AI has made it cheaper and easier than ever to generate convincing deepfakes, turning face biometrics into a prime target across customer and workforce access flows.

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In the Gartner^® report Deepfake Identity Threats: Mitigate Risk in Identity Verification and Face Biometrics, analysts outline how quickly these attacks are evolving and why cybersecurity leaders can’t rely on standalone deepfake detection to stay protected. Instead, Gartner^® recommends focusing on how deepfakes can be used to compromise face biometric systems in the first place—and building layered defenses that account for both presentation and injection attacks.

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At CLEAR, we see the same patterns play out in the field, where attackers blend deepfakes with compromised devices, synthetic identities, and other signals to slip past single-layered checks. CLEAR1’s multi-layered approach to identity—which combines biometrics with document checks, device intelligence, and verified data sources—is designed to help organizations verify the person behind every interaction.

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In this Gartner^® report, you’ll learn:

• How generative AI is lowering the cost and effort required to create high-quality deepfakes
• Why Gartner^® advises cybersecurity leaders to rely on multi-layered defenses
• How presentation attacks and injection attacks create different paths for deepfakes to compromise face biometric systems
• Why Gartner^® recommends favoring solutions that pair face biometrics with a broad range of device and security signals