How Passive Liveness Detects Real Humans
The science behind verifying human presence through involuntary physiological signals, without any user cooperation
Simple Steps to Get Started
Measuring your vitals takes less than a minute
Camera Feed Capture
During any camera-based step in your identity workflow, Circadify captures a brief sequence of video frames. The subject is unaware that liveness detection is occurring. No prompts, no instructions, no interruption to the existing user experience.
rPPG Signal Extraction
Our algorithms isolate the micro-color fluctuations in facial skin caused by cardiac blood flow. Every heartbeat pushes blood through facial capillaries, creating a physiological signal that is present in every living human and absent in every spoofing medium.
Presentation Attack Analysis
The extracted signals are analyzed against known attack vectors: printed photos produce no rPPG signal, screen replays exhibit display refresh artifacts, silicone masks lack vascular response, and deepfake videos contain synthetic patterns that diverge from genuine physiology.
Liveness Determination
A confidence-scored liveness result is returned to your identity pipeline via API. The determination includes an attack type classification when a spoof is detected, enabling your fraud team to analyze attack patterns and refine risk scoring over time.
Ready to Integrate Passive Liveness?
Request the integration guide and start deploying presentation attack detection that verifies real humans without asking them to do anything.