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    About Stytch Fraud and Risk

    Introduction
    Use cases
    Device Fingerprinting
      Overview
      Fingerprints
    • Verdicts

      • Verdicts overview
        Allow
        Block
        Challenge
        Not Found
    Getting started
      Device Fingerprinting API
      DFP Protected Auth
    Decisioning
      Decisioning overview
      Setting rules with DFP
      Intelligent Rate Limiting
    Enforcement
      Enforcement overview
    • Protected Auth

      • Overview
        Handling challenges
    • Strong CAPTCHA

      • Overview
        Getting started
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Fraud and Risk Prevention

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About Stytch Fraud and Risk

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Use cases

Device Fingerprinting use cases and industry needs

Stytch Device Fingerprinting enhances security and user experience across consumer and B2B apps in all industries:

Block advanced programmatic attacks

Stytch Device Fingerprinting detects bot activity and returns a BLOCK verdict. Developers can check for bots before any sensitive operation:

  • Prevent costly attacks: B2B and B2C applications are both vulnerable to automated attacks, especially against your login endpoints. Bot detection may be used to guard against:

    • Credential stuffing and brute-force attacks: Defend your app against these common threats targeting password logins.
    • Phishing and account takeover (ATO) attacks: Assess high-risk logins by detecting man-in-the-middle (MITM) attacks and high-velocity logins using Stytch's bot detection and intelligent rate limiting.
    • Toll fraud: Guard against SMS pumping and SIP fraud caused by bot traffic, particularly in apps using SMS login for international users.
  • Prevent account creation abuse: In product-led growth (PLG) motions and consumer applications, free sign-up flows are vulnerable to abuse. Stop giving away free credit or trials to abusers, and prevent spam and scam activity from new accounts.

Use device IDs as an additional user identifier

Stytch Device Fingerprinting provides unique, stable device UUIDs. Developers can improve UX by adding or removing friction based on a user's device:

  • Detect unrecognized devices or trusted devices: Add additional checks (like multi-factor authentication) when a user uses a new device for the first time, or make it easier to log in from a known device.
  • Ban all of a user's accounts: Ensure policy violators are banned across all accounts associated with their device (fan-out banning).
  • Prevent seat sharing or enforce paywalls: Prevent unauthorized account-sharing by limiting the number of devices per account. Inversely, prevent paywall evasion by limiting the number of accounts per device.

Block advanced programmatic attacks

Use device IDs as an additional user identifier