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Tripwire evaluates every session across multiple detection categories. Each category contributes independently to the final verdict, and the scoring pipeline combines them with weighted confidence.

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Categories

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Environment

Detects automation frameworks and headless browser indicators. Checks for:
  • WebDriver API presence (navigator.webdriver)
  • Automation globals (__playwright, __selenium, cdc_*)
  • Headless browser markers (zero plugins, missing APIs)
  • Stealth plugin artifacts
Environment signals are deterministic — when present, they produce high-confidence bot verdicts.

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Fingerprint

Analyzes the device’s hardware and software configuration for consistency:
  • WebGL renderer and extensions
  • Canvas and audio fingerprinting
  • Screen geometry anomalies
  • Anti-detect browser noise patterns
Fingerprint signals detect spoofed or manipulated device profiles.

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Behavioral

Observes how the user interacts with the page:
  • Mouse movement patterns (linearity, speed, Fitts’ Law compliance)
  • Keyboard timing (inter-keystroke intervals, rollover patterns)
  • Touch dynamics (for mobile devices)
  • Form interaction timing
Behavioral signals require user interaction. Sessions evaluated before interaction may produce inconclusive verdicts.

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Timing

Measures temporal patterns:
  • Time to first interaction
  • Form completion speed
  • Suspiciously regular intervals (100ms, 250ms, 500ms)

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Anti-tamper

Server-side cross-validation of client-reported data:
  • User-Agent vs HTTP headers consistency
  • TLS fingerprint (JA4) vs claimed browser
  • Network characteristics vs device claims
Anti-tamper signals are server-side only and cannot be spoofed from the browser.

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How categories combine

The scoring pipeline weights each category and combines them:
  1. Short-circuit — definitive signals (e.g., navigator.webdriver === true) immediately produce a bot verdict
  2. Weighted combination — non-definitive signals are combined with category weights
  3. Corroboration — behavioral signals alone cannot produce a bot verdict without deterministic corroboration
  4. Normalization — final score mapped to 0–1 range via sigmoid function

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What’s next