Fingerprint Account Takeover Prevention is a device intelligence platform designed to detect and block account takeover (ATO) attacks, including credential stuffing and brute force attempts. The product works by assigning a unique visitor ID to each device and login session, combining this with known user data and device profile information to identify the individual behind a login attempt. Key detection capabilities include: - IP Geolocation to flag logins from unfamiliar or unexpected locations - VPN Detection using timezone mismatch to identify users concealing their identity or location - Bot Detection to differentiate between bad bots, good bots, and human users in real time - Velocity Signals to detect anomalous login patterns, such as logins occurring within too short a time period or across too great a geographic distance - Browser Tampering detection to identify malicious users manipulating their browser environment The platform collects over 100 signals and applies machine learning to compare current behavior against known account history and device attributes. It also provides a Suspect Score to assist fraud decisioning. Fingerprint integrates into existing authentication flows, allowing teams to reduce friction for trusted users while applying additional scrutiny to suspicious traffic. SDKs and documentation are available for multiple languages and frameworks including Swift, Kotlin, Java, Python, Go, Node.js, React, Angular, Vue.js, Next.js, Flutter, Svelte, and JavaScript. The product is used in cases such as preventing fraudulent orders, unauthorized withdrawals, data theft, and credit card fraud.