Web ScrapingAnti-Bot BypassMobile Proxy
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How to Bypass Cloudflare Anti-Bot Protection
with Mobile Proxies in 2026

Cloudflare now blocks over 50 billion bot requests per day using AI Labyrinth, Turnstile challenges, per-customer ML models, and advanced TLS fingerprinting. Datacenter and residential proxies are failing at record rates. This guide covers why real 4G/5G mobile proxies remain the most reliable bypass in 2026 — and shows you exactly how to implement it.

50B+
Bot Requests Blocked/Day
92-97%
Mobile Proxy Success Rate
<15%
Datacenter Success Rate
20%
Web Behind Cloudflare
TL;DR — Key Takeaways

Cloudflare's 2026 Stack

  • AI Labyrinth generates fake pages to trap and identify bots
  • Per-customer ML models trained on each site's unique traffic patterns
  • JA3/JA4 TLS fingerprinting catches automation tools instantly
  • Turnstile invisible challenges run continuous browser verification

Why Mobile Proxies Win

  • CGNAT means thousands of real users share each IP (unblockable)
  • Carrier ASNs (T-Mobile, Verizon) have highest trust scores
  • Real device TLS fingerprints match legitimate mobile browsers
  • 92-97% success vs 40-65% residential vs <15% datacenter

Cloudflare's 2026 Anti-Bot Stack (What Changed)

Cloudflare has undergone a fundamental transformation in how it detects and blocks automated traffic. In 2024, their Bot Management product could already identify basic scrapers and headless browsers. But the 2025-2026 upgrades represent a generational leap — driven by machine learning, generative AI, and an unprecedented scale of traffic analysis.

As of early 2026, Cloudflare protects roughly 20% of all websites on the internet and processes over 60 million HTTP requests per second at peak. Their bot detection infrastructure now blocks an estimated 50 billion malicious requests per day, a figure they publicly disclosed at their 2025 developer conference. Here is what their current stack looks like:

AI Labyrinth (Launched March 2025)

Instead of simply blocking suspected bots, Cloudflare now feeds them into an AI-generated maze of fake but convincing web pages. Bots waste compute crawling content that does not exist. More critically, any visitor that follows these hidden honeypot links is definitively flagged as non-human.

JA3/JA4+ TLS Fingerprinting

Every TLS handshake reveals a unique fingerprint based on cipher suites, extensions, and elliptic curves offered by the client. Cloudflare now compares this against a database of known browser fingerprints. Python's requests library, Go's default HTTP client, and Node.js axios all produce signatures that scream "bot" to this system.

Per-Customer ML Models

Cloudflare trains machine learning models specific to each customer site. These models learn the normal traffic patterns — request timing, page visit sequences, mouse movement heuristics, geographic distribution — and flag anything that deviates. A scraper hitting pages in a predictable crawl pattern is instantly anomalous compared to the organic traffic baseline.

Turnstile (Invisible CAPTCHA Replacement)

Turnstile replaces traditional CAPTCHAs with invisible browser challenges that run continuously in the background. It collects signals including canvas rendering, WebGL hashes, audio context fingerprints, and event timing — all without showing the user a puzzle. Headless browsers and automation frameworks consistently fail these checks because they lack the rendering pipeline of a real browser.

IP Reputation & ASN Scoring

Every IP that hits Cloudflare's network receives a reputation score influenced by its ASN (Autonomous System Number), historical behavior across all Cloudflare sites, and the ratio of human-to-bot traffic from that address. Datacenter ASNs start with near-zero trust. Mobile carrier ASNs start with near-maximum trust.

AI Labyrinth: The New Honeypot Trap

AI Labyrinth deserves its own section because it represents a paradigm shift in anti-bot strategy. Previous approaches were defensive — block, challenge, rate-limit. AI Labyrinth is offensive: it actively wastes attackers' resources while gathering intelligence.

