses use this technique to fight “friendly fraud,” where real customers abuse chargeback policies.

3. Anti-Bot & Anti-Scraping Measures

Bots attempt to automate actions on websites (e.g., ticket scalping, web scraping, brute-force attacks). Browser fingerprinting helps differentiate bots from human users.

Preventing Automated Web Scraping

  • Scraping tools like Scrapy, Selenium, and Puppeteer often use headless browsers, which have incomplete or generic fingerprints.
  • Some scripts modify browser settings to appear human-like, but fingerprinting still detects inconsistencies (e.g., mismatched user agent and rendering engine).
  • Websites can deny access to requests with suspicious fingerprints.

Example:

  • A news website wants to prevent a competitor from scraping its articles.
  • The competitor’s scraper mimics real users, but it has an abnormal fingerprint (no installed fonts, no WebGL data, missing navigator properties).
  • The website blocks access based on these inconsistencies.

Ticket Scalping & Fake Orders

  • Bots buy up high-demand items (e.g., concert tickets, PS5s) to resell at inflated prices.
  • They often switch IPs (via proxies) but can’t easily change their browser fingerprint.
  • Websites use fingerprinting to detect repeated bot-like purchases and block them.

Preventing CAPTCHA Workarounds

  • CAPTCHA solvers use browser automation to bypass security checks.
  • Fingerprinting helps detect headless Chrome/Firefox instances used for CAPTCHA solving.

4. Multi-Factor Authentication (MFA) & Passive Authentication

Browser fingerprinting is increasingly being used as a silent authentication factor to improve security while reducing user friction. Unlike traditional MFA (which requires users to manually enter codes or approve logins), fingerprinting allows for passive authentication, where security checks happen in the background.

Enhancing 2FA Without Extra Hassle

Two-factor authentication (2FA) adds a layer of security, but users often find it annoying. Fingerprinting allows a site to decide when 2FA is actually necessary, reducing unnecessary verification requests.

How it works:

  1. You log into your online banking account.
  2. The system checks your fingerprint (device type, browser, installed fonts, etc.).
  3. If everything matches previous logins, you’re logged in without additional verification.
  4. If something seems off (e.g., a different browser, OS, or GPU), the system triggers a 2FA prompt.

This reduces friction for users who frequently log in from the same device while still blocking unauthorized access.

Example:

  • A bank uses fingerprinting to detect if you're logging in from your usual device.
  • If your fingerprint is consistent, the bank skips the SMS verification step.
  • If your fingerprint is different (e.g., new browser, new system fonts), it requires an additional code before granting access.

This is commonly used by Google, Apple, and Microsoft, allowing users to log in smoothly unless an anomaly is detected.

Browser Fingerprinting as a Security Factor in Passwordless Authentication

As companies move towards passwordless login, fingerprinting plays a crucial role in verifying users.

  1. Biometrics + Fingerprinting → Some systems combine biometric authentication (Face ID, Windows Hello, fingerprint scanners) with browser fingerprinting to verify the same user.
  2. Passwordless email magic links → Many services (like Slack, Notion) send login links to your email. If the fingerprint doesn’t match past logins, the link may expire immediately or require additional verification.
  3. WebAuthn / Passkeys → New authentication standards (like WebAuthn) use browser fingerprinting as part of the verification process, ensuring that login requests come from an expected device.

Example:

  • You log into your workplace portal with Face ID on a Mac.
  • The system also checks your browser fingerprint to confirm it's the same browser & environment you typically use.
  • If your fingerprint doesn’t match, the login fails—even if Face ID was successfully used.

This approach is gaining traction with companies like Google, Apple, and enterprise authentication providers (Okta, Duo Security).

5. Preventing Multiple Accounts & Abuse

One of the strongest non-security applications of browser fingerprinting is enforcing fair-use policies by preventing people from creating multiple accounts to abuse free trials, manipulate online votes, or evade bans.

Stopping Free Trial Abuse

Many subscription-based services (like streaming platforms, SaaS tools, and AI services) offer free trials but restrict users from signing up multiple times.

How fingerprinting stops free trial abuse:

  • A user signs up for a free trial using an email.
  • They later clear cookies, use a different email, or change their IP (via VPN) to get another free trial.
  • The site detects that their browser fingerprint matches a previously used one.
  • The site blocks or limits the new signup, preventing abuse.

Example:

  • An AI writing tool offers a 7-day free trial.
  • A user creates multiple accounts using different emails to keep using the tool for free.
  • The system detects that all accounts are coming from the same fingerprint and blocks further signups.

This is widely used in the SaaS industry, including AI-based tools, cloud storage providers, and VPN services.

Preventing Online Poll Manipulation & Fake Reviews

Many online voting systems, surveys, and e-commerce review platforms struggle with users submitting multiple responses to manipulate results.

How fingerprinting detects vote manipulation:

  • A user submits a vote or review.
  • They switch accounts, change IPs, or use incognito mode to try again.
  • The system detects that the browser fingerprint is the same as a previous submission.
  • The site blocks duplicate responses, ensuring fair results.

Example:

  • A company runs a public online poll to decide the next product feature.
  • A group tries to spam votes for a specific option by using multiple accounts.
  • The website blocks duplicate submissions coming from the same browser fingerprint.

Similarly, e-commerce sites like Amazon, Trustpilot, and Yelp use fingerprinting to detect fake reviews.

Anti-Cheating & Ban Evasion Prevention in Online Gaming

Gaming companies use browser fingerprinting to ban cheaters and prevent them from creating new accounts after a ban.

How fingerprinting prevents ban evasion:

  • A player is caught using cheats and gets banned.
  • They try to create a new account using a different email and VPN.
  • The game detects that their fingerprint matches the previously banned player.
  • The system automatically bans the new account as well.

Example:

  • A player is banned for using aimbot in a competitive shooter (e.g., CS:GO, Valorant).
  • They create a new account, thinking that changing their IP and username is enough.
  • The system detects the same browser fingerprint and auto-bans the new account.

Gaming companies like Riot Games, Valve, and Epic Games actively use this method to combat cheaters and toxic players.

Despite privacy concerns, browser fingerprinting remains one of the most powerful legitimate tools in cybersecurity, fintech, and digital rights enforcement.