Cite as: Real Problem AI problem “Why does our liveness check still pass a face that was never in the room?”. Opportunity score 8.5 out of 10 (severity 9, AI feasibility 8, market signal 8, competition gap 9). Category FinTech. Trend Vision. Source signal: r/FraudPrevention thread on deepfake detection in identity verification flows, 5 September 2026, 10 comments; Quora answers on how deepfakes complicate KYC identity verification.. Canonical URL: https://www.realproblem.ai/archive/why-does-our-liveness-check-still-pass-a-face-that-was-never-in-the-room.
Why does our liveness check still pass a face that was never in the room?
Synthetic faces and virtual-camera injection walk through remote identity checks because most vendors rebadged liveness detection as deepfake protection and still benchmark against public datasets fraudsters solved years ago.
Who has it: Fraud and risk teams at banks, fintechs and marketplaces running remote identity verification at onboarding.
- Severity9/10
- Feasible today8/10
- Market signal8/10
- Competition gap9/10
Heard in public
“Most vendors still benchmark against public GAN datasets that fraudsters cracked years ago”
Quoted word for word from the public post linked below. Nobody submitted it to Real Problem AI.
r/FraudPrevention thread on deepfake detection in identity verification flows, 5 September 2026, 10 comments; Quora answers on how deepfakes complicate KYC identity verification.What nothing does yet
Detection that treats injection and synthesis as two separate attacks: prove the frames came from a real camera on a real device, test the face against current generative architectures rather than a dataset from 2022, and publish the evaluation set with its date so a buyer can see what the score actually covers.
Tools that solve this
3 named so far, and where each one stops.
- Passive liveness vendors
Built to catch a printed photo or a replayed video, not a live synthetic face driven in real time.
- Virtual camera detection add-ons
Match known driver names, so anything unlisted passes straight through the check.
- Document plus selfie matching
Compares two images, both of which can now be generated to match each other.
Why it is archived
Trimmed to 100-cap (oldest live entries make room for newer ones)
How you might build it
- 01Device and camera attestation to prove capture provenance
- 02Stream-injection detection below the application layer
- 03Generative-artefact models retrained against current architectures
- 04Dated, published evaluation set with a per-attack breakdown
- 05Step-up challenge for high-risk actions
Founders working in this area
- Ben Colman, Co-founder and CEO, Reality Defender
Not affiliated with Real Problem AI.
#N27E · Canonical URL: https://www.realproblem.ai/archive/why-does-our-liveness-check-still-pass-a-face-that-was-never-in-the-room