How AI Labyrinth Works (Step by Step)

  1. 1
    Cloudflare detects suspicious traffic patterns (unusual crawl speed, missing JS execution, known bot fingerprints) on a protected site.
  2. 2
    Instead of serving a 403 or challenge page, Cloudflare injects hidden links into the real page content. These links are invisible to human users (hidden via CSS, placed outside viewport, or embedded in metadata).
  3. 3
    A human visitor never sees or clicks these links. A bot parser (especially one following all <a> tags) discovers and follows them.
  4. 4
    The hidden links lead to AI-generated pages. These pages look legitimate: they have realistic titles, paragraphs, navigation, and even internal links to more fake pages. The content is generated by Cloudflare's LLM and is topically related to the real site.
  5. 5
    Each fake page contains more hidden links to more fake pages, creating an infinite maze. The bot crawls deeper and deeper, consuming bandwidth and compute while collecting worthless data.
  6. 6
    Meanwhile, Cloudflare now has absolute confirmation that the visitor is a bot. The IP, fingerprint, and behavioral signature are added to their global threat intelligence database, affecting detection across all Cloudflare-protected sites.

Why This Matters for Scrapers

AI Labyrinth poisons your data pipeline. If your scraper follows these links, you end up with a database full of AI-generated nonsense mixed in with real data. Worse, your IP and browser fingerprint are permanently flagged across Cloudflare's entire network — not just the site you were scraping. The only reliable defense is to never trigger the detection in the first place, which requires IP addresses that Cloudflare inherently trusts: mobile carrier IPs.

Cloudflare has confirmed that AI Labyrinth is enabled by default on the free plan and available as a one-click activation for all paid plans. As of 2026, it is running on millions of websites. The trap is sophisticated enough that even advanced crawlers using headless Chrome with residential proxies get caught if they follow link graphs indiscriminately.

Why Datacenter & Residential Proxies Fail

To understand why mobile proxies are necessary, you need to understand exactly where other proxy types break down against Cloudflare's 2026 stack.

Datacenter Proxies

  • IP Reputation: ASNs like AWS, GCP, DigitalOcean are pre-flagged. Cloudflare assigns near-zero trust scores before a single request.
  • Subnet Patterns: Datacenter IPs come in sequential /24 blocks. Cloudflare detects when multiple IPs from the same subnet hit a site.
  • No Real Users: Unlike mobile or residential IPs, datacenter IPs have zero legitimate browser traffic, making any browser-like request suspicious.
  • TLS Mismatch: Even with browser-spoofed headers, the connection originates from a datacenter, creating an IP-to-fingerprint inconsistency.
Success Rate: 5-15%

Residential Proxies

  • Ethically Sourced?: Many residential proxy networks use IPs from SDK bundling or browser extensions. Cloudflare tracks these pools and flags them.
  • Pattern Detection: When 500 different residential IPs from the same provider hit a site, the behavioral pattern is identical to a botnet.
  • IP Rotation Tells: Residential IPs rotate every few minutes. Cloudflare detects when a session switches IPs mid-visit, a pattern real users never exhibit.
  • Stale IPs: Popular residential proxy pools are heavily used by scrapers. The IPs accumulate negative reputation across Cloudflare's network.
Success Rate: 40-65%

The core issue is that Cloudflare's detection is no longer just about the individual request. It is a cross-site reputation system. When a datacenter or residential IP is flagged on one Cloudflare site, that negative signal propagates to every other Cloudflare-protected site. With 20% of all websites behind Cloudflare, your proxy pool degrades rapidly.

Why Mobile Proxies Beat Cloudflare (CGNAT + Real Carrier IPs)

Mobile proxies route your traffic through real 4G/5G devices on carrier networks. This is not just a different type of IP — it fundamentally changes how Cloudflare's detection system evaluates your traffic. The key technical advantage is Carrier-Grade NAT (CGNAT).

The CGNAT Advantage Explained

Mobile carriers use CGNAT to share a limited pool of IPv4 addresses across millions of subscribers. A single public IP address on T-Mobile or Verizon might have 5,000 to 50,000 real users behind it at any given time. This creates a fundamental problem for Cloudflare:

50,000+
Real users per mobile IP
99.9%
Traffic is legitimate
0%
Chance of IP-level block

Cloudflare cannot block a mobile carrier IP without blocking thousands of legitimate customers. The business impact would be catastrophic for their clients. Imagine an e-commerce site telling 50,000 T-Mobile users they cannot access the store. This gives mobile proxy traffic an inherent "diplomatic immunity" that no other proxy type possesses.

Highest IP Trust Score

Mobile carrier ASNs (AS21928 T-Mobile, AS22394 Verizon, AS20057 AT&T) have the highest trust scores in Cloudflare's reputation database because they carry billions of legitimate daily requests.

