How to bypass AWS WAF in 2026: 4 working methods

Ever tried scraping a website only to hit a wall of 403 errors and "Access Denied" pages? That wall is often AWS WAF (Web Application Firewall). It's Amazon's bot-detection system that guards millions of websites.

In this guide, you'll learn four battle-tested methods to bypass AWS WAF protections. We'll cover everything from browser automation to open-source token solvers. Each method includes working code you can run today.

What is AWS WAF and How Does it Block Scrapers?

AWS WAF is Amazon's cloud-based firewall that inspects HTTP/HTTPS traffic before it reaches the target website. It uses multiple detection layers to identify automated traffic.

The firewall doesn't rely on a single method. It combines several techniques simultaneously.

AWS WAF Detection Methods

IP Reputation Analysis

AWS maintains databases of known datacenter IP ranges, VPN endpoints, and previously flagged addresses. Requests from suspicious IPs get blocked immediately.

TLS/JA3 Fingerprinting

Every client creates a unique "fingerprint" during the TLS handshake. Python's requests library and cURL have distinct signatures that differ from real browsers.

JavaScript Challenges

AWS WAF injects JavaScript code that real browsers execute automatically. The script generates an aws-waf-token cookie required for subsequent requests.

Rate Limiting

Burst traffic from a single IP triggers throttling. Too many requests too quickly results in 429 errors or outright blocks.

Browser Fingerprinting

The WAF checks Canvas rendering, WebGL capabilities, installed fonts, and other browser-specific attributes. Headless browsers often fail these checks.

The aws-waf-token Cookie

When AWS WAF detects a new visitor, it presents a challenge page. Your browser must execute JavaScript to solve this challenge.

Upon success, AWS generates an aws-waf-token cookie. This token proves you passed the verification and grants access to protected content.

The token typically expires within minutes. You need a fresh token for continued access.

Method 1: Open-Source Token Solver (Python & Golang)

This is the most powerful approach for bypassing AWS WAF in 2026. An open-source project reverse-engineered the token generation process.

The solver works by extracting challenge parameters from the initial response and computing the required token locally.

How the Token Solver Works

When you request a protected page, AWS WAF returns HTML containing encrypted challenge parameters:

• key - Encryption key
• iv - Initialization vector
• context - Challenge context
• gokuProps - Configuration object

The solver processes these parameters and generates a valid aws-waf-token without needing a real browser.

Python Implementation

First, install the required dependencies:

pip install requests httpx

Clone the AWS WAF solver repository:

git clone https://github.com/xKiian/awswaf.git
cd awswaf/python

Here's how to use the solver in Python:

from awswaf.aws import AwsWaf
import requests

# Make initial request to get challenge parameters
session = requests.Session()
response = session.get("https://protected-site.com")

# Extract gokuProps from the response
# The solver handles parameter extraction internally

The solver extracts the challenge parameters automatically. Let's break down the core flow:

import re
import requests

WEBSITE_URL = "https://target-protected-site.com"

# Step 1: Get the initial challenge page
client = requests.Session()
response = client.get(WEBSITE_URL)

# Check if AWS WAF protection is active
if response.status_code in [202, 405]:
    print("AWS WAF challenge detected")

This code checks for the telltale status codes. A 202 response indicates a JavaScript challenge. A 405 response means a CAPTCHA is required.

Now extract the challenge parameters:

# Step 2: Extract encryption parameters using regex
html_content = response.text

key_match = re.search(r'"key":"([^"]+)"', html_content)
iv_match = re.search(r'"iv":"([^"]+)"', html_content)
context_match = re.search(r'"context":"([^"]+)"', html_content)
challenge_js = re.search(r'<script.*?src="(.*?)".*?></script>', html_content)

if key_match and iv_match and context_match:
    key = key_match.group(1)
    iv = iv_match.group(1)
    context = context_match.group(1)
    js_url = challenge_js.group(1) if challenge_js else None
    
    print(f"Key: {key[:20]}...")
    print(f"IV: {iv[:20]}...")
    print(f"Context: {context[:20]}...")

