Why mobile proxies are harder to block (Thanks to CGNAT)

Most websites use strict rules to block automation. However, automation through mobile proxies is harder for them to detect. The reason behind this lies in a network setup called Carrier-Grade NAT (CGNAT), which mobile carriers use to manage IP addresses.

Whether you're scraping the web, verifying ads, or registering accounts at scale, understanding CGNAT could be the difference between success and getting blocked. So, let’s dive into the details.

What is CGNAT?

Carrier-Grade NAT (CGNAT) is a network-level method mobile carriers use to conserve public IP addresses. It allows hundreds of subscribers to access the internet through a single, shared IPv4 address.

Why CGNAT makes mobile proxies harder to block

CGNAT not only assigns IP addresses but also reshapes how traffic appears to a detection system. Instead of isolated patterns, websites face a confusing stream of overlapping behavior that defies ordinary filtering.

It effectively accomplishes this in the following ways:

Shared IP reputation

Websites often assign a reputation to individual IPs, associating them with a single user's activity history. With a CGNAT IP, this assumption gets broken because one IP serves hundreds of unrelated mobile users.

Every request from a CGNAT IP contributes to a shared behavior pool that’s impossible to isolate accurately.

If one scraper triggers a flag, websites risk punishing others who share no connection to that behavior.

Because of this, sites often choose leniency over aggression. They don’t want to interfere with legitimate visitors. That’s why mobile proxies can operate for extended periods, even when scraping aggressively or at scale.

High churn of IP assignments

Mobile networks rarely assign IPs to a single device for extended periods. Disconnections, tower switching, and bandwidth management lead to frequent churn in IP address allocations.

Every time this happens, a scraper appears to come from a new source, evading persistent tracking attempts. The changes happen behind the scenes, without disrupting the session or triggering anti-bot alarms directly.

Scrapers using mobile proxies benefit from this built-in churn that residential and datacenter networks can’t replicate. Even advanced tools struggle to follow identity across rotating CGNAT IPs with no fixed connection trail.

Real mobile device patterns

Websites often profile user behavior using signals such as screen resolution, connection delay, hardware acceleration timing, etc. Mobile proxies relay those signals through real devices, making it challenging to detect automation.

Because CGNAT mixes traffic with real usage, detectors lose the patterns they depend on to flag suspicious behaviors. The undertaking becomes difficult since device fingerprinting varies naturally across mobile traffic.

Typically, mobile users exhibit variable activity, such as app refreshes, background requests, and unpredictable session shifts. This randomness provides effective camouflage, allowing your scrapers to operate under conditions that mimic everyday usage.

Carrier trust

Most telecom providers operate within trusted Autonomous System Numbers (ASNs), which identify owners of specific IP routes. These ASNs allows online platforms to recognize large networks, and telecom-owned ones are typically considered low-risk.

Blocking one address could disrupt access for customers relying on basic connectivity and mobile services. Because of this, most websites apply caution when assessing traffic from within a CGNAT IP pool.

This trust buffer allows your mobile proxies to maintain access, even when engaging in aggressive scraping campaigns. Unlike datacenter providers, telecoms offer an environment where a mobile carrier’s reputation naturally mitigates risk.

Comparing CGNAT with residential proxies

CGNAT and residential proxies may look similar on the surface, but their underlying IP behavior reveals critical differences. While residential IP addresses stay fixed per user, Carrier-Grade NAT shares and rotates IP addresses across multiple devices.

Here’s how each stands apart below:

The consistency of residential proxies makes them easier to profile and block. CGNAT-grade mobile proxies, however, create network ambiguity that even advanced detection systems struggle to overcome.

Real-world impact: CGNAT vs bot detection

Bot detectors rely heavily on clear signals, starting with IP reputation as a risk marker. They score activity based on known history, but that approach weakens when CGNAT mixes multiple identities.

Traditional detection assumes that each IP address represents a single device, which allows the quick identification of repeat patterns. When hundreds share a CGNAT IP, those assumptions break down and create noisy, conflicting behavior signals.

