Didit Passive Liveness API

Overview

Verifies that a user is physically present by analyzing a single captured image. No video, movement or user interaction is required.

Key constraints:

• Allowed file extensions: tiff, jpg, jpeg, png, webp (no PDF)
• Maximum file size: 5 MB (images are compressed to about 0.5 MB before processing, so higher resolutions do not improve accuracy)
• One clearly visible face. With several faces the largest one is scored and MULTIPLE_FACES_DETECTED is added
• Original real-time capture (no screenshots, prints or photos of screens)

Pricing: $0.05 (per successful call; standalone calls have no free tier). These are the list prices until 1 November 2026, when Didit pricing changes and the 500 free checks a month become $10 of free credit a month. Check didit.me/pricing for current prices.

Accuracy: 99.9% liveness detection accuracy, <0.1% false acceptance rate (FAR).

Decision: status is Declined when any error warning fires (no face, score at or below the threshold, presentation attack, blocklist hit) and Approved otherwise. There is no In Review on this endpoint. Only the score threshold is configurable.

Blocklist and duplicate screening: runs on every call, also with save_api_request=false. The face is compared with your application's face search index (your face blocklist and allowlist, faces from approved sessions, faces uploaded to User profiles and retained biometric templates). Earlier faces with the same vendor_data are skipped for the duplicate check, so re-verifying the same user does not raise DUPLICATED_FACE. A blocklisted face is still caught when it carries the same vendor_data. A match on your face allowlist suppresses the duplicate warnings.