The solver then computes the token using these extracted values.

Golang Implementation

For production systems, the Golang version offers better performance:

package main

import (
    "awswaf/internal/aws"
    "log"
)

func main() {
    // Create new AWS WAF solver instance
    waf, err := aws.NewAwsWaf(
        host,           // Target host
        "example.com",  // Domain
        "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36",
        gokuProps,      // Challenge parameters
        "",             // Proxy (optional)
    )
    
    if err != nil {
        log.Fatal(err)
    }
    
    // Generate the aws-waf-token
    token, err := waf.Run()
    if err != nil {
        log.Fatal(err)
    }
    
    // Use token for authenticated requests
    log.Printf("Token: %s", token)
}

The Golang implementation handles the cryptographic operations more efficiently. It's ideal for high-volume scraping operations.

When to Use This Method

Use the open-source solver when:

• You need high-volume token generation
• Browser automation is too slow
• You want full control over the bypass process
• You're building production scraping infrastructure

The solver supports both "invisible" challenges (type "token") and visual CAPTCHAs when combined with AI image recognition like Gemini.

Method 2: Browser Automation with Stealth Plugins

Browser automation remains the most reliable way to bypass AWS WAF challenges. Real browsers execute JavaScript naturally and pass fingerprinting checks.

Why Headless Browsers Get Detected

Standard headless browsers expose detectable artifacts:

• navigator.webdriver returns true
• Missing browser plugins and extensions
• Abnormal Canvas and WebGL fingerprints
• Predictable TLS handshakes

AWS WAF specifically checks for these indicators.

Playwright with Stealth Mode

Playwright provides excellent stealth capabilities in 2026:

from playwright.sync_api import sync_playwright
import time
import random

def bypass_aws_waf(url):
    with sync_playwright() as p:
        # Launch browser with stealth settings
        browser = p.chromium.launch(
            headless=False,  # Use headed mode for better success
            args=[
                '--disable-blink-features=AutomationControlled',
                '--no-sandbox',
                '--disable-web-security',
            ]
        )
        
        context = browser.new_context(
            viewport={'width': 1920, 'height': 1080},
            user_agent='Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'
        )
        
        page = context.new_page()

This setup disables automation detection flags. The browser appears as a regular user session.

Now navigate and wait for the challenge to resolve:

        # Navigate to protected URL
        page.goto(url, wait_until='networkidle')
        
        # Wait for potential challenge to complete
        time.sleep(random.uniform(2, 4))
        
        # Check for aws-waf-token cookie
        cookies = context.cookies()
        waf_token = None
        
        for cookie in cookies:
            if 'aws-waf-token' in cookie['name']:
                waf_token = cookie['value']
                print(f"Token acquired: {waf_token[:50]}...")
                break
        
        if not waf_token:
            print("Challenge may still be processing...")
            time.sleep(5)

The script waits for network activity to settle. This gives AWS WAF time to process the challenge.

Human-Like Behavior Simulation

AWS WAF analyzes behavioral patterns. Add realistic interactions:

        # Simulate human behavior
        page.mouse.wheel(0, random.randint(200, 500))
        time.sleep(random.uniform(0.5, 1.5))
        
        # Random mouse movements
        page.mouse.move(
            random.randint(100, 800),
            random.randint(100, 600)
        )
        
        # Get the page content after challenge completion
        content = page.content()
        
        browser.close()
        return content, waf_token

These interactions make your automation indistinguishable from real users.

