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Atlas Live
Passive liveness: detects replayed screens, printed photos and reused document portraits.
Access by invitation: no account yet? Ask for your sandbox workspace.
What it checks
A real person, in front of the camera.
Atlas Live analyses the selfie without asking the customer to move, and flags known presentation attempts.
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Passive liveness
No movement required: a single selfie is enough, and the flow stays short.
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Replayed screen
A photo or video shown on another screen is detected, and the check fails.
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Printed photo
A printed or photocopied face held up to the camera is flagged for review.
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Reused document portrait
The document portrait presented as a selfie is recognised, and the check fails.
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Capture quality
No face, several faces or a weak image: the customer is guided and the file is flagged.
How it works
One selfie, no gestures.
- 1 The customer takes a selfie In the hosted flow, with an oval to guide them.
- 2 Atlas analyses the image Liveness score and attack signals computed on the capture.
- 3 The result follows your rules Confirmed attack: fail. Doubt: human review. Otherwise, the check passes.
Presentation checks
- Replayed screen not detected
- Printed photo not detected
- Document portrait reused not detected
- One face only yes
- Deepfakes and injection Coming soon
Liveness Passed
For developers
Reasons, not just a score.
The liveness check returns its status and the reasons detected, the same in the API and in the webhooks.
Request
curl https://verify.atlasidv.com/v1/verifications/7f3c9a2e-… \
-H "Authorization: Bearer atlas_sk_sandbox_…" Response 200 OK
{
"status": "needs_review",
"reason_codes": ["liveness_screen_replay"],
"checks": [
{
"type": "liveness",
"status": "failed"
}
]
} Take the next step
Try Atlas Live on your own flows.
A demo on your real cases, then a sandbox space with synthetic identities to integrate without any real data.