Fastly Antibot is a sophisticated protection system designed to block automated web scrapers. This system uses advanced traffic analysis and device fingerprinting to distinguish humans from bots.
In this guide, you'll learn multiple proven techniques to bypass Fastly's defenses, from simple API solutions to advanced browser automation.
We'll provide working code examples and explain the underlying mechanisms that make these bypass methods effective.
The main challenge with Fastly Antibot is its multi-layered detection system. It combines IP reputation checks, behavioral analysis, and JavaScript challenges to identify and block bots.
Successful bypassing requires mimicking human behavior across all these detection vectors.
How Fastly's Bot Detection Works
Fastly uses sophisticated bot classification that goes beyond simple user-agent checks.
The system analyzes traffic patterns to detect robotic behavior like making requests too quickly.
It also collects detailed device fingerprints including plugins, screen resolution, and language settings.
Additionally, Fastly maintains IP reputation databases to block addresses associated with known bot activity .
The system employs active challenges like JavaScript execution tests and CAPTCHAs that traditional scrapers cannot handle. It also performs passive behavior analysis, monitoring for human signals like mouse movements and scrolling patterns.
Rate limiting and custom blocking rules provide additional protection layers that can instantly stop scrapers .
Method 1: Using fastly-antibot solver
Open sourced Github fastly anitbot solver helps to handle bypass complexity automatically. Services like ScraperAPI manage proxy rotation, JavaScript rendering, and header management.
This approach requires minimal code changes while providing high success rates against Fastly's protections .
Here's a complete Go (golang) implementation using fastly-anitbot to bypass Fastly:
package main
import (
"fmt"
"github.com/pagpeter/fastify/pkg/solver"
)
func main() {
s, _ := solver.NewFastifySolver("https://pypi.org/search/?q=django")
cookie, _ := s.Solve()
fmt.Println(cookie)
}The render='true' parameter is crucial because it enables JavaScript rendering servers.
This allows the request to pass Fastly's JavaScript challenges that would normally block basic HTTP clients.
Method 2: Browser Automation with Stealth Techniques
Browser automation tools can mimic human behavior when properly configured.
However, standard Selenium and Puppeteer implementations leak automation fingerprints that Fastly easily detects. You need fortified versions with stealth plugins to avoid detection .
Here's a stealth-enhanced implementation using Puppeteer-Extra:
const puppeteer = require('puppeteer-extra');
const StealthPlugin = require('puppeteer-extra-plugin-stealth')();
puppeteer.use(StealthPlugin);
(async () => {
const browser = await puppeteer.launch({
headless: true,
args: ['--no-sandbox', '--disable-setuid-sandbox']
});
const page = await browser.newPage();
// Set a realistic viewport
await page.setViewport({width: 1920, height: 1080});
// Navigate to the protected site
await page.goto('https://www.fastly-protected-site.com', {
waitUntil: 'networkidle2'
});
// Your scraping logic here
const content = await page.content();
console.log(content);
await browser.close();
})();
The stealth plugin patches numerous automation leaks that Fastly monitors.
It removes webdriver flags, masks headless browser characteristics, and randomizes fingerprintable attributes. This makes the automated browser nearly indistinguishable from a human-controlled one to Fastly's detection systems .
For Python developers, SeleniumBase with Undetected ChromeDriver provides similar stealth capabilities:
from seleniumbase import Driver
# Initialize driver with undetected mode
driver = Driver(uc=True, headless=True)
# Open URL with reconnection capability
url = "https://www.fastly-protected-site.com"
driver.uc_open_with_reconnect(url, reconnect_time=6)
# Your scraping logic here
page_content = driver.get_page_source()
print(page_content)
driver.quit()
Method 3: Advanced HTTP-Only Bypass
For high-performance scraping needs, browser automation may be too resource-intensive.
Advanced HTTP bypass techniques using libraries like tls-client can mimic real browser TLS fingerprints without the overhead of a full browser .
This Python implementation uses tls-client to emulate Chrome's TLS fingerprint:
import tls_client
# Create a session with Chrome emulation
session = tls_client.Session(
client_identifier="chrome_108",
random_tls_extension_order=True
)
# Set realistic headers
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/108.0.0.0 Safari/537.36',
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8',
'Accept-Language': 'en-US,en;q=0.5',
'Accept-Encoding': 'gzip, deflate, br',
'Connection': 'keep-alive',
}
response = session.get(
"https://www.fastly-protected-site.com",
headers=headers
)
print(response.status_code)
print(response.text)
The key advantage of tls-client is its ability to emulate specific browser TLS fingerprints.
Fastly and other advanced protections analyze JA3 signatures and TLS handshake characteristics to detect automation tools.
