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How to Bypass and Scrape HUMAN Bot Protected Sites with Python

Tutorial on how and Scrape Human Bot protected sites with Python

If you’ve ever tried scraping a website and suddenly hit a roadblock, there’s a good chance you’ve encountered a system like HUMAN Bot Defender. This advanced anti-bot solution detects even the smallest signs of automation, ensuring that only real users can access the site’s content. While these defenses are incredibly effective, they’re not insurmountable.

In this guide, I’ll walk you through:

  • Understand HUMAN Bot Defender
  • A breakdown of the system’s toughest defenses, such as the press-and-hold challenge and other advanced detection mechanisms
  • How to bypass HUMAN Bot Defender using Python and ScraperAPI

By the end, you’ll have the tools to scrape HUMAN-protected sites effectively and responsibly.

Ready to dive in? Let’s get started!

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What is HUMAN Bot Defender?

So, what exactly are we dealing with? HUMAN Bot Defender is an advanced bot mitigation platform that blocks automated traffic by analyzing how users interact with websites.

Rather than relying on basic CAPTCHAs or static rules, HUMAN employs a more sophisticated approach by looking for subtle patterns in user behavior—like how you move your mouse or interact with page elements. This allows the system to identify highly advanced bots that mimic real users.

Let’s break down how it works:

HUMAN Sensor

The HUMAN Sensor is at the heart of HUMAN Bot Defender, a JavaScript snippet embedded into the site. This sensor tracks and records detailed user interactions, such as mouse movements, clicks, and scrolling behavior. The collected data is anonymized and returned to HUMAN’s servers for analysis. These signals help the system determine whether the user behaves like a human or a bot.

Detector

The real magic happens in the Detector. This component analyzes the data sent by the HUMAN Sensor using machine learning models trained on millions of interactions. The Detector looks for anomalies in mouse movements, click timing, page navigation, and other interaction patterns that could indicate bot activity. It uses a combination of behavioral analysis and a global database of known attacks, constantly learning and improving based on new threats.

Enforcer

Once suspicious activity is detected, the Enforcer steps in. This component decides how to handle the flagged traffic in real time, using pre-configured security rules set by the site owner. Based on the level of risk, the Enforcer can block the traffic, rate-limit it, serve a CAPTCHA, or present a Human Challenge (such as the press-and-hold button). The goal is to keep bots out while ensuring legitimate users aren’t negatively impacted.

Risk Cookie

HUMAN Bot Defender assigns each user session a Risk Cookie to further enhance security. This cookie tracks critical session data, allowing HUMAN to monitor each visitor’s behavior over time. If the cookie collects enough evidence of bot-like activity—such as unusual navigation patterns or high-speed interactions—it may trigger additional security actions, such as blocking or presenting a challenge.

Human Challenge

Instead of relying on traditional CAPTCHAs, HUMAN employs a press-and-hold challenge, which is easier for real users and more complicated for bots to bypass. This challenge may look simple—requiring the user to click and hold a button for a few seconds—but it’s designed to track the subtle variations in how humans press and release buttons. These variations, such as timing, pressure, and cursor movements, are difficult for bots to replicate. HUMAN continues to refine this challenge to stay ahead of bot developers, making it a key hurdle for scrapers.

How HUMAN Bot Defender Protects Websites

HUMAN Bot Defender is more than just a simple bot blocker—it’s a multi-layered system that uses a combination of behavioral analysis, machine learning, and real-time decision-making to stop bots in their tracks. Here’s a breakdown of its core defenses:

  • Behavioral Fingerprinting: Tracks how users interact with the page, looking for irregular mouse movements, scrolling behavior, and click patterns that bots can’t easily replicate.
  • Browser Fingerprinting: Builds a unique profile of the browser and device, gathering details such as screen resolution, installed fonts, and plugins to detect discrepancies between what’s reported and actual behavior.
  • JavaScript Challenges: HUMAN injects JavaScript challenges into the page that bots, especially headless browsers, struggle to pass. These tests might check how a browser executes specific APIs or handles DOM manipulation.
  • Human Challenge: The press-and-hold challenge is designed to detect bots by analyzing the timing and pressure of user clicks—something automated scripts typically can’t simulate well.
  • IP Reputation & Risk Scoring: HUMAN assigns each user an IP reputation score based on the user’s history and known bot activity. Suspicious IPs may trigger rate-limiting, blocking, or additional challenges.

By combining these methods, HUMAN Bot Defender ensures that bots struggle to get through, no matter how advanced. However, you can navigate these defenses without detection with the right tools and techniques.

How to Bypass HUMAN Bot Defender

Now that we’ve covered how HUMAN Bot Defender protects websites, let’s explore how to bypass these sophisticated defenses using Python.