Puppeteer Stealth Plugin (Node.js)

For Node.js projects, use puppeteer-extra with the stealth plugin:

const puppeteer = require('puppeteer-extra');
const StealthPlugin = require('puppeteer-extra-plugin-stealth');

// Apply stealth plugin
puppeteer.use(StealthPlugin());

async function bypassAwsWaf(url) {
    const browser = await puppeteer.launch({
        headless: false,
        args: [
            '--no-sandbox',
            '--disable-setuid-sandbox',
            '--disable-infobars',
            '--window-position=0,0',
            '--ignore-certificate-errors',
        ]
    });
    
    const page = await browser.newPage();
    
    // Set viewport to standard desktop size
    await page.setViewport({ width: 1920, height: 1080 });

The stealth plugin patches multiple detection vectors automatically.

    // Navigate and wait for challenge
    await page.goto(url, { waitUntil: 'networkidle0' });
    
    // Wait for AWS WAF to process
    await page.waitForTimeout(3000);
    
    // Extract cookies
    const cookies = await page.cookies();
    const wafToken = cookies.find(c => c.name.includes('aws-waf-token'));
    
    if (wafToken) {
        console.log('Token acquired:', wafToken.value.substring(0, 50));
    }
    
    const content = await page.content();
    await browser.close();
    
    return { content, token: wafToken?.value };
}

// Usage
bypassAwsWaf('https://protected-site.com')
    .then(result => console.log('Success'))
    .catch(err => console.error('Failed:', err));

This implementation handles the complete bypass flow in just a few lines.

Method 3: TLS Fingerprint Spoofing with curl_cffi

Standard HTTP libraries like requests have recognizable TLS fingerprints. AWS WAF blocks these fingerprints before any application-level checks.

Understanding JA3 Fingerprints

JA3 is the standard algorithm for TLS client fingerprinting. It hashes these handshake parameters:

• TLS version
• Cipher suites (in order)
• TLS extensions
• Elliptic curves
• Elliptic curve formats

Each HTTP client produces a unique JA3 hash. Python's requests library has a completely different fingerprint than Chrome.

curl_cffi: Chrome Fingerprint Impersonation

The curl_cffi library wraps curl-impersonate, a modified cURL that mimics real browser TLS handshakes:

pip install curl_cffi

Basic usage to bypass AWS WAF with proper fingerprinting:

from curl_cffi import requests

# Impersonate Chrome's TLS fingerprint
response = requests.get(
    "https://protected-site.com",
    impersonate="chrome120"
)

print(f"Status: {response.status_code}")
print(f"Content length: {len(response.text)}")

The impersonate parameter tells curl_cffi which browser fingerprint to use.

Available Browser Impersonations

curl_cffi supports multiple browser profiles:

# Chrome versions
CHROME_PROFILES = [
    "chrome99", "chrome100", "chrome101",
    "chrome110", "chrome116", "chrome120"
]

# Firefox versions
FIREFOX_PROFILES = [
    "firefox99", "firefox100", "firefox102"
]

# Safari versions
SAFARI_PROFILES = [
    "safari15_3", "safari15_5"
]

Rotate between profiles to avoid pattern detection.

Session Management with curl_cffi

Maintain cookies across requests:

from curl_cffi import requests

# Create a session with browser impersonation
session = requests.Session(impersonate="chrome120")

# First request triggers AWS WAF challenge
response = session.get("https://protected-site.com")

if response.status_code == 202:
    print("Challenge page received")
    # The session automatically handles cookies
    
# Subsequent requests include aws-waf-token
response = session.get("https://protected-site.com/data")
print(f"Data request status: {response.status_code}")

The session object persists cookies between requests. Once you have the aws-waf-token, subsequent requests succeed.

Combining with Proxy Rotation

Add proxy support for IP rotation:

from curl_cffi import requests
import random

PROXIES = [
    "http://user:pass@proxy1.example.com:8080",
    "http://user:pass@proxy2.example.com:8080",
    "http://user:pass@proxy3.example.com:8080",
]

def fetch_with_rotation(url):
    proxy = random.choice(PROXIES)
    
    response = requests.get(
        url,
        impersonate="chrome120",
        proxies={"http": proxy, "https": proxy}
    )
    
    return response

This approach combines fingerprint spoofing with IP diversity.

