Group_ injection attack

Deepfake attack detection

Detect and prevent deepfake attacks in digital ID verification

Go beyond detection of common deepfakes. Identify sophisticated attacks, and synthetic media in real time. 

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53%

of businesses have been targets of a financial scam powered by “deepfake” technology.

Medius

47%

of organizations cited adversarial GenAI advances as a primary concern.

World Economic Forum

30%

of enterprises will no longer consider fraud solutions in isolation by 2026 due to AI deepfakes.

Gartner

The rising threat of deepfake attacks in identity verification

Deepfake images, face swaps, and video are among the fastest-growing threats to identity verification and online trust. Criminals exploit readily available tools to manipulate IDs, carry out template attacks, and fool biometric systems.

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Basic deepfake detection isn’t enough

Protecting identity verification goes beyond detecting deepfakes created using common tools. Evolving threats require broader media analysis. And, because deepfakes are often combined with tactics like injection and template attacks, a comprehensive fraud defense is essential. 

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THE RISK

How AI deepfakes fuel fraud

Generative AI deepfakes enable fraudsters to convincingly impersonate real individuals, bypass security controls, and conduct attacks at scale. During identity verification and onboarding, deepfakes may be used to:

  • Create fake ID documents that appear authentic
  • Build sophisticated synthetic identities combining real and fabricated data
  • Bypass biometric checks, often alongside injection attacks

According to Javelin Research, 2024 new account fraud losses reached $6.2 billion in the US alone.

 

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the mitek solution

Secure identity verification with Mitek

Mitek’s AI-powered platform detects deepfakes of any type, content, or delivery method, while keeping the customer experience smooth. By examining artifacts across multiple layers within the media rather than simply focusing on the most popular deepfake generators, we help businesses protect identity verification and biometric checks to reduce fraud losses and maintain trust during and after onboarding.

Mitek key capabilities

Digital content manipulation

AI-generated watermarks

Synthetic content and use of content engines

Explore Digital Fraud Defender

Fight fraud with Mitek’s AI deepfake detection

Robust protection

Effectively identifies complex deepfakes such as face swaps and diffusion techniques.

Comprehensive defense

Covers a wide range of attacks, examining evidence from the point of capture to comparison.

Flexible integration

Available as part of Mitek’s Digital Fraud Defender solution or as an SDK.

How does Mitek’s deepfake detection work?

Using sophisticated AI algorithms, Mitek analyzes subtle clues in image and video data to distinguish real content from AI-manipulated or generated deepfakes.

Digital content manipulation assessment 

Detects signs of content that is digitally altered using image editing software or deep learning models.

AI-generated artifact detection

Looks for artifacts such as watermarks to detect face swaps, face morphing, and synthetic images created by AI image generators.

Synthetic content and engine detection 

Identifies digitally manipulated or AI-generated selfie images by analyzing subtle image attributes and artifacts that reveal potential tampering. 

Holistic fraud protection

Defends against multiple digital attack vectors inlcuding deepfakes, injection, and template attacks, whether used alone or in combination.

Explore Digital Fraud Defender

“Fraudsters don’t rest. They’re constantly evolving, which means we need to stay agile and adaptable. This isn’t a future threat, it’s happening right now. We’ve adopted Mitek’s fraud detection solution because of the clear benefits it brings in tackling these types of emerging fraud.”

LLOYDS BANKING GROUP

Mitek is trusted by over 7,000 organizations worldwide

Trusted by millions globally, our enterprise-grade solutions are relied on by some of the world’s leading enterprises, offering peace of mind for both the company and their customers.

FREQUENTLY ASKED QUESTIONS

What types of deepfake attacks does Mitek’s solution detect? 

Face swaps: Replacing one person’s face with another’s in a video or image, typically using neural networks to smoothly blend facial features and expressions. 

 Synthetic images: Fully AI-generated faces or scenes that don’t exist in the real world, created by models like general adversarial networks (GANs). 

3D mesh faces: Using 3D model of a face (a mesh) to animate or manipulate expressions and angles realistically, often enabling dynamic face reenactment or manipulation in real time. 

What is the detection accuracy of Mitek’s deepfake attack solution? 

The solution has an over 95% detection rate at a BPCER of 1.5% on selfie images across the most popular deepfake generation engines and services. The common equal error rate (EER) on most engines is 3%.

How adaptable is the solution to new deepfake techniques?

We continuously update our models using real-world data and insights from our internal deepfake generation lab, which creates a wide range of synthetic content using different techniques to help our models generalize more effectively.

What additional steps can enhance protection against emerging AI threats?

For the strongest protection against future generative AI threats, combine this technology with our injection attack detection. By analyzing inputs on multiple layers — both visual content, video stream, and the underlying delivery method — this combination offers even more robust coverage and improved accuracy against evolving attack vectors.