Uma autenticação biométrica por etapas nos momentos exatos que os atacantes visam, transferências, redefinições de palavra-passe, logins em novos dispositivos. Veredito em menos de dois segundos, cerca de $0.13 por evento. 500 verificações grátis todos os meses.
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Confiado por mais de 2.000 organizações em todo o mundo.
Como os atacantes atacam
Ataques de preenchimento de credenciais, troca de SIM e cookies de sessão roubados ignoram palavras-passe e códigos únicos. Troque-os por uma autenticação por etapas Didit no momento da ação, $0.10 por chamada, veredito em menos de dois segundos, 500 grátis todos os meses.
Escolha as verificações que pretende, ID, prova de vida, correspondência facial, sanções, morada, idade, telefone, e-mail, perguntas personalizadas. Arraste-as para um fluxo no dashboard, ou publique o mesmo fluxo na nossa API. Crie ramificações com base em condições, execute testes A/B, sem necessidade de código.
Incorpore nativamente com os nossos SDKs Web, iOS, Android, React Native ou Flutter. Redirecione para uma página alojada. Ou simplesmente envie um link ao seu utilizador, por e-mail, SMS, WhatsApp, em qualquer lugar. Escolha o que melhor se adapta à sua stack.
A Didit aloja a câmara, as indicações de iluminação, a transição móvel e a acessibilidade. Enquanto o utilizador está no fluxo, pontuamos mais de 200 sinais de fraude em tempo real e verificamos cada campo contra fontes de dados autorizadas. Resultado em menos de dois segundos.
Os webhooks assinados em tempo real mantêm a sua base de dados sincronizada no momento em que um utilizador é aprovado, recusado ou enviado para revisão. Consulte a API a pedido. Ou abra a consola para inspecionar cada sessão, cada sinal e gerir os casos à sua maneira.
Didit · Step-up policy
Didit · Biometric Authentication
Step 2 / 2
Hold still for the check
Didit · Face Match 1:1
Sign-up
Step-up
Didit · Passive Liveness
Didit · Device & IP Analysis
Didit · Webhook · X-Signature-V2
{
"session_id": "abc-…",
"vendor_data": "user-42",
"status": "Approved",
"liveness": { "status": "Approved" },
"face": { "status": "Approved",
"similarity_score": 0.94 }
}$ 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: Approved.documentação →// X-Signature-V2 verified upstream
if (payload.status === "Aprovado") {
unblockAction(payload.vendor_data);
} else if (payload.status === "Recusado") {
logWarnings(payload.liveness.warnings);
blockAndAlert(payload.vendor_data);
}X-Signature-V2 antes de ler o payload.documentação →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.$0 / mês. Não é necessário cartão de crédito.
Pague apenas pelo que usa. Mais de 25 módulos. Preços públicos por módulo, sem taxa mínima mensal.
MSA e SLA personalizados. Para grandes volumes e programas regulados.
Comece grátis → pague apenas quando uma verificação for executada → desbloqueie o Enterprise para um contrato personalizado, SLA ou residência de dados.
Didit is infrastructure for identity and fraud, the platform we wished existed when we were building products ourselves: open, flexible, and developer-friendly, so it works as a real part of your stack instead of a black box you integrate around.
One API covers verifying people (KYC, know your customer), verifying businesses (KYB, know your business), screening crypto wallets (KYT, know your transaction), and monitoring transactions in real time, on a stack built to be:
The footprint underneath: 14,000+ document types in 48+ languages, 1,000+ data sources, and 200+ fraud signals on every session. The Didit infrastructure dynamically learns from every session and gets better every day.
An account takeover (ATO) happens when an attacker gains control of a legitimate user account, usually with stolen credentials, a hijacked session cookie, or a SIM-swap that intercepts the One-Time Password (OTP). From there they drain wallets, move funds, change payout details, or reset email and lock the real owner out.
The attack walks past the password because the password is already correct. It walks past the Short Message Service (SMS) code because the attacker controls the phone number. The defence is to interrupt the moment of action with something the attacker does not have, the legitimate user's face.