Method 4: Residential Proxy Rotation

IP reputation is a primary detection signal for AWS WAF. Datacenter IPs are almost always blocked.

Why Residential Proxies Work

Residential proxies route traffic through real consumer IP addresses. These IPs belong to legitimate ISP customers.

AWS WAF trusts residential IP ranges more than datacenter ranges. Your requests appear to originate from regular home users.

If you need reliable residential or mobile proxies, Roundproxies.com offers high-quality options including Residential Proxies, Datacenter Proxies, ISP Proxies, and Mobile Proxies for various scraping needs.

Building a Proxy Rotation System

Create a simple rotation manager:

import requests
from itertools import cycle
import time

class ProxyRotator:
    def __init__(self, proxy_list):
        self.proxies = cycle(proxy_list)
        self.current = next(self.proxies)
        self.request_count = 0
        self.max_requests = 10  # Rotate after N requests
    
    def get_proxy(self):
        self.request_count += 1
        
        if self.request_count >= self.max_requests:
            self.current = next(self.proxies)
            self.request_count = 0
            print(f"Rotated to new proxy")
        
        return {
            "http": self.current,
            "https": self.current
        }

This class rotates proxies after a set number of requests.

    def make_request(self, url, **kwargs):
        proxy = self.get_proxy()
        
        try:
            response = requests.get(
                url,
                proxies=proxy,
                timeout=30,
                **kwargs
            )
            return response
            
        except requests.exceptions.ProxyError:
            # Skip bad proxy and try next
            self.current = next(self.proxies)
            return self.make_request(url, **kwargs)

The error handling ensures failed proxies don't break your scraping.

Usage Example

# Initialize with your proxy list
proxies = [
    "http://user:pass@residential1.example.com:8080",
    "http://user:pass@residential2.example.com:8080",
    "http://user:pass@residential3.example.com:8080",
]

rotator = ProxyRotator(proxies)

# Make requests with automatic rotation
for i in range(100):
    response = rotator.make_request("https://protected-site.com/page")
    
    if response.status_code == 200:
        print(f"Request {i}: Success")
    else:
        print(f"Request {i}: Got {response.status_code}")
    
    time.sleep(random.uniform(1, 3))  # Random delay

Adding random delays between requests further reduces detection risk.

How to Detect AWS WAF Protection

Before attempting any bypass, confirm you're dealing with AWS WAF.

Response Header Analysis

Look for these telltale headers:

import requests

response = requests.get("https://target-site.com")

# Check for AWS-specific headers
headers_to_check = [
    'x-amz-cf-id',
    'x-amz-request-id',
    'x-amzn-requestid',
    'x-amz-apigw-id'
]

for header in headers_to_check:
    if header in response.headers:
        print(f"AWS indicator found: {header}")

These headers strongly indicate AWS infrastructure.

Cookie Analysis

AWS WAF sets specific cookies:

# Check for AWS WAF cookies
aws_waf_cookies = [
    'aws-waf-token',
    'awswaf-',
    'aws-waf-'
]

for cookie in response.cookies:
    for pattern in aws_waf_cookies:
        if pattern in cookie.name.lower():
            print(f"AWS WAF cookie found: {cookie.name}")

The presence of aws-waf-token confirms AWS WAF protection.

HTML Content Indicators

Challenge pages contain recognizable elements:

import re

html = response.text

# Look for AWS WAF challenge indicators
patterns = [
    r'"key":"[a-zA-Z0-9+/=]+"',
    r'"iv":"[a-zA-Z0-9+/=]+"',
    r'"context":"[a-zA-Z0-9+/=]+"',
    r'window\.gokuProps',
    r'awsWafCaptcha'
]

for pattern in patterns:
    if re.search(pattern, html):
        print(f"AWS WAF challenge pattern found: {pattern}")

These patterns appear on AWS WAF challenge pages.

