Document Liveness Detection SDK

Document Liveness Detection SDK to Stop Document Fraud

Detect photographed-off-a-screen, scanned, or otherwise spoofed documents before they reach your verification workflow — designed to work alongside document recognition.

Source available on GitHub. See pricing & licensing →

An ID card inside a scan frame with a green shield and checkmark showing the document passed the authenticity checkAuthenticity check
What it detects

Authenticity checks for the document capture itself

Document liveness detection analyzes how a document was captured, screening across every stage of the document-fraud pipeline — from a simple re-photograph through to a fully synthetic, template-generated fake — rather than checking for a single spoof type.

6
Spoof categories detected out of the box
2
Fraud types covered: recapture & fabrication
1
Checkpoint before extracted data is trusted

Photographed documents

Flags images that appear to be a photo taken of another photo or printout, rather than the original physical document.

Screen replays

Flags documents presented on a phone or monitor screen instead of a physical original.

Scans & copies

Flags scanned or photocopied reproductions submitted in place of the original document.

Edited & tampered documents

Flags signs of digital editing on an otherwise genuine document — altered fields, cloned regions, or inconsistent fonts and spacing.

Template-generated fakes

Flags documents that don't originate from a real physical capture at all — generated from a template or design file rather than photographed.

Injected & virtual camera feeds

Flags capture sessions where the video stream doesn't originate from a genuine camera reading a physical document in real time.

These six categories are the specific document-spoof types detected today; new attack variants are added to the detection model as they emerge in the field.

How it works with document recognition

A checkpoint before data is trusted

Document Liveness Detection is designed to run alongside the ID Document Recognition SDK: recognition extracts the data, liveness detection evaluates whether the capture itself can be trusted. Used together, a low-liveness result can gate whether extracted data proceeds through your workflow.

Key capabilities

  • ✓ Detection of photographed, scanned, or copied documents
  • ✓ Screen-replay detection
  • ✓ Designed to run alongside document recognition
  • ✓ On-device and server-side deployment

Deployment

Runs on-device for immediate capture feedback or server-side for centralized policy, inside infrastructure you control — see on-premise deployment.

Supported platforms & languages

Integrate in the stack you already use

JavaKotlinSwift Objective-CC++Python FlutterReact Native Ionic CordovaIonic Capacitor.NET
AndroidiOSWindows LinuxServer / Docker
Use cases

Where teams use the Document Liveness Detection SDK

KYC onboarding

Add an authenticity checkpoint before extracted document data is trusted downstream.

Fraud prevention

Reduce reliance on document images that could be reused, edited, or replayed across fraudulent applications.

Remote document submission

Add assurance to document capture flows where a physical original can't be inspected in person.

FAQ

Frequently asked questions

Document recognition reads and extracts data from a document. Document liveness detection evaluates whether the capture itself is authentic — a live capture of a physical original rather than a photo, scan, or screen replay. The two are designed to run together.
It's designed to reduce reliance on manual review by flagging likely spoofed captures automatically, not necessarily to eliminate review from your process.
Yes, where supported by the target platform.

Evaluate the Document Liveness Detection SDK

Get a technical walkthrough with our engineering team.