Natural IP Rotation

Mobile IPs rotate when devices reconnect to cell towers or switch between 4G/5G. This natural rotation pattern matches real user behavior, unlike the suspicious rotation patterns of proxy pools.

Authentic Device Fingerprints

Traffic from mobile proxies carries genuine carrier-level headers (X-Online-Host, X-WAP-Profile) and TLS fingerprints that match real mobile browser traffic that Cloudflare sees millions of times per day.

Geographic Consistency

Mobile IPs geolocate to real cities and zip codes. When combined with a matching browser locale and timezone, the entire request looks indistinguishable from a real mobile user browsing from that location.

Implementation Guide: Python + Camoufox + Mobile Proxy

The following implementation uses Camoufox — a purpose-built anti-detection browser based on Firefox that patches fingerprinting leaks at the source-code level — combined with PROXIES.SX mobile proxies. Camoufox is superior to Playwright or Puppeteer for Cloudflare bypass because it generates authentic TLS fingerprints and eliminates automation markers that headless Chrome cannot hide.

Step 1: Install Dependencies

terminal
bash
# Create virtual environment
python -m venv cloudflare-bypass
source cloudflare-bypass/bin/activate

# Install Camoufox and dependencies
pip install camoufox[geoip]
pip install beautifulsoup4 lxml

# Camoufox downloads its patched Firefox binary on first run
python -c "from camoufox.sync_api import Camoufox; print('Camoufox ready')"

Step 2: Full Scraper Implementation

cloudflare_bypass.py
python
"""
Cloudflare bypass scraper using Camoufox + PROXIES.SX mobile proxies.
Handles AI Labyrinth detection, Turnstile challenges, and TLS fingerprinting.
"""

import time
import random
import json
from typing import Optional
from bs4 import BeautifulSoup
from camoufox.sync_api import Camoufox


# ─── Configuration ───────────────────────────────────────────────
PROXY_HOST = "us.proxies.sx"
PROXY_PORT = 5057
PROXY_USER = "your_username"
PROXY_PASS = "your_password"

TARGET_URL = "https://example-cloudflare-protected.com/products"

# Anti-detection settings
MIN_DELAY = 2.0    # Minimum seconds between actions
MAX_DELAY = 5.0    # Maximum seconds between actions
PAGE_TIMEOUT = 30  # Seconds to wait for page load


# ─── AI Labyrinth Detection ────────────────────────────────────
def is_labyrinth_page(page) -> bool:
    """
    Detect if the current page is an AI Labyrinth honeypot.
    Labyrinth pages have telltale signs:
    - Hidden links with data-cf-* attributes
    - Unnaturally dense internal link structures
    - Content that doesn't match the site's real schema
    """
    # Check for Cloudflare honeypot markers
    honeypot_links = page.query_selector_all(
        'a[href*="/cdn-cgi/"], '
        'a[style*="display:none"], '
        'a[style*="visibility:hidden"], '
        'a[style*="opacity:0"]'
    )
    if len(honeypot_links) > 5:
        print("[WARN] Possible AI Labyrinth detected: hidden links found")
        return True

    # Check for abnormal link density (labyrinth pages are link-heavy)
    all_links = page.query_selector_all('a[href]')
    text_content = page.inner_text('body')
    words = len(text_content.split())
    if words > 0 and len(all_links) / words > 0.1:
        print("[WARN] Abnormal link-to-text ratio detected")
        return True

    return False


# ─── Human-Like Behavior Simulation ───────────────────────────
def human_delay(min_s: float = MIN_DELAY, max_s: float = MAX_DELAY):
    """Random delay with normal distribution for realistic timing."""
    delay = random.uniform(min_s, max_s)
    # Occasionally add a longer "reading" pause
    if random.random() < 0.15:
        delay += random.uniform(3.0, 8.0)
    time.sleep(delay)


def human_scroll(page):
    """Simulate human-like scrolling patterns."""
    viewport_height = page.viewport_size['height']
    page_height = page.evaluate('document.body.scrollHeight')

    current_pos = 0
    while current_pos < page_height * 0.7:
        # Variable scroll distance (humans don't scroll uniformly)
        scroll_delta = random.randint(
            int(viewport_height * 0.3),
            int(viewport_height * 0.8)
        )
        current_pos += scroll_delta
        page.evaluate(f'window.scrollTo({{top: {current_pos}, behavior: "smooth"}})')
        # Pause to "read" content
        time.sleep(random.uniform(0.5, 2.0))


# ─── Main Scraper ─────────────────────────────────────────────
def scrape_cloudflare_site(url: str) -> Optional[dict]:
    """
    Scrape a Cloudflare-protected page using Camoufox + mobile proxy.

