How Device Fingerprints Are Blocking You Online (And What You Can Do About It)
In the battle for data on the internet, there‘s an ongoing arms race between those trying to access and collect publicly available information, and those seeking to block and restrict that access. A key weapon in this fight is device fingerprinting – techniques that websites use to identify and track visitors based on the unique attributes of their devices and browsing behavior.
Device fingerprints serve as a digital signature that can give away who you are and enable sites to block your access, even if you try to hide behind proxies or VPNs. For businesses engaged in competitive research, price comparison, or other forms of web data collection, it‘s essential to understand how device fingerprinting works and take steps to mask your identity.
In this post, we‘ll take an in-depth look at the most common types of device fingerprinting used today and share some tips on how to fly under the radar and avoid getting blocked.
What is Device Fingerprinting?
Device fingerprinting refers to the process by which websites collect information about the devices and software used by their visitors to identify and track them. By piecing together details like your browser version, operating system, screen size, installed fonts, and more, sites can form a unique profile or "fingerprint" for each visitor.
This fingerprint remains relatively stable even if you switch networks or use incognito mode. Whenever you visit a site, your device fingerprint is checked against a database of known fingerprints to see if you‘ve visited before. Based on your past behavior and reputation score, the site can choose to allow or block your access.
Device fingerprinting evolved as a way to uniquely identify visitors and track them in a more persistent way than cookies, which can be easily cleared by users. Unlike cookies, fingerprinting operates discreetly in the background and is very difficult for the average user to detect or prevent.
While fingerprinting has some legitimate uses, like preventing fraud and bot abuse, it‘s increasingly being leveraged in an adversarial way. Companies employ fingerprinting to block competitors from accessing their data, prevent web scraping, and restrict features based on a user‘s identity or reputation.
The 5 Types of Device Fingerprinting
Now let‘s break down the primary methods of fingerprinting you need to be aware of and defend against. We‘ll cover the "big 5" of IP, header, protocol, client-side, and behavioral analysis.
1. IP Fingerprinting
IP fingerprinting is one of the simplest and most common methods for tracking and blocking users. Whenever you connect to a website, the site logs your IP address – the numerical label assigned to your device on the internet.
Your IP address reveals key information like your geographical location and internet service provider. Sites can check your IP against databases of known VPNs, proxies, hosting providers, and past offenders to decide whether to let you in.
IP fingerprinting also enables sites to link your current visit to your past activity on the site. They can enforce restrictions like only allowing one account per IP address, or permitting only a certain number of actions (searches, page views, etc.) per IP in a given timeframe, to prevent bots and block suspected scrapers.
2. Header Fingerprinting
Headers are snippets of information included with every web request that your browser sends to websites. Headers communicate key technical details about your browser and device so the website can tailor its response.
The most identifying header is the User-Agent string, which specifies your browser, its version, your operating system, and other details. Additional headers disclose your preferred languages, character encodings, compression methods, and more.
For normal users, browsers automatically add the appropriate headers to every request. But for web scrapers or other automated tools, it‘s up to the developer to properly set these headers. Even minor deviations from what‘s expected – like putting headers in the wrong order or case – can make your requests stand out as abnormal.
Header fingerprinting techniques compare your headers against known configurations for different browsers and devices. Discrepancies between your user agent and other headers can reveal that you‘re trying to spoof your identity. More advanced analysis can even detect suspiciously rapid or patterned changes to your headers.
3. Protocol Fingerprinting
Websites can also fingerprint you based on the specific networking protocols your browser supports. Most modern sites use HTTPS, the secure version of HTTP, to encrypt traffic. But within HTTPS, there are different versions of the TLS encryption protocol that can be used.
By analyzing technical details of how your browser carries out the TLS handshake and which encryption methods it supports, sites can make inferences about your browser and device. Unusual or outdated protocol configurations are a red flag.
Many web scraping tools still rely on older protocol versions like HTTP/1.1 and TLS 1.2, while most modern browsers have moved on to HTTP/2 and TLS 1.3. To avoid standing out, scrapers need to closely imitate the protocol behavior of the browsers they‘re impersonating.
4. Client-Side Fingerprinting
Client-side fingerprinting, also known as browser fingerprinting, uses JavaScript to probe the internals of a visitor‘s browser and extract identifying information. Websites can inspect a wide range of attributes about your browser, operating system, hardware, and configuration settings.