Common Pitfalls and How to Avoid Them

Pitfall 1: Token Expiration

AWS WAF tokens expire quickly, often within 5-10 minutes.

Solution: Implement token refresh logic:

import time

class TokenManager:
    def __init__(self):
        self.token = None
        self.token_time = 0
        self.max_age = 300  # 5 minutes
    
    def needs_refresh(self):
        return (time.time() - self.token_time) > self.max_age
    
    def set_token(self, token):
        self.token = token
        self.token_time = time.time()

Pitfall 2: Inconsistent Fingerprints

Using a Chrome TLS fingerprint with a cURL User-Agent triggers detection.

Solution: Match all fingerprint components:

# All elements should match the same browser
CHROME_CONFIG = {
    "user_agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36",
    "impersonate": "chrome120",
    "headers": {
        "Accept": "text/html,application/xhtml+xml",
        "Accept-Language": "en-US,en;q=0.9",
        "Sec-Ch-Ua": '"Not_A Brand";v="8", "Chromium";v="120"'
    }
}

Pitfall 3: Rate Limit Violations

Sending too many requests triggers blocks even with valid tokens.

Solution: Implement exponential backoff:

import time
import random

def request_with_backoff(url, max_retries=5):
    for attempt in range(max_retries):
        response = make_request(url)
        
        if response.status_code == 429:
            wait_time = (2 ** attempt) + random.uniform(0, 1)
            print(f"Rate limited. Waiting {wait_time:.1f}s")
            time.sleep(wait_time)
        else:
            return response
    
    raise Exception("Max retries exceeded")

Pitfall 4: Session State Loss

Losing cookies between requests breaks authentication.

Solution: Always use session objects:

# Good: Persistent session
session = requests.Session()
session.get("https://site.com/page1")
session.get("https://site.com/page2")  # Cookies preserved

# Bad: New session each time
requests.get("https://site.com/page1")
requests.get("https://site.com/page2")  # Cookies lost

Frequently Asked Questions

Is it legal to bypass AWS WAF?

Accessing publicly available data is generally legal in most jurisdictions. However, always review the target website's Terms of Service.

The bypass techniques themselves are not illegal. Using them to access protected private data or cause harm could be.

How long does an aws-waf-token last?

Token validity varies by website configuration. Most tokens expire within 5-15 minutes. Some sites set longer expiration times.

Always implement token refresh logic in your scraper.

Can I bypass AWS WAF without proxies?

Yes, for low-volume scraping. The open-source token solver and browser automation work from a single IP.

For production-scale scraping, residential proxies are essential.

What's the success rate of each method?

Based on 2025 testing:

Combining methods yields the best results.

Does AWS WAF use machine learning?

Yes. AWS WAF includes AWS Machine Learning rules that analyze request patterns beyond static rules.

This means bypass techniques that work today may become less effective over time.

Advanced: Combining Multiple Methods for Maximum Success

The methods above work well individually. Combining them creates a robust bypass system that handles edge cases.

Architecture for Production Scraping

Here's a battle-tested architecture:

┌──────────────────────────────────────────────────────┐
│                   Request Handler                      │
├──────────────────────────────────────────────────────┤
│  1. Check token cache                                  │
│  2. If token valid → make request with curl_cffi       │
│  3. If token expired → trigger token refresh           │
│  4. If blocked → rotate proxy and retry                │
└──────────────────────────────────────────────────────┘
                          │
                          ▼
┌──────────────────────────────────────────────────────┐
│                  Token Refresh Layer                   │
├──────────────────────────────────────────────────────┤
│  1. Try open-source solver (fast)                      │
│  2. If fails → fall back to browser automation         │
│  3. Cache new token with timestamp                     │
└──────────────────────────────────────────────────────┘
                          │
                          ▼
┌──────────────────────────────────────────────────────┐
│                    Proxy Manager                       │
├──────────────────────────────────────────────────────┤
│  1. Maintain pool of residential proxies               │
│  2. Track success rates per proxy                      │
│  3. Remove failing proxies automatically               │
└──────────────────────────────────────────────────────┘

This layered approach ensures maximum uptime.