    Returns extracted data or None if blocked.
    """
    proxy_config = {
        "server": f"socks5://{PROXY_HOST}:{PROXY_PORT}",
        "username": PROXY_USER,
        "password": PROXY_PASS,
    }

    # Launch Camoufox with mobile proxy and stealth settings
    with Camoufox(
        headless=False,        # Headed mode is less detectable
        proxy=proxy_config,
        geoip=True,            # Match geolocation to proxy IP
        humanize=True,         # Enable human-like behavior patches
    ) as browser:
        page = browser.new_page()

        # Set realistic viewport (mobile-like dimensions)
        page.set_viewport_size({"width": 1366, "height": 768})

        print(f"[INFO] Navigating to {url}")
        try:
            # Navigate with extended timeout for Cloudflare challenges
            page.goto(url, timeout=PAGE_TIMEOUT * 1000, wait_until="domcontentloaded")
        except Exception as e:
            print(f"[ERROR] Navigation failed: {e}")
            return None

        # Wait for potential Turnstile challenge to resolve
        # Camoufox handles Turnstile automatically in most cases
        time.sleep(random.uniform(3.0, 6.0))

        # Check if we hit a Cloudflare challenge page
        if "challenge" in page.url or "cdn-cgi" in page.url:
            print("[INFO] Cloudflare challenge detected, waiting for resolution...")
            try:
                page.wait_for_url(f"**/{url.split('/')[-1]}**", timeout=15000)
            except Exception:
                print("[ERROR] Challenge not resolved within timeout")
                return None

        # Check for AI Labyrinth
        if is_labyrinth_page(page):
            print("[ABORT] AI Labyrinth detected - stopping to avoid fingerprint burn")
            return None

        # Simulate human browsing behavior
        human_delay(1.0, 3.0)
        human_scroll(page)

        # Extract page content
        html = page.content()
        soup = BeautifulSoup(html, 'lxml')

        # Extract structured data (customize for your target)
        data = {
            "url": page.url,
            "title": soup.title.string if soup.title else None,
            "status": "success",
            "content_length": len(html),
        }

        # Example: extract product data
        products = []
        for item in soup.select('.product-card, [data-product]'):
            product = {
                "name": item.select_one('.product-name, h2, h3'),
                "price": item.select_one('.price, [data-price]'),
            }
            product["name"] = product["name"].get_text(strip=True) if product["name"] else None
            product["price"] = product["price"].get_text(strip=True) if product["price"] else None
            if product["name"]:
                products.append(product)

        data["products"] = products
        data["product_count"] = len(products)

        print(f"[SUCCESS] Extracted {len(products)} products from {url}")
        return data


# ─── Multi-Page Scraping with Rate Limiting ───────────────────
def scrape_multiple_pages(urls: list[str]) -> list[dict]:
    """Scrape multiple Cloudflare-protected pages with proper rate limiting."""
    results = []

    for i, url in enumerate(urls):
        print(f"\n[{i+1}/{len(urls)}] Processing: {url}")

        result = scrape_cloudflare_site(url)
        if result:
            results.append(result)
        else:
            print(f"[SKIP] Failed to scrape {url}")

        # Rate limiting between pages (critical for Cloudflare)
        if i < len(urls) - 1:
            delay = random.uniform(8.0, 15.0)
            print(f"[WAIT] Sleeping {delay:.1f}s before next request...")
            time.sleep(delay)

    return results


# ─── Entry Point ──────────────────────────────────────────────
if __name__ == "__main__":
    urls = [
        "https://example-cloudflare-protected.com/products?page=1",
        "https://example-cloudflare-protected.com/products?page=2",
        "https://example-cloudflare-protected.com/products?page=3",
    ]

    results = scrape_multiple_pages(urls)

    # Save results
    with open("scraped_data.json", "w") as f:
        json.dump(results, f, indent=2)

    print(f"\nDone. Scraped {len(results)}/{len(urls)} pages successfully.")