Some of the most commonly collected client-side signals include:
- Screen resolution and color depth
- Browser window size and zoom level
- Time zone and system clock
- Installed fonts and plugins
- WebGL and canvas fingerprint
- AudioContext fingerprint
- Device memory and CPU info
- Keyboard layout
- Bluetooth and battery status
Websites use open source tools like FingerprintJS to gather hundreds of these attributes into a unique hash that persistently identifies your browser. Even if you change your IP address, clear your cookies, or switch browsers, your fingerprint will often stay the same and give away your identity.
More advanced techniques like canvas fingerprinting work by rendering hidden graphics in your browser and analyzing minute differences in how the image is drawn on different devices. Other cutting-edge approaches use WebRTC to discover your true IP address even if you‘re behind a VPN.
With so many identifying factors in play on the client side, creating a convincingly spoofed browser fingerprint is a huge challenge for web scrapers. Automated tools are often blocked for having fingerprints that are missing key attributes or match known headless browser signatures.
5. Behavioral Fingerprinting
The newest frontier of fingerprinting looks at patterns in how you interact with websites to determine if you‘re a human or bot. Behavioral fingerprinting systems analyze your clicks, keystrokes, mouse movements, page scrolling, and other activity to create a unique profile of your behavior.
Real users exhibit distinctive micro-behaviors, like slightly curved mouse trajectories, hesitation before clicking, uneven scrolling speeds, and text entered in irregular bursts. Bots and automated tools, by contrast, tend to have more linear, mechanical actions without human imperfections.
Behavioral fingerprinting models are trained on millions of normal user sessions to learn the statistical distributions of human behavior signals. Deviations from these baseline patterns – like moving the mouse too directly or filling out forms too quickly – lead to higher bot scores.
Websites often combine multiple behavioral signals into an overall risk assessment for each visitor. High risk scores result in additional verification challenges like CAPTCHAs, or getting blocked outright. As behavioral fingerprinting becomes more prevalent, it‘s an increasingly uphill battle for bots and scrapers to convincingly mimic human-like behaviors at scale.
How To Protect Yourself from Fingerprinting
As we‘ve seen, device fingerprinting is a powerful tool for identifying and blocking unwanted visitors. For businesses that depend on web data collection, understanding fingerprinting techniques and how to combat them is essential to avoid getting shut out of critical data sources.
Here are some of the key strategies and tools you can use to mask your fingerprint and maintain access to the web data you need:
Rotate your IP address: Using proxy servers or a VPN that regularly cycles your IP address can help you avoid IP-based blocking. Be sure to choose reputable providers with extensive IP pools to minimize the risk of getting flagged.
Spoof your user agent and headers: Open source libraries make it relatively easy to generate legitimate-looking user agent strings and HTTP headers. Rotate your user agent periodically and ensure your headers are ordered and cased correctly.
Use up-to-date protocols: Configure your scraper to use the same protocol versions as the browsers you‘re imitating, which often means HTTP/2 and TLS 1.3 nowadays. Make sure there are no inconsistencies between your protocol and the rest of your fingerprint.
Emulate human behavior: Adding random delays, mouse movements, page scrolling and other human-like gestures to your scraper can help you get past behavioral fingerprinting. Even better, consider leveraging real human workers to carry out your data collection through crowdsourcing platforms.
Leverage browser automation tools: Frameworks like Puppeteer and Selenium allow you to automate full instances of Chrome or Firefox, making your traffic much harder to distinguish from real users. Be careful to configure these tools correctly to avoid emitting other bot signals.
Use a comprehensive fingerprint masking solution: Bright Data‘s Web Unlocker is an example of an end-to-end solution that takes care of masking all the key aspects of your device fingerprint. By routing your requests through a pool of real user devices, managed by the proxy provider, you can bypass fingerprinting techniques while collecting the data you need.
The Ongoing Battle for Web Data
Device fingerprinting is a powerful weapon in the cat-and-mouse game between web scrapers and websites that want to restrict access to their publicly available data. As fingerprinting techniques grow more sophisticated, data collectors need to stay on top of the latest countermeasures.
At its core, this battle over web data is a fight for fairness and transparency in online commerce. By blocking competitors from gathering pricing and product data, companies are trying to stifle competition and artificially segment markets. Retailers are increasingly showing different prices and offers to different users based on their past behavior and perceived willingness to pay.
Web scraping levels the playing field by revealing what‘s really happening behind the scenes and allowing companies to compete on equal footing. With the right tools and techniques to get past device fingerprinting, businesses can continue to collect the web data they need to make informed decisions and serve their customers.
The arms race between fingerprinters and data collectors is sure to rage on, but one thing is clear – the future belongs to companies that can adapt quickly and stay ahead of the curve. By understanding device fingerprints and how to combat them, you‘ll be well positioned to win the battle for web data and keep the online playing field open and fair.
