What is ShieldLabs?
ShieldLabs is a Visitor Identification and Anonymity Detection API platform. The solution uses a single JavaScript snippet to collect browser and network signals during website visits, returning a persistent identifier and a risk score ranging from 0 to 100 via a REST API and signed Webhooks.
Key Capabilities
- Visitor Identification: The platform recognizes returning visitors across separate sessions, cleared browser cookies, incognito/private modes, IP rotations, and extended timeframes. According to the vendor, the system achieves an accuracy rate of up to 99% to support both defensive security (linking multi-accounting profiles) and user experience personalization (recognizing known users without requiring secondary authentication).
- Anonymity Detection: Detects network and device anonymity markers with a vendor-stated accuracy of up to 99% using multi-level analysis rather than binary flags. Network Intelligence evaluates VPN, Proxy, Tor, Apple Private Relay, and datacenter IP ranges. Device Intelligence identifies anti-detect browsers, browser automation tools, operating system mismatches, and undetectable operating systems. Findings are returned as individual named signals for granular visibility.
- Explainable Scoring: Assigns a risk score from 0 to 100 alongside the specific named signals that generated the score, maintaining an auditable decision trail for security analysts and administrators.
- Traffic Analytics & Pattern Detection: The dashboard pre-computes correlation across accounts, devices, and identities to highlight multi-accounting, account sharing, account takeover (ATO), and account farms. Analytics break down traffic by risk band and acquisition source (including channel, referrer, and UTM Parameters).
Audience & Use Cases
- Audience: Fraud prevention teams, security analysts, risk engineers, and web developers.
- Use Cases: Prevention of multi-accounting, free-trial abuse, bonus/promo/referral/loyalty fraud, new-account fraud, account takeover, account sharing, ban evasion, paywall bypass, payment fraud, ad fraud, location spoofing, and Sybil attacks.
Technical Specifications & Integration
- Deployment: Single JavaScript snippet.
- Supported Frameworks & Platforms: React, Next.js, Vue, Angular, Svelte, Preact, React Native WebView, WordPress, Shopify, and Tilda.
Categories & Use Cases
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Screenshot of Overview: an aggregate traffic risk score with the split across Clean, Low, Medium and High risk bands, the trend over the selected period, and visitor counts against the previous period.