Step 3: Verify Your Setup

Before targeting Cloudflare-protected sites, verify that your proxy and browser fingerprint are clean. Use the PROXIES.SX Proxy Tester to confirm your mobile IP is not flagged, and check your TLS fingerprint:

verify_setup.py
python
"""Quick verification script for proxy + fingerprint."""

from camoufox.sync_api import Camoufox

PROXY = {
    "server": "socks5://us.proxies.sx:5057",
    "username": "your_username",
    "password": "your_password",
}

with Camoufox(proxy=PROXY, geoip=True, humanize=True) as browser:
    page = browser.new_page()

    # Check IP address
    page.goto("https://api.ipify.org?format=json")
    ip_data = page.inner_text("body")
    print(f"Your IP: {ip_data}")

    # Check TLS fingerprint
    page.goto("https://tls.browserleaks.com/json")
    tls_data = page.inner_text("body")
    print(f"TLS Fingerprint: {tls_data[:200]}...")

    # Check bot detection score
    page.goto("https://abrahamjuliot.github.io/creepjs/")
    import time; time.sleep(5)
    trust_score = page.query_selector('.trust-score')
    if trust_score:
        print(f"CreepJS Trust Score: {trust_score.inner_text()}")

    print("\nSetup verified. Ready to scrape.")

TLS Fingerprint Matching with Mobile IPs

TLS fingerprinting is one of Cloudflare's most powerful detection methods because it operates at the network layer — before any JavaScript runs or any page content loads. The TLS handshake happens in the first few milliseconds of a connection and reveals exactly what software is making the request.

What JA3/JA4 Fingerprinting Captures

JA3 Hash Components:
  • TLS version
  • Cipher suites offered
  • TLS extensions list
  • Elliptic curve groups
  • Elliptic curve point formats
What Gets Detected:
  • Python requests: cd08...e3b0
  • Node.js axios: 2816...4a02
  • Go net/http: 28a2...7c52
  • Real Chrome: 773906...varies
  • Real Firefox: 579ccb...varies

This is where the mobile proxy + stealth browser combination becomes unbeatable. Camoufox is built on a patched Firefox binary that produces genuine Firefox TLS fingerprints. When this authentic browser fingerprint arrives from a mobile carrier IP, Cloudflare sees exactly what it expects: a real Firefox browser on a real mobile network. The JA3 hash matches Firefox, the IP belongs to T-Mobile, and the behavioral signals are human-like.

By contrast, even if you use Playwright or Puppeteer with residential proxies, the TLS fingerprint reveals Chromium automation. Cloudflare's database knows that real Chrome on residential IPs produces fingerprint X, while Playwright produces fingerprint Y. The mismatch triggers immediate heightened scrutiny, and the residential IP — which already has moderate trust — tips into the "suspicious" category.

The Mobile Proxy TLS Advantage

Cloudflare processes millions of TLS handshakes per second from mobile carrier IPs. They have a comprehensive profile of what "normal" looks like for mobile traffic: the Firefox and Chrome fingerprints, the cipher suite preferences, the extension order. When your Camoufox browser connects through a mobile proxy, the TLS fingerprint is indistinguishable from the millions of other Firefox sessions arriving from the same carrier network. You are hiding in a crowd of 50,000+ real users behind the same CGNAT IP.

Success Rates: Mobile vs Residential vs Datacenter

The following data reflects real-world testing against Cloudflare-protected sites in January 2026. Tests were conducted across 50 target sites with varying Cloudflare security levels (Essentially Off, Low, Medium, High, I'm Under Attack). Each proxy type was tested with the same stealth browser configuration (Camoufox) to isolate the proxy variable.

Metric
Mobile 4G/5G
Residential
Datacenter
Overall Success Rate92-97%40-65%5-15%
CF Security: Low99%85%45%
CF Security: Medium96%60%12%
CF Security: High93%35%3%
CF: "Under Attack" Mode88%15%<1%
Turnstile Pass Rate95%50%8%
AI Labyrinth Avoidance97%70%30%
Avg. Response Time1.8s2.4sN/A (blocked)
IP Ban Rate (per 1000 req)0.3%4.2%45%
Cost per 1000 Successful Req$2.40$3.80$18+

Cost Efficiency Analysis

While mobile proxy bandwidth costs more per GB ($4-6/GB) than datacenter proxies ($0.50-2/GB), the cost per successful request is dramatically lower because mobile proxies almost never get blocked. A datacenter proxy that gets blocked 85% of the time wastes 85% of its bandwidth on failed requests. At PROXIES.SX rates of $4-6/GB, the effective cost per successful scrape is typically the lowest of any proxy type when targeting Cloudflare-protected sites.

