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

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

BrowserAct provides a dedicated stealth browser that is ready to use once you've created a stealth browser profile. According to BrowserAct's documentation, its stealth browser is designed to reduce common automation signals by providing characteristics such as:

• WebDriver not exposed
• Realistic plugin surface
• Chrome user agent instead of HeadlessChrome
• Hardware-like WebGL rendering
• Reduced Chrome DevTools Protocol (CDP) detection signals
• A browser fingerprint designed to resemble a regular browsing session

To launch the browser, I simply opened my existing stealth browser profile:

browser-act --session stealth-test browser open <browser-id> https://example.com --headed

No additional stealth configuration was required before running my tests.

Agent Browser

For Agent Browser, 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

The report looked very clean. The key observations I noted were:

• WebDriver: Passed
• Chrome object: Present
• Plugin detection: Passed
• Browser fingerprint appeared consistent with a normal browser session

BrowserAct passed all of the major fingerprint checks reported by SannySoft during my testing. The browser exposed very few characteristics that would immediately identify it as automation.

Agent Browser Test

For Agent Browser, I also launched a browser session directly.

agent-browser --session fingerprint open https://bot.sannysoft.com --headed

The overall report was fairly strong, but one result immediately stood out. The key observations were:

• WebDriver: Failed
• Chrome object: Present
• Plugin detection: Passed
• Most browser fingerprint checks passed successfully

From my test, WebDriver was the only major fingerprint check that failed. The remaining fingerprint characteristics appeared much closer to a regular browser session.

Side-by-Side Results

What I Observed

Before running the test, I expected both tools to perform similarly because both advertise stealth capabilities. BrowserAct passed all of the major checks reported by SannySoft during my test, while Agent Browser exposed one remaining automation indicator through the WebDriver check.

Of course, browser fingerprinting is only one layer of modern anti-bot detection, and websites evaluate many more signals before deciding whether to trust a browser session. But still, this benchmark gave me a good first impression. BrowserAct presented a browser fingerprint that looked slightly closer to a regular user session based on the checks reported by SannySoft.

Now, let's see how both tools would behave when facing an actual anti-bot challenge instead of a diagnostic website.

Test 2: Cloudflare Challenge

Fingerprint tests are useful because they reveal how detectable a browser is. That's why I also tested both tools against the Cloudflare Challenge page provided by ScrapingCourse. Unlike SannySoft, this isn't a diagnostic report. The browser either reaches the protected page or it doesn't.

BrowserAct Test

I opened a fresh BrowserAct stealth browser session and navigated directly to the Cloudflare challenge page.

browser-act --session cloudflare browser open <browser-id> https://www.scrapingcourse.com/cloudflare-challenge --headed

Within a few moments, the verification completed successfully. The page displayed:

"You bypassed the Cloudflare challenge! :D"

I inspected the current page again directly from the terminal using:

browser-act --session cloudflare state

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

The result was noticeably different from BrowserAct. Instead of reaching the protected content, the browser remained on Cloudflare's verification screen. On the terminal, it displayed:

"Just a moment"

And on the Cloudflare page, it repeatedly displayed:

"Verify you are human"

The challenge kept refreshing, and even after 4 attempts, it never progressed to the protected page.

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 good fingerprint results but struggled with Cloudflare.