BotRefund’s Bot‑Traffic Detection Signals

Key signals BotRefund monitors

BotRefund evaluates a range of independent checks to decide whether a visit is automated. The most prominent signals are:

• Ghost click detection – catches click activity that happens without the natural sequence of human intent.
• Trap behavior (honeypot) – watches for bots that respond to hidden or intentionally 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, which bots lack.
• 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, showing an absence of clicks or scrolling.
• Session behavior – catches visit lengths that are too short, too long, or too uniform to be human.
• Suspicious ports – one of 106 independent checks that looks for mismatched network, location, and timing data often produced by proxy rotation or browser spoofing.
• Monitor sync anomaly – examines timing and movement inconsistencies that scripts struggle to reproduce, adding another layer of evidence.

Each signal on its own is not a verdict; BotRefund’s AI model cross‑checks them with other browser, network, and device data to reach a 99 % accurate classification.