Residential Proxies Have Become One of Security’s Largest Blind Spots

This guest article was contributed by Alastair Parr, CTO of Spur

A growing share of the traffic security teams evaluate each day comes from residential proxies that pool IP addresses from consumer ISPs and mobile devices. Most people don’t realize they’ve opted into a residential proxy, and most organizations lack the context to fully understand how often this traffic reaches them.

Residential proxies make it difficult to distinguish legitimate traffic from malicious activity because actors hide behind what appear to be real IPs. Because of this obfuscation, residential proxies are a common infrastructure used in fraud campaigns and automation.

How an Obfuscation Layer Took Shape Over Time

The residential proxy ecosystem has evolved beyond compromised devices through a combination of free mobile games, free VPNs, embedded SDKs, and low-cost devices that monetize themselves by selling access. Buried somewhere in the terms is a line authorizing a third party to route traffic through that device. That’s all it takes. Multiply that across millions of households, and you have a global residential proxy network made up of ordinary people’s lives.

We observe residential proxy use occurring much more frequently than security and fraud teams might expect, especially in cases such as inventory hoarding, agentic scraping, and account farming.

Why Automation Operators Rely on Residential Traffic

Automation adds another layer to residential proxies, enabling a much larger scale in creating and managing new user accounts, scraping large quantities of content, testing credentials, and bypassing regional restrictions. None of these capabilities relies solely on exploiting a system weakness. They’re successful because of the credibility associated with the residential address linked to the IP address. That’s why it’s difficult for systems to differentiate between authentic demand and synthetic activity.

Where Enterprise Visibility Breaks Down

Teams continue to rely on IP reputation, VPN identification, or known hosting providers as early markers. But residential proxies are able to pass those checks as they operate on legitimate infrastructure. Therefore, it’s easy to overlook some of the suspicious customer activity. Although the IP address might appear OK, the activities and the context in which they’re performed tell a different story. This has created inconsistencies in risk scoring, identity assurance, and triage workflows. Signals that once carried weight no longer offer clear guidance.

The same residential proxy traffic that hides fraud also distorts basic business performance. In e-commerce, for example, growing automation has affected more than just security. It slows down queue systems due to the number of automated loads. Agentic bot traffic and automated clicks deplete marketing budgets and skew performance results. Teams also struggle to accommodate unexpected surges in traffic during product launches or periods of heavy enrollment, resulting in a majority of the inventory selling out before real consumers have even had a chance to check out.

In other online services, normal-looking traffic can hide acts of scraping, denial-of-service attempts, account farming, and credential testing, which can create significant disruption to forecasts and create swings in demand that teams don’t model for. A single flawed assumption that residential traffic is low-risk can drive much of this.

Residential Traffic Belongs in the Threat Model

It’s never been a good option to require excessive friction, as it impairs legitimate use. Instead, a more effective approach is to use passive signals that help establish a comprehensive view of the IP’s context and can inform selective friction. Organizations that are making progress look at location consistency, network stability, patterns associated with known proxy-resale applications, and session behavior that doesn’t match a human’s activity. Another indicator is distributed access in patterns that look orchestrated. Each of these signals sit in the background without interrupting legitimate users. They simply give teams more confidence in what they’re seeing.

A large part of this ecosystem survives because people don’t know what they’re trading away when they install free software or buy low-cost devices. More transparency from marketplaces, app developers, and manufacturers would help users understand what their devices are doing and how they’re being used. Organizations also benefit when users have a clearer view of what runs on their hardware.

Residential proxies now sit across the internet as a permanent layer. They were developed with user consent and not as a result of exploiting a vulnerability. That’s why they’re easy to overlook. Security teams encounter this traffic constantly, but many struggle with trust that no longer matches reality.

By viewing residential proxy traffic as inherently safe, security teams have created gaps in their ability to detect fraudulent activity, verify identity, or monitor operations. As a result, they misjudge where fraud starts, how it spreads, and how much volume sits behind these sessions.

It’s time to bring the residential proxy layer into the threat model. Attackers already treat it like infrastructure. Security teams need to treat it like part of the attack surface.

About the author

Alastair Parr is the CTO at Spur, where he oversees the company’s technology strategy, research agenda, and product development. He brings over 17 years of experience in governance, risk, compliance, and technical consulting. He previously served as SVP of global products and services at Prevalent and was a founder of the risk and security consultancy 3GRC.