Analyze Your Urban Terror Demos
Upload a .urtdemo file for multi-metric behavioral analysis. Our system examines aiming patterns, shot timing, and movement to detect potential aimbot usage.
Upload Demo File
Drag and drop a .urtdemo file, or click to browse
Maximum file size: 100MB
How It Works
Our multi-metric behavioral analysis examines aiming patterns from multiple angles to detect potential aimbot usage while minimizing false positives.
Measures how fast the crosshair moves throughout the demo. Natural players make fast flicks (2000-4000°/s), show gradual acceleration, and mix horizontal and vertical movements. Aimbots produce unnatural patterns: artificially limited speeds, instant teleport-like snaps with no transition, and perfectly single-axis movements.
💡 Our most reliable indicator: 80% of cheaters have 0% medium-velocity shots vs. only 9% of natural players.
Analyzes WHEN shots are fired relative to aim movement. Natural players fire in various states: while tracking, while adjusting, and when locked. Aimbots only fire when perfectly locked (zero velocity) or immediately after snapping - they never fire while 'adjusting' because they don't need to adjust.
💡 The most statistically significant single indicator with 80% vs 9% separation between cheaters and natural players.
Trigger bots don't move your aim - they automatically fire when your crosshair passes over an enemy. Human reaction time is 150-300ms minimum; trigger bots fire in under 10ms. We detect inhuman reaction times, suspicious timing consistency, and the characteristic snap→stop→instant-fire pattern.
💡 Trigger bots are harder to detect since aim looks natural. We focus on TIMING - the instant shots that bypass human reaction time limits.
Identifies robotic precision in targeting. Natural players hit targets at varying heights (enemies crouch, jump, use stairs). Aimbots configured for headshots always snap to the same vertical level and show robotic repetition in angle changes that humans cannot achieve.
💡 If 70%+ of snaps end at the same pitch, or the same exact angle appears repeatedly, it's a strong aimbot indicator.
Based on USC research achieving 97%+ detection accuracy. We split the demo into 60-second windows and analyze each independently. Natural players may occasionally trigger individual flags during intense moments, but cheaters show consistent suspicious patterns throughout gameplay.
💡 Research shows 30-60 second windows are optimal. Flagging 50%+ of windows indicates continuous aimbot usage vs. occasional anomalies.
In realistic FPS games, accuracy drops 50-70% while moving - this is intentional game design. Aimbots can compensate for movement and maintain high accuracy even while sprinting. We compare kill rates while stationary vs. moving.
💡 Natural accuracy ratio: 0.3-0.5. Aimbots maintaining 0.8+ ratio shows impossible accuracy while moving.