Implementation Example

import time
from curl_cffi import requests as curl_requests
from playwright.sync_api import sync_playwright
import random
import threading

class AwsWafBypassEngine:
    def __init__(self, proxies):
        self.proxies = proxies
        self.token_cache = {}
        self.lock = threading.Lock()
        
    def get_token(self, domain):
        """Get valid token, refreshing if needed"""
        with self.lock:
            cached = self.token_cache.get(domain)
            
            if cached and (time.time() - cached['time']) < 300:
                return cached['token']
            
            # Try solver first
            token = self._try_solver(domain)
            
            if not token:
                # Fall back to browser
                token = self._try_browser(domain)
            
            if token:
                self.token_cache[domain] = {
                    'token': token,
                    'time': time.time()
                }
            
            return token

The class manages token lifecycle automatically.

    def _try_solver(self, domain):
        """Attempt token generation via solver"""
        try:
            # Import the solver library
            from awswaf.aws import AwsWaf
            
            # Get challenge parameters
            proxy = random.choice(self.proxies)
            response = curl_requests.get(
                f"https://{domain}",
                impersonate="chrome120",
                proxies={"https": proxy}
            )
            
            # Extract and solve challenge
            # (Implementation depends on solver version)
            return self._extract_and_solve(response.text, domain)
            
        except Exception as e:
            print(f"Solver failed: {e}")
            return None
    
    def _try_browser(self, domain):
        """Fall back to browser automation"""
        try:
            with sync_playwright() as p:
                browser = p.chromium.launch(headless=True)
                context = browser.new_context()
                page = context.new_page()
                
                page.goto(f"https://{domain}")
                time.sleep(5)
                
                cookies = context.cookies()
                for cookie in cookies:
                    if 'aws-waf-token' in cookie['name']:
                        browser.close()
                        return cookie['value']
                
                browser.close()
                return None
                
        except Exception as e:
            print(f"Browser failed: {e}")
            return None

The fallback mechanism ensures you always get a token.

Making Requests with the Engine

    def fetch(self, url):
        """Fetch URL with automatic bypass"""
        from urllib.parse import urlparse
        domain = urlparse(url).netloc
        
        # Get valid token
        token = self.get_token(domain)
        
        if not token:
            raise Exception("Could not obtain valid token")
        
        # Make request with token
        proxy = random.choice(self.proxies)
        
        response = curl_requests.get(
            url,
            impersonate="chrome120",
            cookies={'aws-waf-token': token},
            proxies={"https": proxy}
        )
        
        if response.status_code == 403:
            # Token might be invalid, force refresh
            del self.token_cache[domain]
            return self.fetch(url)  # Retry once
        
        return response

This method handles the complete bypass flow.

Usage

# Initialize with your proxies
proxies = [
    "http://user:pass@residential1.com:8080",
    "http://user:pass@residential2.com:8080",
]

engine = AwsWafBypassEngine(proxies)

# Scrape multiple pages
urls = [
    "https://protected-site.com/page1",
    "https://protected-site.com/page2",
    "https://protected-site.com/page3",
]

for url in urls:
    response = engine.fetch(url)
    print(f"Got {len(response.text)} bytes from {url}")
    time.sleep(random.uniform(2, 5))

AWS WAF Detection Changes Expected in 2026

Based on current AWS announcements and industry trends, expect these changes:

Enhanced Machine Learning Rules

AWS continuously improves their ML models. Expect:

• Better behavioral pattern recognition
• Faster adaptation to new bypass techniques
• Cross-site intelligence sharing

HTTP/3 and QUIC Fingerprinting

As HTTP/3 adoption grows, AWS WAF will fingerprint QUIC connections. Current JA3/JA4 fingerprinting focuses on TLS over TCP.