Now consider volume-based rules, which flag unusual traffic spikes or repeated actions from one IP address. In a CGNAT setup, one user may consume a significant amount of bandwidth while others browse, resulting in unreliable volume metrics.

Accordingly, rate limiting stops working as intended because every request adds to a shared total. A site might throttle a CGNAT IP after minor activity, even if that scraper barely exceeded any limit.

The same problem applies to IP reputation systems that track violations or aggressive usage over time. Since CGNAT mixes legitimate and automated traffic, malicious signals pollute otherwise safe and trusted IP addresses.

Behavioral detection also suffers when heuristics such as mouse speed, click timing, or scroll behavior are analyzed. Because CGNAT proxies carry both human and non-human behavior, those signals become inconsistent and harder to trust.

This ambiguity leads to more false positives, especially when patterns appear to be off but originate from valid mobile users. Sites risk breaking core functionality or alienating real visitors when blocks misfire based on shared indicators.

In practice, CGNAT forces detection systems to make safer guesses or avoid blocking mobile IPs altogether. That hesitation gives mobile proxies a unique advantage where datacenter and residential proxies fail.

What is the CGNAT IP range? (and why it matters)

There is no official CGNAT IP range, as each mobile carrier dynamically assigns public IP addresses to its users. These IPs don’t follow a universal block or identifier, which makes detection and blocking more difficult.

Unlike private IPs used in home routers, CGNAT assigns public-facing addresses that are visible to external websites. Although the IP is shared, it still behaves like a regular public IP in terms of routing and visibility.

Because there's no fixed block to filter, websites can’t reliably blacklist CGNAT activity by range alone. This limits preemptive blocking and forces detection systems to rely on behavior rather than IP origin.

Some websites try to recover the original client IP by reading headers like X-Forwarded-For, HTTP_VIA, and True-Client-IP. If those headers aren’t stripped or replaced, scrapers can unintentionally reveal real device information behind CGNAT.

To stay protected, scrapers, including SOAX’s, remove identifying headers that might expose routing paths or local IP metadata. They sanitize requests at the transport layer to maintain anonymity and consistency.

Ultimately, the strength of CGNAT lies not in the IP range but in the network-level ambiguity it creates. Detection tools can't reliably connect a shared IP to a single user without risking mass false positives.

Use cases where CGNAT mobile proxies are most effective

Mobile proxies powered by CGNAT offer a unique combination of flexibility, ambiguity, and real-world signal blending. They’re helpful in use cases where reputation, identity, or access limits would usually cause failure.

Below are scenarios where CGNAT-enabled mobile proxies shine: 

Web scraping at scale

At large volumes, even well-distributed scrapers eventually hit rate limits, IP bans, or reputation penalties. Mobile proxies using CGNAT help mitigate these risks by distributing traffic across trusted, carrier-assigned IP addresses.

The shared structure makes it harder for websites to identify suspicious patterns tied to a single scraper. As a result, scrapers running at scale experience fewer disruptions and can complete bulk tasks efficiently.

Scraping tools also benefit from high IP churn, which allows jobs to rotate through fresh, untarnished addresses. This dynamic rotation helps maintain access to sensitive targets, such as ecommerce platforms or travel aggregators.

Social media automation

Most social platforms use behavioral heuristics and IP scoring to identify bots that manage multiple accounts. CGNAT undermines those checks by embedding automated actions within streams of real mobile user activity.

Actions like posting, liking, or following seem more authentic when routed through IPs with real mobile patterns. Detection systems struggle to distinguish between automation and background app traffic, as well as real-time user behavior.

Mobile proxies also mimic common session interruptions, including signal drops, app reloads, or location changes. Such traits help social automation tools behave in ways that resemble natural, real-world device usage.

Ad verification

Ad fraud often hides in mobile environments, making mobile traffic essential for accurate ad validation. Using CGNAT-backed proxies, you can simulate real viewers and test how ads display across various devices.

Since CGNAT IPs appear tied to live users, they bypass filters that block datacenter or static proxies. That access allows ad teams to catch cloaked redirects, placement fraud, or manipulated creative delivery.

This visibility is especially important for global campaigns, where targeting rules change based on device type or location. Fraud prevention systems can’t reliably block traffic from a carrier-grade NAT range IP addresses without risking access loss for real users.