Because SIM-swap fraud puts the Short Message Service (SMS) code in the attacker's pocket. The attacker convinces the carrier to port the victim's number to a new Subscriber Identity Module (SIM); from then on, every code the bank sends arrives on the attacker's phone.
Phishing kits in 2026 also proxy the code in real time, the user types it into a fake page, the kit replays it to the real site, the session opens. SMS gives a single shared secret per channel; biometrics give a per-action proof tied to the human in front of the camera.
The full flow normally takes under 30 seconds end-to-end, pick up the ID, snap the document, snap the selfie, done. That is the fastest in the market. Legacy KYC providers usually take more than 90 seconds for the same flow.
On the back end, Didit returns the result in under two seconds at p99, measured from the moment the user finishes the selfie to the moment your webhook fires. Mobile capture is tuned for slow phones and slow networks: progressive image compression, lazy software development kit load, and a one-tap hand-off from desktop to phone via QR code if the user starts on web.
Sign-up captures the user's identity for the first time, government identity document, Optical Character Recognition (OCR), Passive Liveness, and a portrait that becomes the enrollment baseline. It is a one-off, heavy-weight flow.
Step-up is the lightweight, repeatable version. The same liveness engine runs on a new selfie; Face Match 1:1 compares the new selfie against the stored sign-up portrait. No identity document, no OCR. Sub-two-second, $0.10 per session.
Every session lands on one of seven clear statuses, so your code always knows what to do:
Approved, every check passed. Move the user forward.Declined, one or more checks failed. You can allow the user to resubmit the specific failed step (for example, re-take the selfie) without re-running the whole flow.In Review, flagged for compliance review. Open the case in the console, see every signal, decide approve or decline.In Progress, user is mid-flow.Not Started, link sent, user has not opened it yet. Send a reminder if it sits too long.Abandoned, user opened the link but did not finish in time. Re-engage or expire.Expired, the session link aged out. Create a new session.A signed webhook fires on every status change, so your database always stays in sync. Abandoned and declined sessions are free.
Production data is processed and stored in the European Union by default, on Amazon Web Services. Enterprise contracts can request alternative regions for jurisdictions whose regulators require it.
Encryption everywhere. AES-256 at rest across every database, object store, and backup. Transport Layer Security 1.3 in transit on every API call, webhook, and Business Console session. Biometric data is encrypted under a separate Customer Master Key.
Retention is yours to control. Default retention is indefinite (unlimited) unless you configure shorter, between 30 days and 10 years per application, and you can delete any individual session at any time from the dashboard or the API.
Certifications: SOC 2 Type 1 (Type 2 audit in progress), ISO/IEC 27001:2022, iBeta Level 1 PAD, and a public attestation from Spain''s Tesoro / SEPBLAC / CNMV that Didit''s remote identity verification is safer than verifying someone in person. Full report at /security-compliance.
Didit ships compliant by default for the regulators that matter to identity infrastructure:
Detailed memo, every certificate, every regulator letter: /security-compliance.
Three integration paths, pick whichever fits your stack:
Same dashboard, same billing, same pay-per-success price for all three. Step-by-step guide at docs.didit.me/integration/integration-prompt.
Compose Device & IP Analysis ahead of the step-up. $0.03 per check, under 100ms, returns a 0–100 risk score plus Virtual Private Network (VPN), proxy, The Onion Router (Tor), datacenter, country, and Autonomous System Number (ASN) flags.
If the network looks clean (residential Internet Service Provider (ISP), trusted device fingerprint, no country flip), skip the face check. If the score is high or any flag fires, run the step-up. That keeps the biometric budget on the events that actually need it.
Two line items:
Around $0.13 per fully-screened sensitive action. The first 500 verifications every month are free on every account, most teams find their step-up volume sits inside that allowance for the first few weeks.
No minimums, no annual commitment, no per-seat pricing.
The recipe applies to any team handling high-value actions. Common live patterns:
Same Workflow Builder, different triggers, one integration, one pricing line.
Uma API para KYC, KYB, Monitorização de Transações e Rastreio de Carteiras. Integre em 5 minutos.