Here are some techniques to help you bypass HUMAN Bot Defender’s defenses:

1. IP Rotation to Avoid Blocking

One of the first ways HUMAN Bot identifies bots is through IP tracking. If multiple requests come from the same IP or an IP has a suspicious reputation, it can lead to blocks or rate-limiting. To prevent this, you must rotate your IP address with every request.

How to Handle It:

  • Use a pool of high-quality residential proxies and rotate IPs regularly to simulate different users from various locations.
  • This keeps your scraper under the radar, as each request appears to come from a new source.

Example: Using Python to Rotate IPs

import requests
import random

# List of proxies (ensure they are residential or high-quality)
proxies = [
    {'http': 'http://proxy1:port', 'https': 'https://proxy1:port'},
    {'http': 'http://proxy2:port', 'https': 'https://proxy2:port'}
]

# Function to rotate IP and send request
def get_with_proxy(url):
    proxy = random.choice(proxies)
    response = requests.get(url, proxies=proxy)
    return response

# Target URL
url = 'https://target-website.com'

# Make a request with rotated IP
response = get_with_proxy(url)
print(response.text)

By rotating proxies, you can avoid triggering IP-based detection mechanisms, especially on sites that implement rate limiting or IP blacklisting.

Example: Using ScraperAPI in Proxy Mode for IP Rotation

ScraperAPI’s proxy mode allows you to rotate IPs without manually managing a proxy pool. Here’s how to set it up in Python:

import requests

# Define ScraperAPI proxy with your API key
proxies = {
    "http": "http://scraperapi:YOUR_API_KEY@proxy-server.scraperapi.com:8001",
    "https": "http://scraperapi:YOUR_API_KEY@proxy-server.scraperapi.com:8001"
}

# Target URL
url = 'http://httpbin.org/ip'  # Replace with the target site

# Send the request with IP rotation through ScraperAPI
response = requests.get(url, proxies=proxies, verify=False)

# Print the response
print(response.text)

In this example, each request is sent through ScraperAPI’s proxy server, which automatically rotates IPs. Additionally, by adding render=true to the proxy URL, ScraperAPI will render JavaScript on the page, making it easier to scrape content from dynamic websites that rely on JavaScript. This approach reduces the chances of triggering IP-based detection, especially for HUMAN-protected sites that monitor IP patterns for rate limiting or blacklisting.

2. Rotate User Agents and Headers to Evade Fingerprinting

HUMAN Bot Defender doesn’t just rely on IP addresses—it also tracks your browser’s fingerprint, which includes your User-Agent string, browser settings, and headers. It will likely be flagged if your scraper repeatedly uses the same User-Agent or headers.

How to Handle It:

  • Rotate User-Agent strings and add standard headers (Accept-Language, Referer, and Connection) with each request to mimic legitimate traffic.

Rotating your User-Agent string and setting typical browser headers makes your scraper look more legitimate and reduces the chances of being flagged by HUMAN’s fingerprinting techniques.

Note: Alternatively, use ScraperAPI to automatically assign headers and generate matching cookies with a simple API call.

3. Manage Cookies and Sessions Properly

HUMAN Bot Defender uses session tracking and cookies to monitor user behavior across multiple requests. If your scraper doesn’t handle cookies properly—such as creating a new session with every request or not storing cookies—it will trigger suspicion.

How to Handle It:

  • Use Python’s requests.Session() to manage cookies across requests and simulate a continuous user session. This prevents HUMAN from detecting disjointed behavior.

Example: Managing Sessions with Python

import requests

# Create a session object to handle cookies automatically
session = requests.Session()

# First request to store cookies
response = session.get('https://target-website.com')

# Subsequent request within the same session
response = session.get('https://target-website.com/another-page')

print(response.text)

By managing session cookies, you ensure your scraper behaves like a real user, making multiple requests within a valid session.

4. Simulate Human-Like Interactions to Bypass Behavioral Analysis

HUMAN Bot Defender relies on behavioral analysis to detect bots based on user interactions like mouse movements, clicks, and scrolling behavior. Automated scripts often fail to simulate this human-like behavior, which can lead to detection.

How to Handle It:

  • Use Selenium or Puppeteer to simulate realistic human interactions with the site, including moving the mouse, scrolling, and clicking buttons.

Example: Simulating Mouse Movements and Clicks with Selenium

from selenium import webdriver
from selenium.webdriver.common.action_chains import ActionChains
import time

# Initialize the browser
driver = webdriver.Chrome()

# Navigate to the target website
driver.get('https://target-website.com')

# Simulate scrolling
driver.execute_script("window.scrollTo(0, document.body.scrollHeight);")

# Simulate pressing and holding a button for 3 seconds
button = driver.find_element_by_id('press-hold-button')
actions = ActionChains(driver)
actions.click_and_hold(button).pause(3).release().perform()

time.sleep(3)  # Allow time for JavaScript execution
driver.quit()

Simulating human-like behavior makes it more difficult for HUMAN Bot to distinguish between a bot and a legitimate user.

