In a recent head-to-head analysis between Stytch's device fingerprinting solution and Fingerprint Pro, we found that both solutions had similar accuracy in identifying unique site visitors, but that Stytch offered superior tamper resistance.

Stytch's solution also incorporates a number of tamper-resistant and tamper-evident features via cryptographic signing. Stytch's robust deception detection techniques also ensure that if Stytch's payload internals are somehow tampered with, the results won’t be accepted by Stytch's servers for access.

Fingerprint.js provides users with a wide array of individual attributes, such as VPN detection, IP geolocation, and more. With Fingerprint, aggregating the output of these attributes to make a decision on what behavior to allow or disallow is up to you. An advantage of this approach is the ability to see and customize behavior based on raw device attributes; however, these individual signals are susceptible to large numbers of false positives and negatives. For example, Fingerprint's VPN detection is largely based on IP address lookups and timezone mismatch. While these factors are effective in a large number of cases, they’re also imperfect and easily gamed by bad actors, leading to inaccurate data.

In contrast, Stytch's solution looks holistically at the hardware, network, and browser-level profile of a website visitor and uses deterministic pattern matching to generate an action recommendation and a unique, stable fingerprint. This allows for a more streamlined implementation when using Stytch, and avoids creating an illusion of accuracy by presenting raw attributes that may not be fully reliable.