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Glossary
An injection attack, in identity verification, is when an attacker bypasses the device camera and feeds fabricated images or video, often a deepfake, directly into the verification pipeline, so the system never sees a real capture of a real person. It is one of the most serious emerging threats to face-based verification, because it defeats checks that assume the camera is trustworthy.
Traditional spoofing holds something up to the camera (a photo, a mask). An injection attack skips the camera entirely, inserting synthetic media into the data stream as if it came from the sensor.
Attackers use virtual cameras, emulators, manipulated mobile apps, or tampered SDKs to substitute their own feed for the real camera. Paired with a convincing deepfake face or a forged document image, this can pass a naive liveness or document check, because the check is analyzing attacker-supplied media rather than a genuine capture. It is a favored technique precisely because it targets the trust the system places in the capture itself.
Defending against injection attacks requires proving the integrity of the capture, not just analyzing its content. That means confirming the media came from a genuine, untampered camera on a real device, detecting virtual cameras and emulators, and hardening the SDK against tampering, layered on top of strong deepfake and presentation-attack detection. As generative AI makes the injected content more convincing, capture-integrity has become the decisive defense.
What is an injection attack in identity verification?
Bypassing the camera to feed fake or deepfake media directly into the verification pipeline.
How is it different from a presentation attack?
A presentation attack shows a spoof to the camera; an injection attack skips the camera and inserts media into the data stream.
How do you stop injection attacks?
Prove capture integrity (genuine untampered camera), detect virtual cameras and emulators, and harden the SDK, plus deepfake detection.
Related: Deepfakes · Liveness Detection · Presentation Attack Detection (PAD) · Identity Verification (IDV) · Generative AI Fraud