This library helps your requests match the TLS profile of real browsers .
Method 4: Residential Proxies with IP Rotation
Fastly tracks IP reputation and request patterns.
Using datacenter proxies or making too many requests from a single IP will quickly get you blocked. Residential proxies with automatic rotation are essential for large-scale scraping .
This Python implementation combines requests with a rotating proxy service:
import requests
import random
# List of residential proxies
proxies_list = [
'http://user:pass@proxy1.example.com:8080',
'http://user:pass@proxy2.example.com:8080',
'http://user:pass@proxy3.example.com:8080',
]
# Rotate user agents
user_agents = [
'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/108.0.0.0 Safari/537.36',
'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/16.1 Safari/605.1.15',
'Mozilla/5.0 (X11; Linux x86_64; rv:108.0) Gecko/20100101 Firefox/108.0'
]
def make_request(url):
proxy = random.choice(proxies_list)
user_agent = random.choice(user_agents)
headers = {'User-Agent': user_agent}
proxies = {'http': proxy, 'https': proxy}
response = requests.get(url, headers=headers, proxies=proxies, timeout=30)
return response
response = make_request('https://www.fastly-protected-site.com')
print(response.status_code)
Residential proxies use IP addresses from real Internet Service Providers, making them appear as regular user traffic to Fastly.
Combined with user-agent rotation and realistic request timing, this approach significantly reduces blocking probability for medium-volume scraping .
Method 5: Mobile API Endpoints and Alternative Access Points
Many websites maintain separate infrastructure for their mobile applications.
These mobile API endpoints often have lighter security implementations than the main website. Fastly protections might be completely absent or simplified on these alternative access points .
To discover mobile endpoints, you can use several approaches. Monitor network traffic from official mobile apps using tools like mitmproxy or Charles Proxy.
Look for subdomains like m.example.com, mobile.example.com, or api.example.com. Also check for path patterns containing /mobile/, /m/, or /api/v2/ .
Here's how to leverage discovered endpoints:
import requests
# Mobile API endpoint (discovered through traffic analysis)
mobile_url = "https://api.target-site.com/mobile/v2/content"
headers = {
'User-Agent': 'Mozilla/5.0 (Linux; Android 10; SM-G973F) AppleWebKit/537.36',
'Accept': 'application/json',
'X-API-Key': 'optional_api_key_if_required'
}
response = requests.get(mobile_url, headers=headers)
if response.status_code == 200:
data = response.json()
# Process the JSON data
print(data)
Mobile endpoints typically return structured data like JSON, which is often easier to parse than HTML.
The protection layers on these endpoints are frequently less aggressive, as they assume requests come from trusted official applications .
Troubleshooting Common Issues
Even with proper implementation, you may encounter blocking. Here are solutions for common problems:
If you're getting 403 Forbidden errors, your request fingerprint is likely being detected. Try switching to a different TLS client fingerprint or browser profile. Add more human-like headers such as Accept-Language and Sec-Ch-Ua .
For 429 Too Many Requests responses, you're hitting rate limits. Implement exponential backoff in your request timing and increase your proxy pool size. Add random delays between requests to mimic human browsing patterns more closely .
When facing CAPTCHA challenges, consider integrating a solving service like 2Captcha or Anti-Captcha. For persistent CAPTCHAs, switch to residential proxies with higher reputation scores or reduce your request rate .
Best Practices for Long-Term Success
Successful Fastly bypassing requires ongoing adaptation. Here are strategies for maintaining access:
Regularly update your fingerprints and automation tools. Fastly continuously improves detection, so what works today might fail tomorrow. Keep your browser emulation and TLS fingerprints current with real browser versions .
Implement comprehensive monitoring to detect when your scraping starts getting blocked. Track success rates, response codes, and CAPTCHA frequency. Set up alerts for increased failure rates so you can adapt quickly .
Use a hybrid approach combining multiple techniques. For example, use residential proxies with TLS fingerprint emulation and occasional browser automation for particularly challenging endpoints. Diversification makes your scraping more resilient to detection improvements .
Conclusion
Bypassing Fastly Antibot requires understanding their multi-layered detection approach and implementing corresponding countermeasures.
The most effective strategy combines proper TLS fingerprinting, residential proxy rotation, and behavioral mimicry.
For most developers, specialized scraping APIs provide the easiest starting point with good success rates.
As your needs grow or change, you can implement more customized solutions using the browser automation and HTTP bypass techniques covered in this guide.
Remember to always respect robots.txt, terms of service, and applicable laws when scraping.
Use these techniques only on sites where you have permission to access data, and implement reasonable rate limiting to avoid overwhelming target servers.
