Seatext library / BotRefund evidence
BotRefund’s Bot‑Traffic Detection Signals
BotRefund examines a mix of behavioral and network signals—like ghost clicks, honeypot traps, linear mouse paths, super‑fast inputs, grid‑aligned movement, missing engagement, odd session lengths, and suspicious ports—to spot bot traffic.
✓ Built for advertisers who need clear, refund-ready traffic evidence.
Key signals BotRefund analyzes
BotRefund looks at more than 100 independent checks. The most critical categories are:
- Ghost click detection – catches clicks that occur without the natural sequence of human intent.
- Trap behavior (honeypot) – watches for bots that interact with hidden or deliberately deceptive page elements.
- Pointer behavior – flags unnaturally straight mouse paths that rarely appear in real user sessions.
- Motion behavior – looks for the tiny imperfections and jitter typical of human movement; their absence suggests automation.
- Speed behavior – identifies interactions that happen faster than a person could realistically perform (under 1 ms).
- Path behavior – detects grid‑aligned movement patterns that snap to precise lines instead of natural curves.
- Engagement behavior – highlights sessions that stay too static, with no clicks or scrolling, to match a real browsing journey.
- Session behavior – catches visit lengths that are too short, too long, or too uniform to be human.
- Network signals – such as suspicious ports, which reveal mismatches between connection details, location, language and timing that a genuine browser would not normally create.
- Monitor sync anomaly – looks for timing and interaction mismatches that scripts struggle to reproduce, indicating automated activity.
Each signal on its own is not a verdict; BotRefund’s AI cross‑checks them together to reach a high‑confidence decision.
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