Prepare by using tools that support HTTP/3 impersonation.

Encrypted Client Hello (ECH)

TLS 1.3 with ECH will change fingerprinting dynamics. While ECH hides some details, new fingerprinting methods will emerge.

Bot Behavior Scoring

Instead of binary block/allow decisions, expect nuanced scoring systems. Requests will receive trust scores based on multiple signals.

Lower scores might trigger CAPTCHAs while higher scores pass through.

Performance Benchmarks

We tested each method against AWS WAF-protected sites in December 2025:

Speed Comparison

The open-source solver offers the best speed when tokens are required.

Success Rate by Site Complexity

*With AI image recognition integration

Browser automation provides the highest reliability but lowest throughput.

Resource Usage

For resource-constrained environments, the solver or curl_cffi are optimal choices.

Troubleshooting Guide

Problem: "403 Forbidden" Despite Valid Token

Causes:

1. Token expired during request
2. IP was blacklisted mid-session
3. Request fingerprint mismatch

Solutions:

# Check token age before each request
if time.time() - token_timestamp > 240:  # 4 min buffer
    token = refresh_token()

# Verify IP isn't blacklisted
response = requests.get("https://httpbin.org/ip", proxies=proxy)
if blocked_check(response):
    proxy = get_new_proxy()

Problem: Challenge Page Returns Empty Parameters

Causes:

1. JavaScript not fully loaded
2. Anti-bot measure blocking initial request
3. Geographic restriction

Solutions:

# Wait for full page load
page.wait_for_load_state('networkidle')
time.sleep(2)

# Check for geographic blocks
response_geo = session.get(url, headers={'Accept-Language': 'en-US'})

Problem: Browser Automation Detected

Causes:

1. WebDriver flag exposed
2. Headless mode artifacts
3. Missing browser features

Solutions:

# Use headed mode
browser = playwright.chromium.launch(headless=False)

# Add extensions to appear more real
context = browser.new_context(
    locale='en-US',
    timezone_id='America/New_York'
)

Problem: High Block Rate with Proxies

Causes:

1. Proxy quality issues
2. Shared proxy abuse
3. Datacenter IPs used as "residential"

Solutions:

• Use verified residential proxy providers
• Monitor per-proxy success rates
• Remove underperforming proxies automatically

Legal and Ethical Considerations

Respecting robots.txt

Always check robots.txt before scraping:

from urllib.robotparser import RobotFileParser

def can_scrape(url):
    parser = RobotFileParser()
    parser.set_url(f"{url}/robots.txt")
    parser.read()
    return parser.can_fetch("*", url)

Rate Limiting Your Requests

Even when bypassing AWS WAF, be respectful:

# Minimum 1 second between requests
MIN_DELAY = 1.0
MAX_DELAY = 3.0

time.sleep(random.uniform(MIN_DELAY, MAX_DELAY))

Data Usage Restrictions

Some data may be public but still protected by:

• Copyright law
• Database rights (EU)
• Terms of service agreements

Consult legal counsel for commercial scraping projects.

Conclusion

You now have four proven methods to bypass AWS WAF protection in 2026:

1. Open-source token solver for direct token generation
2. Browser automation for reliable challenge completion
3. TLS fingerprint spoofing for lightweight HTTP requests
4. Residential proxy rotation for IP diversity

The most effective approach combines multiple methods. Use browser automation to establish sessions, then maintain them with proper TLS fingerprints and rotating proxies.

Start with the simplest solution for your use case. Add complexity only when needed.

For high-volume projects, the open-source Golang solver offers the best performance. For occasional scraping, Playwright with stealth plugins is easier to set up and maintain.

Stay updated on AWS WAF changes. Their detection methods evolve continuously. What works today may need adjustment tomorrow.