무료
월 $0. 신용 카드 필요 없음.
- 무료 KYC 번들 (ID 확인 + 수동 라이브니스 + 얼굴 매칭 + 장치 및 IP 분석) — 매월 500회
- 차단된 사용자
- 중복 감지
- 모든 세션에서 200개 이상의 사기 신호
- Didit 네트워크 전반에 걸쳐 재사용 가능한 KYC
- 사례 관리 플랫폼
- 워크플로우 빌더
- 공개 문서, 샌드박스, SDK, MCP(모델 컨텍스트 프로토콜) 서버
- 커뮤니티 지원




전 세계 2,000개 이상의 조직에서 신뢰합니다.

공격자가 공격하는 방법
자격 증명 스터핑, SIM 스왑, 도난된 세션 쿠키 공격은 모두 비밀번호와 일회성 코드를 우회합니다. 작업 순간에 Didit 단계별 인증으로 교체하세요. 호출당 $0.10, 2초 미만 판정, 매월 500회 무료.
원하는 확인 사항(ID, 생체 인식, 얼굴 매칭, 제재, 주소, 연령, 전화, 이메일, 맞춤 질문)을 선택하세요. 대시보드에서 플로우로 드래그하거나 동일한 플로우를 API에 게시하세요. 조건에 따라 분기하고 A/B 테스트를 실행하며 코드가 필요 없습니다.
웹, iOS, Android, React Native 또는 Flutter SDK를 사용하여 기본적으로 임베드하세요. 호스팅된 페이지로 리디렉션하세요. 또는 이메일, SMS, WhatsApp 등 어디든 사용자에게 링크를 보내세요. 스택에 맞는 것을 선택하세요.
Didit은 카메라, 조명 신호, 모바일 핸드오프 및 접근성을 호스팅합니다. 사용자가 플로우를 진행하는 동안 200개 이상의 사기 신호를 실시간으로 채점하고 모든 필드를 신뢰할 수 있는 데이터 소스와 비교하여 확인합니다. 2초 이내에 결과가 나옵니다.
실시간 서명된 웹훅은 사용자가 승인, 거부 또는 검토로 전송되는 순간 데이터베이스를 동기화 상태로 유지합니다. 필요에 따라 API를 폴링하세요. 또는 콘솔을 열어 모든 세션, 모든 신호를 검사하고 원하는 방식으로 사례를 관리하세요.
Didit · 단계별 정책
Didit · 생체 인증
2단계 / 2
확인을 위해 잠시 멈춰주세요
Didit · 얼굴 매칭 1:1
가입
단계 상향
Didit · 수동적 생체 인식
Didit · 장치 및 IP 분석
Didit · 웹훅 · X-Signature-V2
{
"session_id": "abc-…",
"vendor_data": "user-42",
"status": "Approved",
"liveness": { "status": "Approved" },
"face": { "status": "Approved",
"similarity_score": 0.94 }
}$ curl -X POST https://verification.didit.me/v3/session/ \
-H "x-api-key: $DIDIT_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"workflow_id": "wf_ato_step_up",
"vendor_data": "user-42",
"metadata": { "trigger": "high_value_transfer" },
// base64 KYC enrolment selfie, ≤ 1MB
"portrait_image": "/9j/4AAQSkZJRgABAQE..."
}'status: Approved를 반환할 때까지 작업을 차단합니다.문서 →// X-Signature-V2 verified upstream
if (페이로드.status === "승인됨") {
unblockAction(페이로드.vendor_data);
} else if (페이로드.status === "거부됨") {
logWarnings(페이로드.liveness.경고);
blockAndAlert(페이로드.vendor_data);
}X-Signature-V2를 확인하십시오.문서 →You are integrating Didit account-takeover defence into an application that already has the user signed in. Your job: when a sensitive action fires (large transfer, password reset, payout to a new destination, new-device login, geo anomaly), gate it on a Didit biometric step-up. One API call. One signed webhook. Three branches.
WHY THIS SHAPE
- Credential stuffing, SIM-swap, and stolen-session-cookie attacks all walk past passwords and SMS one-time codes. A face check at the moment of the sensitive action does not.
- Didit runs Passive Liveness (the user is alive, present, not a deepfake) plus 1:1 Face Match against the portrait captured at sign-up. A stolen selfie cannot pass — the comparison target is locked to the original enrollment.
- $0.10 per step-up (Biometric Authentication module) + $0.03 IP pre-check (optional) = around $0.13 per event. Sub-two-second verdict on entry-level Android. 500 verifications free every month.
PRE-REQUISITES
- Production API key from https://business.didit.me (sandbox key in 60 seconds, no credit card).
- A webhook endpoint with HMAC SHA-256 verification of the X-Signature-V2 header using your webhook secret.
