Amazon Rekognition (Faces)

Amazon Rekognition: Biometric Sovereignty & Deepfake Injection Defense Audit (2026)

As of January 2026, Amazon Rekognition (Faces) has transitioned to an Agentic Identity Layer. The architecture leverages User Vector Aggregation to consolidate multi-image biometric profiles, significantly reducing False Rejection Rates (FRR) in non-deterministic lighting conditions across 100M+ enterprise-scale identities 📑.

Biometric Orchestration & User Vectors

The core engine utilizes a 'User-Centric' persistence model where up to 100 mathematical embeddings (Face Vectors) are fused into a single UserID cluster 📑.

• Enterprise Verification Scenario: Input: Multi-angle mobile face capture → Process: Similarity scoring against 100-vector UserID clusters in a 100M-subject collection → Output: High-precision identity confirmation with sub-500ms latency 📑.
• Gaze-Driven Liveness: Implements active biometric challenges by tracking eye-line pitch and yaw (independent of head pose) to thwart advanced 3D projection attacks 📑.

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Deepfake Injection Defense & Liveness v2

Architecture 2026 features Face Liveness v2, a specialized component that identifies frequency-domain artifacts characteristic of generative AI and digital injection at the hardware-abstraction layer 📑.

• Agentic Grounding (Bedrock Nova): Visual metadata is interpreted by the Amazon Bedrock Nova model, providing a natural language 'Thought Trace' to explain the reasoning behind biometric confidence scores 📑.
• Vector Persistence Security: Embeddings are stored in an encrypted, non-reversible Managed Persistence Layer with per-tenant salting. The specific vector-graph indexing topology remains undisclosed to prevent reconstruction attacks 🌑.

Evaluation Guidance

Technical evaluators should verify the following architectural characteristics:

• High-Scale Retrieval Latency: Benchmark the RTT (Round-Trip Time) for 1:N searches when UserID collections exceed the 100 million subject threshold [Documented].
• Liveness v2 Efficacy: Conduct red-team testing of the Deepfake Injection Defense against real-time diffusion models to validate claimed zero-penetration rates [Unknown].
• Regional Availability: Verify that the User Vector Aggregation features are fully deployed in your specific AWS region, as localized Data Residency flags may impact feature availability in the EU and Japan [Inference].