Note: You can also use ScraperAPI’s rendering instructions to simplify your code, improve performance, and mimic human behavior without using headless browsers.

5. Use ScraperAPI for Effortless Bypassing (The Ultimate Solution)

While manual techniques can help bypass specific defenses, they can be time-consuming and complex. ScraperAPI offers a streamlined, all-in-one solution that automates IP rotation, JavaScript rendering, session management, and CAPTCHA solving, making it the optimal choice for tackling HUMAN Bot’s sophisticated protections.

Here’s how ScraperAPI effectively bypasses HUMAN Bot’s challenges:

  • Automatic IP rotation: HUMAN Bot relies on IP-based detection to block automated access. However, ScraperAPI’s global IP rotation network seamlessly assigns a fresh IP to each request, reducing detection risk.
  • JavaScript rendering: By enabling JS rendering, ScraperAPI automatically handles any dynamic elements or challenges that require JavaScript, simulating real user interaction and making it possible to extract data from pages protected by HUMAN Bot’s JavaScript checks.
  • Session and cookie management: ScraperAPI maintains sessions and cookies across requests, ensuring your activity resembles a legitimate user session. This behind-the-scenes management minimizes detection risks and creates a seamless browsing experience for continuous scraping.
  • CAPTCHA handling: When ScraperAPI detects a CAPTCHA challenge, it drops the connections and retries the request with a new configuration, effectively avoiding CAPTCHA challenges – only charging for successful requests.

Example: Using ScraperAPI to Scrape a HUMAN-Protected Site

import requests

# ScraperAPI key and target URL
API_KEY = 'your_scraperapi_key'
URL = 'https://www.zillow.com/homes/for_sale/'  # Example site protected by HUMAN Bot

# Parameters for the ScraperAPI request
params = {
    'api_key': API_KEY,
    'url': URL,
    'render': 'true'  # Ensures JavaScript is rendered, which is crucial for HUMAN challenges
}

# Send request through ScraperAPI
response = requests.get('http://api.scraperapi.com', params=params)

# Check the response status
if response.status_code == 200:
    print('Successfully bypassed HUMAN Bot and scraped the site.')
    print(response.text)  # Contains the HTML content of the scraped page
else:
    print(f'Failed to scrape the site. Status code: {response.status_code}')

Code Breakdown:

  1. Importing requests: The requests library allows us to make HTTP requests.
  2. API Key and URL: Replace 'your_scraperapi_key' with your actual ScraperAPI key, and specify the site URL you want to scrape. Here, https://www.zillow.com/homes/for_sale/ is an example site that HUMAN Bot protects.
  3. Setting Parameters:
    • 'api_key': Your unique ScraperAPI key, which authenticates your requests.
    • 'url': The URL you want to scrape.
    • 'render': ‘true’: Enabling the render option to handle JavaScript rendering is necessary for dynamic pages and HUMAN Bot protections that require it.
  4. Making the Request: The requests.get function sends a GET request to ScraperAPI’s endpoint (http://api.scraperapi.com) with the parameters. ScraperAPI manages IP rotation, user agents, sessions, and other details in the background.
  5. Checking the Response:
    • Success (status_code == 200): If the request is successful, the HTML content of the page is printed, confirming that you bypassed HUMAN Bot’s protections.
    • Failure: If unsuccessful, the status code is displayed, helping you troubleshoot issues like rate limits or errors.

With ScraperAPI handling all the complexities, this code snippet shows how simple it is to bypass HUMAN Bot’s protections, letting you effortlessly access the content you need.

Conclusion

Scraping websites protected by HUMAN Bot Defender presents significant challenges, including IP-based detection, session tracking, and behavioral analysis. However, you can bypass these defenses by employing IP rotation, User-Agent rotation, and human-like interaction simulation strategies.

ScraperAPI offers an all-in-one solution that automatically handles IP rotation, JavaScript rendering, session management, and CAPTCHA handling for a more efficient and automated approach. Whether you’re scraping real estate data from Zillow or any other site protected by HUMAN, ScraperAPI simplifies the process and helps you stay under the radar.

Ready to get started? Sign up for ScraperAPI and start scraping smarter today!

About the author

Picture of Ize Majebi

Ize Majebi

Ize Majebi is a Python developer and data enthusiast who delights in unraveling code intricacies and exploring the depths of the data world. She transforms technical challenges into creative solutions, possessing a passion for problem-solving and a talent for making the complex feel like a friendly chat. Her ability brings a touch of simplicity to the realms of Python and data.

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