BrowserAct vs Agent Browser: A Hands-On Stealth Execution Comparison

A hands-on comparison where I tested BrowserAct and Agent Browser using the SannySoft browser fingerprint test and the Cloudflare Challenge benchmark to evaluate their stealth execution and anti-bot capabilities under identical conditions.

You switched to a browser automation tool built specifically for AI agents.

That should have solved the hardest part... right?

After all, these tools are designed for production workflows, autonomous agents, and modern browser automation. So you launch your agent against a website protected by Cloudflare, expecting everything to work.

Instead, you find yourself in front of another verification page. Or the browser keeps asking you to verify you're human. Or the automation simply never reaches the content you need.

So I was asking myself:

If both BrowserAct and Agent Browser are built for AI agents, how different are they when it comes to stealth execution and anti-detection?

Instead of comparing documentation or feature lists, I decided to run both tools through the same hands-on tests under the same conditions.

For this comparison, I focused on one capability: stealth execution.

I tested both tools against the two most widely used benchmarks in the automation community.

• 
  SannySoft for browser fingerprint detection


• 
  Cloudflare Challenge for real-world anti-bot protection

These two tests measure different aspects of browser automation, and together they provide a clearer overview than a simple feature comparison.

I'll walk through exactly what I observed during both tests, where each tool performed well, where I noticed differences, and which one I would choose depending on the type of automation I'm building.

Before getting into the results, it's important to understand why stealth execution has become one of the biggest challenges in modern browser automation.

Why Stealth Execution Matters in Modern Browser Automation

A few years ago, getting browser automation working mostly meant writing reliable scripts.

If your selectors were correct and your timing was good, there was a good chance your automation would work consistently.

Today, that's only half of the challenge.

Modern websites don't just respond to browser actions. They also evaluate the browser itself almost immediately after the page starts loading.

That creates two different layers of anti-bot protection.

The first layer is browser fingerprint detection.

This focuses on identifying whether the browser behaves like a normal user or an automated environment. Websites inspect signals such as:

• navigator.webdriver


• browser plugins


• user agent


• WebGL renderer


• Chrome object


• other browser fingerprint characteristics

Many of these checks happen before your automation even clicks its first button.

The second layer is real-world anti-bot protection.

Services such as Cloudflare combine browser fingerprinting with additional signals like browser behavior, challenge-response verification, network reputation, and other detection techniques before deciding to trust a session.

That's an important distinction because passing a fingerprint test doesn't automatically mean a browser will get through Cloudflare or similar protection systems.

This is exactly why I used two different benchmarks for this article.

On paper, both BrowserAct and Agent Browser offer stealth capabilities.

The important thing is how they approach it. And that difference isn't obvious from their documentation.

It becomes easier to understand the difference when you run the same tests against both tools.

BrowserAct vs Agent Browser: Stealth Approach Before Testing

Before running the benchmarks, I wanted to understand how each tool approaches browser execution in environments that actively inspect automation.

Although both tools target AI agent workflows, they expose their browser environments differently.

BrowserAct

, I used the standard CLI installation and launched a browser session directly without adding any extra plugins or manually modifying the browser fingerprint.

The browser was started with:

agent-browser --session stealth-test open https://example.com --headed

Since my goal was to compare the tools using their default workflows after installation, I intentionally avoided adding third-party extensions or making manual browser modifications.

Hands-On Testing Methodology

To keep the comparison as fair as possible, I tested both tools under the same environment using fresh test runs for this article.

Test Environment

• Windows


• BrowserAct CLI (using a built-in stealth browser profile)


• Agent Browser CLI (default installation)


• Chromium-based browsers

Why SannySoft and the Cloudflare Challenge were selected

I selected two benchmarks because they evaluate different aspects of browser automation.

• 
  bot.sannysoft.com checks browser fingerprint characteristics, including WebDriver detection, browser plugins, user agent characteristics, Chrome object availability, WebGL information, and several other browser signals.


• 
  scrapingcourse.com/cloudflare-challenge simulates a real Cloudflare-protected page and shows whether the browser can successfully reach the protected content.

Together, these tests provide a practical view of both browser detectability and real-world behavior.

