In effect, the true user won’t even receive a notification of suspicious activity or that someone else has logged into their account. By spoofing a user’s specific device and cookies, a service will think that the login is coming from the genuine user. However, we’ve observed an emerging criminal tradecraft which targets these fingerprinting anti-fraud technologies and is making use of so-called anti-detection or “anti-detect” browsers combined with stolen digital fingerprints. These fingerprints are fairly unique for each user and can be used to identify suspicious behavior, such as when a user’s fingerprint changes suddenly from their last login, which may trigger a security question challenge, captcha, or multi-factor authentication (MFA) prompt. Browser fingerprints are typically generated based on a user’s browser version, operating system, timezone, language settings, screen size, and many other variables.
Modern bot-detection and anti-fraud systems rely on ‘browser fingerprinting’ to detect suspicious or potentially fraudulent traffic.
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