ShieldLabs - 2026 Pricing, Features, Reviews & Alternatives

ShieldLabs is a software platform for anonymous visitor detection and fraud prevention that identifies website visitors operating behind virtual private networks, proxy servers and anti-detect browsers while assigning risk scores to prevent fraudulent activities. It serves businesses across artificial intelligence, iGaming, cryptocurrency, software as a service, financial technology, e-commerce, travel, marketplace, media and streaming, ticketing and gaming sectors that require protection against multiple account creation, promotional abuse, fabricated registrations and various forms of digital fraud. The platform delivers high accuracy in visitor identification and incorporates traffic quality assessment capabilities to help organizations distinguish legitimate users from fraudulent actors. It prevents losses and ensures that business metrics reflect genuine user behavior rather than manipulated data.

The platform builds persistent visitor identifiers from device, network and browser signals collected during the initial page interaction, enabling recognition of the same visitor across cleared cookies, rotated network addresses and private browsing sessions. It analyzes an extensive array of browser, network and device signals to detect anonymity indicators and suspicious behavior patterns. Network intelligence capabilities span virtual private network detection, proxy server identification, Tor network usage, privacy relay services, datacenter infrastructure recognition, IP reputation analysis and geolocation integrity checks. Device and browser intelligence features detect anti-detect browsers, operating system tampering, browser automation tools, private browsing modes and anomalous click activity. Risk assessments are accompanied by the specific signals that contributed to each score to maintain transparency in fraud detection decisions.

ShieldLabs leverages preconfigured pattern recognition functionality to correlate accounts, devices and signals across historical traffic data, identifying multi-accounting schemes, account sharing, account takeovers, account farming and ban evasion without requiring custom rule configuration. Each finding is presented with a severity rating and details of the involved entities. A comprehensive traffic analytics dashboard provides a unified risk metric for traffic quality and breaks down anonymity indicators by acquisition channel, referring source and campaign parameters to reveal sources of invalid traffic. This level of visibility enables organizations to make informed decisions based on clear insights into traffic composition.

Deployment involves a single JavaScript snippet that integrates seamlessly with a variety of technology stacks, including modern JavaScript frameworks, content management systems and no-code builders, and becomes operational within minutes. Visitor identification data, risk assessments, anonymity signals and detection flags are delivered through application programming interfaces and webhook responses. The platform does not autonomously block traffic; it surfaces actionable data and assessments for client systems to determine appropriate actions. Fraud and abuse scenarios addressed by the solution include traffic quality evaluation, account takeover detection, account sharing identification, multi-accounting prevention, promotional abuse mitigation, free trial abuse detection, advertising fraud filtering and recognition of returning trusted users.