Avoiding blocks during account registration

Websites often block new signups based on IP repetition, suspicious patterns, or known botnet behavior. CGNAT traffic dilutes these signals, helping automation systems pass as regular activity from legitimate users.

Each registration attempt originates from a real IP that matches expected mobile characteristics. That makes it harder for anti-bot systems to flag or reject the request confidently.

Even if one attempt fails, the next likely uses a different IP with no associated negative history. Sign-up attempts spread across a CGNAT IP range blend in with genuine mobile traffic, avoiding suspicion and filtering.

Penetration testing and fraud detection

Security teams use mobile proxies to test how systems respond to unpredictable, high-churn traffic sources. CGNAT proxies let them simulate real-world conditions where threats might hide behind trusted carrier networks.

Pen testers benefit from IP ambiguity because it challenges systems to offer protection without blocking legitimate access. This exposes weaknesses in rate limiting, session validation, and anomaly-based detection frameworks.

Fraud analysts also use CGNAT proxies to test how well their controls flag identity spoofing or location evasion. By simulating attackers' mobile behavior, they can improve defenses without harming the normal user experience.

Best practices for using mobile proxies with CGNAT

Using CGNAT-based mobile proxies means more than just rotating IPs. Here are four best practices to keep your sessions stable, undetected, and efficient.

Rotate user agents and browser fingerprints

Websites often track browser fingerprints, which include details like screen resolution, platform, and rendering engine. You should rotate these regularly to suggest a diverse range of mobile devices and avoid appearing predictable.

In addition to user agents, vary fonts, language settings, and device memory to match real usage patterns. Using static fingerprints across sessions makes your traffic stand out, even when CGNAT hides your IP origin.

Avoid overusing the same IP session

While CGNAT provides shared IP ambiguity, long sessions from a single IP can still raise suspicion. Sites may detect sustained behavior patterns and associate that activity with risk, with the IP that you’re using.

To reduce this risk, limit the duration of your sessions and rotate connections more frequently. Ending sessions after a specific time or when action thresholds are met helps reset behavioral signals and preserve IP integrity.

Use mobile proxies for high-risk tasks

Some targets enforce stricter rules, including logging in, scraping dynamic content, or interacting with protected user flows. Mobile proxies are effective for these tasks because web platforms are unlikely to block their IP addresses.

By contrast, residential and datacenter proxies are more likely to trigger blocks during intense automation. This is common when attempting to bypass geo-restrictions or scrape content behind authenticated sessions.

Monitor for CAPTCHAs and fingerprint mismatches

Detection systems often flag suspicious activity using telltale signs like CAPTCHAs, misrendered pages, or blocked assets. You must monitor those signals closely to recognize when websites begin resisting your scraping efforts.

Track these indicators in your logs and adjust headers, behavior patterns, or delays when responses shift unexpectedly. By reacting early, you maintain proxy health and avoid bans that waste IP resources or break workflows.

Fortunately, our CGNAT mobile proxies help bypass these bottlenecks automatically, adapting in real-time without requiring constant manual tuning. They run on autopilot, so you can focus on output instead of dealing with detection hassles.

Do more with SOAX’s CGNAT mobile proxies

As you’ve read, websites struggle to block automation when one IP represents hundreds of real users in constant rotation. That’s what CGNAT’s shared infrastructure makes mobile proxies harder to detect and punish.

This gives you a tactical advantage when scraping at scale, verifying ads, or registering multiple user accounts. Your traffic appears to originate from genuine devices on trusted networks, rather than a controlled proxy pool.

Traditional IP-based rules fail more often when mobile behavior overlaps with automation behind a CGNAT-assigned address. That overlap forces websites to choose between blocking bots and risking disruption to genuine mobile users.

By routing tasks through mobile proxies, you bypass most of the triggers that flag datacenter or residential IPs. You get reliable access, less noise, and fewer headaches, especially on targets that are aggressive against automation.

Whether you're automating tests or extracting data, CGNAT gives you an edge worth leveraging today. Now it’s time to explore SOAX mobile proxies.