With both environments ready, I moved on to the fingerprint and Cloudflare challenge tests.

Test 1: Browser Fingerprint Detection (SannySoft)

The first benchmark I ran was SannySoft.

Instead of checking whether a browser can bypass a specific anti-bot provider, SannySoft focuses on the browser fingerprint itself.

I ran the test separately with BrowserAct and Agent Browser using fresh browser sessions.

BrowserAct Test

For BrowserAct, I opened a new stealth browser session and navigated directly to SannySoft.

browser-act --session fingerprint browser open <browser-id> https://bot.sannysoft.com --headed

BrowserAct also provides a useful CLI command (state) that lets you inspect the current page directly from the terminal.

browser-act --session fingerprint state

Within a few moments, the verification completed successfully.

The page displayed:

Unlike several Cloudflare tests I've previously run with other browser automation tools, this session didn't get stuck repeatedly asking for additional verification.

It simply completed the challenge and proceeded to the protected content.

That was the outcome I was hoping to evaluate with this benchmark.

Next, I repeated the same test using Agent Browser under the same conditions.

Agent Browser Test

For Agent Browser, I followed the same process and opened the Cloudflare challenge page using a fresh browser session.

agent-browser --session cloudflare open https://www.scrapingcourse.com/cloudflare-challenge --headed

Unlike BrowserAct, which completed the verification during my first attempt, Agent Browser remained stuck in the verification loop throughout the test.

I also kept the terminal running during the test to make sure nothing else was happening in the background.

Side-by-Side Results

What I Observed

BrowserAct completed the verification and reached the protected page on my first attempt.

Agent Browser, on the other hand, never moved beyond Cloudflare's verification screen during my testing. The browser continued asking me to verify that I was human and never reached the protected content.

Of course, Cloudflare constantly updates its detection systems, so no single test guarantees that a browser will always succeed or always fail in every environment.

Still, these were the results I consistently observed while running both tools under the same conditions.

BrowserAct vs Agent Browser: Test Results and Comparison

These observations come directly from what I saw during the tests.

The important difference for me was what happened when the browser reached a protected website.

The fingerprint benchmark showed only one failed check for Agent Browser, which initially made me think the Cloudflare test might produce similar results.

Instead, the two tools behaved very differently.

Which Tool Should You Choose?

Both BrowserAct and Agent Browser are designed for AI-powered browser automation, but based on my testing, they currently perform differently when stealth execution is the primary concern.

BrowserAct is a better fit if you:

• regularly work with websites protected by Cloudflare or similar anti-bot systems


• need the strongest browser fingerprint possible from the initial setup


• prioritize getting through anti-bot protection over browser customization

During my testing, BrowserAct passed every major SannySoft fingerprint check and successfully completed the Cloudflare challenge test on the first attempt. If those are the kinds of environments you work with every day, that was a meaningful advantage.

Agent Browser is worth considering if you:

• are already building AI agent workflows around its ecosystem


• don't primarily target heavily protected websites

In my tests, Agent Browser produced a good fingerprint overall, with the exception of the WebDriver check. The larger limitation appeared during the Cloudflare benchmark.

That doesn't necessarily mean it will struggle with every protected website, but it was the outcome I consistently observed.

So the right choice depends on the problems you're trying to solve.

Final Thoughts

Before starting this comparison, I expected the two tools to produce fairly similar results.

Since both are built for AI agents and both offer stealth capabilities, I assumed the differences would mostly come down to developer experience or workflow preferences.

After running the tests, I found different results.

The browser fingerprint benchmark already showed a small difference between the two tools, but the Cloudflare challenge test made the distinction more obvious.

So, it's easy to compare features on a website or read through documentation, but running the same benchmark under the same conditions often makes the differences much clearer.

Of course, anti-bot systems evolve constantly, and no browser automation tool will succeed against every protected website forever. Results can also vary depending on the target site, browser version, network environment, and future updates to both tools.

These findings simply reflect what I observed while testing BrowserAct and Agent Browser side by side.

If you'd like to reproduce the same tests I ran in this article, you can try , you'll receive 500 free credits to help you get started with your own experiments.