GetReal Security Spotlights Deepfake Risks at Gartner

GetReal Security, one of the more prominent vendors in the emerging deepfake detection market, used the recent Gartner Security & Risk Management (SRM) Summit to spotlight what it describes as the fastest-growing identity-layer threat facing enterprises: AI-generated audio, video, and image content used in social engineering, fraud, and impersonation attacks. The company's presence at one of the security industry's flagship analyst events underscores how rapidly synthetic media defense is moving from an academic curiosity into a mainstream enterprise security category.

Why Gartner SRM Matters for Deepfake Defense

The Gartner SRM Summit is where CISOs, risk officers, and security architects benchmark their stacks against analyst guidance. Historically, the agenda has been dominated by endpoint detection, identity, cloud security, and zero trust. The inclusion of deepfake-focused vendors like GetReal reflects Gartner's own evolving coverage, which now treats generative AI-enabled fraud as a distinct category within identity threat detection and response (ITDR) and communication security.

Recent Gartner research has projected that by 2026, a significant share of enterprises will see deepfake attacks targeting executive communication, biometric authentication, and KYC processes. That forecast aligns with a wave of real-world incidents — including the widely reported $25 million Arup deepfake video call fraud — that have moved synthetic media from theoretical risk to documented loss event.

GetReal's Technical Approach

GetReal Security, founded by deepfake-detection pioneer Hany Farid alongside industry veterans, has built its platform around a multi-modal forensic analysis stack. Rather than relying on a single classifier — an approach that tends to collapse as generative models evolve — the company combines several layers of analysis:

• Physical and physiological signal analysis: inspecting lighting consistency, reflections, blood-flow signals (rPPG), and micro-expressions that current generators struggle to replicate faithfully.
• Provenance and metadata inspection: evaluating file structure, encoding artifacts, and content credentials such as C2PA manifests where present.
• Generative model fingerprinting: identifying statistical traces left by diffusion models, GANs, and voice cloning systems like ElevenLabs-class architectures.
• Behavioral and contextual signals: particularly for real-time video calls, where liveness and interaction patterns can be probed.

This ensemble approach is increasingly the consensus design pattern in the detection community, because no single technique generalizes across the rapidly diversifying generator landscape — from Sora-style video diffusion to open-source face-swap tools like DeepFaceLive and voice cloners that need only seconds of reference audio.

The Enterprise Use Cases Driving Demand

GetReal's pitch at Gartner SRM reportedly emphasized three high-value workflows where deepfake detection is becoming a procurement priority:

1. Executive communication protection: screening inbound video conferences, voicemails, and recorded messages purporting to come from C-suite leaders to prevent wire-fraud and credential-handover attacks.
2. Contact center and KYC defense: validating that callers and document submissions in onboarding flows are not synthetically generated, especially in financial services and insurance.
3. Brand and disinformation monitoring: identifying fabricated content involving company executives, products, or events circulating on social platforms.

Strategic Implications for the Market

GetReal is competing in a crowded but rapidly consolidating space that includes Reality Defender, Truepic, Hive AI, Pindrop (for voice), and platform-native efforts from Microsoft, Adobe, and Google. The visibility at Gartner SRM is strategically important because analyst recognition often precedes budget allocation: once Gartner formally names a Magic Quadrant or Market Guide category for synthetic media defense, procurement cycles accelerate significantly.

For the broader authenticity ecosystem, the takeaway is that deepfake detection is no longer being sold to communications or trust-and-safety teams in isolation — it is being positioned inside the core security stack alongside email security, identity verification, and fraud prevention. That repositioning unlocks materially larger budgets and pulls detection vendors into integrations with SIEM, SOAR, and identity providers.

As generative video models continue to close the perceptual gap with real footage, expect more vendors to follow GetReal's playbook: meet enterprise buyers where they already make security decisions, and frame synthetic media not as a novelty risk but as a core component of modern threat surface management.

Stay informed on AI video and digital authenticity. Follow Skrew AI News.