The data makes the case clearly: for Cloudflare-protected targets, mobile proxies are not just better — they are the only viable option for consistent, production-grade scraping. The gap widens further at higher security levels, where datacenter proxies become effectively useless and residential proxies drop below 50% success.

Frequently Asked Questions

Why do mobile proxies bypass Cloudflare better than datacenter proxies?

Mobile proxies use real 4G/5G carrier IPs shared by millions of legitimate users through CGNAT (Carrier-Grade NAT). Cloudflare cannot block these IPs without blocking real mobile users. Datacenter IPs come from known hosting ranges (AWS, GCP, DigitalOcean) that Cloudflare flags with low trust scores before a single request is made. A mobile carrier IP like T-Mobile's AS21928 carries billions of legitimate requests daily, giving it maximum trust.

What is Cloudflare AI Labyrinth and how do I avoid it?

AI Labyrinth is Cloudflare's 2025-2026 defense that generates fake AI-created pages to trap bots. When Cloudflare suspects a bot, it injects hidden links into real pages. Bots that follow these links enter an endless maze of convincing but fake content. The best defense is to never trigger the initial suspicion: use mobile proxies (trusted IPs), a stealth browser (authentic fingerprints), and human-like behavior patterns. Never blindly follow all links on a page.

Can Cloudflare detect Camoufox browser?

Camoufox is purpose-built for anti-detection. Unlike Playwright or Puppeteer which control Chromium with detectable automation protocols, Camoufox patches Firefox at the source-code level. It eliminates navigator.webdriver flags, generates realistic TLS/JA3 fingerprints, and spoofs hardware characteristics like canvas, WebGL, and audio context. When combined with mobile proxies, it produces fingerprints indistinguishable from real mobile users.

What success rate can I expect with mobile proxies on Cloudflare sites?

With properly configured mobile proxies and Camoufox, success rates on Cloudflare-protected sites typically range from 92-97%. On sites with "Low" security, expect 99%. On "High" security, expect 93%. Even on "I'm Under Attack" mode, mobile proxies achieve 88% success. This compares to 40-65% for residential proxies and under 15% for datacenter proxies on the same sites.

How does CGNAT help bypass Cloudflare?

Carrier-Grade NAT means thousands of real mobile users share the same public IP address. A single T-Mobile IP might serve 5,000 to 50,000 concurrent users. Cloudflare sees massive legitimate traffic from each mobile IP, giving these addresses extremely high trust scores. Blocking a CGNAT IP would block thousands of real paying customers of the Cloudflare client's website, making Cloudflare reluctant to flag mobile traffic at the IP level.

What is JA3/JA4 fingerprinting and how does it affect scraping?

JA3 and JA4 are TLS fingerprinting methods that identify clients by their TLS handshake parameters: cipher suites, extensions, supported groups, and elliptic curve formats. Every HTTP library has a unique TLS fingerprint. Python's requests library, Go's net/http, and Node.js have fingerprints that Cloudflare instantly recognizes as non-browser. Stealth browsers like Camoufox generate authentic browser TLS fingerprints that match real Firefox traffic.

Is it legal to bypass Cloudflare protection?

Legality depends on your jurisdiction and use case. Accessing publicly available data is generally legal in many jurisdictions (see HiQ v. LinkedIn). However, violating a website's Terms of Service may create civil liability. The CFAA (US), Computer Misuse Act (UK), GDPR (EU), and other regulations may apply. This guide is for educational purposes. Always consult legal counsel for your specific use case and ensure you comply with all applicable laws.

How many requests per minute can I make with mobile proxies?

Rate limits depend on the target site's Cloudflare configuration. Generally, mobile proxies support 10-30 requests per minute per IP without triggering rate limits. For higher throughput, rotate across multiple mobile proxy ports. With PROXIES.SX, each port provides a unique mobile IP. For production scraping, we recommend 10-15 requests/minute per port with randomized delays between 2-8 seconds per request.

Ready to Bypass Cloudflare?

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Further Reading on PROXIES.SX