HMAC-SHA256 verification MUST run against the raw body bytes (the raw payload as Didit sent it) BEFORE any JSON parsing — re-serialising the parsed body changes whitespace and key order, which invalidates the signature. - A Workflow Builder workflow that bundles Passive Liveness + Face Match 1:1 (with the user's stored sign-up portrait as the comparison target). Optionally compose Device & IP Analysis ahead of the step-up to pre-gate the check.
- Persist the user's sign-up portrait — either base64 on your side, or rely on Didit's stored enrollment via vendor_data lookup.
STEP 1 — Decide WHEN to step up (your code, not Didit's)
Run your usual fraud signals. Common triggers worth a biometric step-up:
- Wire / crypto transfer above the user's daily limit
- Password / email reset on a session less than 24h old
- Payout to a bank account or wallet seen for the first time
- Login from a new device or new country
- Velocity anomaly — N actions of type T within window W
Cheap pre-check (optional, ~100ms, $0.03):
- Score the user's IP via Device & IP Analysis. If the IP is a residential trusted address with a low risk score AND the device fingerprint matches the user's trusted device, skip the step-up. Otherwise run Step 2.
STEP 2 — Create a biometric step-up session
POST https://verification.didit.me/v3/session/
Headers:
x-api-key: <your api key>
Content-Type: application/json
Body:
{
"workflow_id": "<wf id bundling Passive Liveness + Face Match 1:1>",
"vendor_data": "<your user id, max 256 chars>",
"callback": "https://<your-app>/ato/step-up/callback",
"metadata": {
"trigger": "high_value_transfer",
"action_id": "<your internal action reference>"
},
"portrait_image": "<base64 JPEG of the user's stored sign-up portrait, ≤ 1 MB — REQUIRED when the workflow has FACE_MATCH active; the step-up matches the new live selfie against this stored reference>"
}
Response: 201 Created with a hosted session URL. Redirect the user there inline (or open it in a webview / Didit mobile SDK). The action stays BLOCKED on your side until the signed webhook lands.
STEP 3 — Read the signed webhook on completion
Didit POSTs the decision to your callback. Verify X-Signature-V2 (HMAC SHA-256 of the raw request body using your webhook secret) BEFORE reading the JSON.
Payload (excerpted):
{
"session_id": "<uuid>",
"vendor_data": "<your user id>",
"status": "Approved",
"liveness": { "status": "Approved" },
"face": { "status": "Approved", "similarity_score": 0.94 },
"ip_analysis": { "status": "Approved", "score": 11 }
}
Session status enum (exact case, Title Case With Spaces): Approved | Declined | In Review | Resubmitted | Expired | Not Finished | Kyc Expired | Abandoned.
STEP 4 — Branch the original action on status
Approved → unblock the sensitive action. Log session_id + similarity score on the audit trail.
In Review → hold the action, route to a human review queue.
Declined → block the action, log liveness warnings (mask / deepfake / replay / morph), alert the user.
Not Finished → invite the user to retry with a fresh session URL.
Expired → resend the link; the original session has timed out.
Abandoned → the user closed the flow before completing; resend the link.
STEP 5 — (Optional) Pull the full decision payload
GET https://verification.didit.me/v3/session/{session_id}/decision/
Headers:
x-api-key: <your api key>
Returns the same payload as the webhook plus the structured signals (liveness warnings, face-match similarity, IP / device flags). Use for analyst review.
WEBHOOK EVENT NAMES
- Sessions: standard session webhook (one endpoint, status field tells you where in the lifecycle).
- Verify X-Signature-V2 (HMAC SHA-256) on every payload.
CONSTRAINTS
- Session statuses use Title Case With Spaces (Approved, In Review). Never use UPPER_SNAKE_CASE for session verdicts — that's the Transactions API and lives in a different surface.
- 1:1 face match's comparison target is the user's STORED sign-up portrait, not a freshly captured one. A stolen selfie cannot pass.
- iBeta Level 1 Presentation Attack Detection (PAD) certified against the full ISO/IEC 30107-3 catalogue — print, replay, paper / silicone / latex mask, deepfake, morph.
- The Workflow Builder is where you choose the modules in the step-up — change them in the console without redeploying.
- 200+ fraud signals are surfaced on every session at no extra cost — read them off the decision payload, don't re-query.
Read the docs:
- https://docs.didit.me/sessions-api/create-session
- https://docs.didit.me/core-technology/biometric-auth/overview
- https://docs.didit.me/core-technology/ip-analysis/overview
- https://docs.didit.me/integration/webhooks
Start free at https://business.didit.me — sandbox key in 60 seconds, 500 verifications free every month, no credit card.월 $0. 신용 카드 필요 없음.
사용한 만큼만 지불하세요. 25개 이상의 모듈. 공개된 모듈별 가격, 월 최소 요금 없음.
맞춤형 MSA 및 SLA. 대량 및 규제 프로그램용.
무료로 시작 → 검사가 실행될 때만 지불 → 맞춤형 계약, SLA 또는 데이터 상주를 위해 엔터프라이즈 잠금 해제.