ShieldLabs is fraud detection and prevention with traffic quality scoring. It detects users running multiple accounts, account sharing and account takeovers under any masking, so you prevent losses from free-trial, bonus, promo and API abuse.

Email checks, IP limits and cookies do not stop one person with a VPN, a residential proxy and an anti-detect browser. ShieldLabs looks underneath: it identifies the visitor, user, device and IP address behind each visit and checks whether any of them are masked.

How it works: one JavaScript snippet collects more than 100 device and network signals on every visit and cross-checks them against each other, which exposes deep masking with 99.9% identification accuracy. For each visit you get a persistent visitor ID that survives cleared cookies, incognito and IP changes, a risk score from 0 to 100 in three bands (Trusted, Suspicious, Dangerous), named risk signals such as VPN, proxy, Tor, datacenter IP, anti-detect browser and browser automation, and traffic quality by source, channel and campaign. The score arrives through the API and webhooks, and your own code decides what to allow, review or block.

Key features: identification of the same person across sessions, accounts and devices; risk signals for VPNs, proxies, Tor, Apple Private Relay, anti-detect browsers, bots and AI agent traffic, each returned by name; explainable risk scoring with the signals behind every score; traffic quality analytics that show which channels and campaigns bring masked or automated traffic.

Use cases: free-trial, bonus and promo abuse; multi-accounting and ban evasion; account sharing on paid plans; account takeover; signup and API abuse.

Getting started takes about five minutes: sign up at shieldlabs.ai, add the snippet to signup, login and checkout pages, read the score through the API or webhooks, and add your own rules. Pricing is self-serve with a free plan of 5,000 identifications, paid monthly plans for growing traffic, and chat and email support on every plan.