BotRefund’s Bot‑Traffic Detection Signals

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.