How Modern Scrapers Bypass TLS with Custom Fingerprints

Anyone who has done web scraping knows that in the past few years, besides various CAPTCHAs, the increasingly “smart” anti-scraping mechanisms have been the biggest headache for developers.

Especially with modern techniques like TLS fingerprinting, HTTP/2 fingerprinting, and browser fingerprinting, it’s no longer an era where adding a header or changing a User-Agent could fool the system.

Why can websites identify whether you are a “scraper” or a “real browser” simply through TLS and HTTP/2 fingerprints? Next, the editor will explain this in detail.

1. Why are websites now using TLS fingerprinting?

It’s simple—traditional User-Agent / Cookie / IP rate limiting is no longer effective.

When a real browser establishes an HTTPS connection, it performs a TLS handshake. This handshake contains a huge amount of extremely detailed information, such as:

• Supported cipher suites
• Order of extension fields
• Supported protocol versions
• SNI, ALPN, and how these fields are combined

These combinations are different across browsers, operating systems, and versions.

What the server sees is:

“This TLS ClientHello doesn’t look like Chrome, nor Firefox, nor Safari. You’re very likely a script-generated client.”

This is the basic logic of TLS fingerprinting.

2. HTTP/2 Fingerprinting: The new favorite of anti-scraping

If TLS fingerprinting is the first filter, then HTTP/2 fingerprinting is the second.

Some characteristics of HTTP/2, such as:

• Frame type order
• PRIORITY and SETTINGS configuration
• The behavior of WINDOW_UPDATE

These are extremely consistent in real browsers, but behave very differently in many network libraries (such as default implementations in Python/Go).

Therefore, to make a scraper “look more human,” one must solve the fingerprint differences at the HTTP/2 layer as well.

3. Browser fingerprinting: From appearance to behavior, nothing escapes

Beyond the network layers of TLS / H2, the browser itself exposes many fingerprints.

This explains why the ToDetect fingerprinting tool is so professional—it does not rely on single-point detection but evaluates multiple dimensions comprehensively.

4. Custom Fingerprint Libraries: The “makeup” of modern scrapers

Modern scraping frameworks often adopt a “fingerprint templating” approach, meaning that they pre-record TLS / HTTP/2 / JS environment fingerprints across different browsers, operating systems, and versions, forming a fingerprint library.

This library may include:

• TLS fingerprints of Chrome 120 on Windows, macOS, and Ubuntu
• HTTP/2 SETTINGS of different Chrome versions
• Default font sets for various systems
• Common WebGL messages from browsers
• Typical object structures in JavaScript environments

When sending requests, a scraper selects a template so its behavior “looks like a real browser.”

It’s like “makeup”—not random painting, but mimicking the face of a real person.

5. Why can a “fingerprint library” improve success rates?

Because the behavior of real browsers is stable, consistent, and predictable.

When your scraper “learns” the behavior patterns of real browsers, it naturally becomes harder to detect. For example:

• The cipher suite order in Chrome follows a fixed pattern
• Chrome’s HTTP/2 SETTINGS parameters are always the same
• Browser extension fields don’t randomly change
• JavaScript object structures and function counts follow standards

Conclusion: Use fingerprint technology responsibly

TLS fingerprinting, HTTP/2 fingerprinting, and browser fingerprinting are fundamentally part of Internet security. These technologies must be used legally, following site terms of use, and cannot be used for unauthorized data scraping or access circumvention.

In legally authorized scenarios—such as testing your own site’s anti-scraping effectiveness, improving risk control strategies, or conducting security research—fingerprint simulation technology is extremely valuable.