Injection Attack Detection for Digital Identity Verification

200%

Increase in injection attacks in 2023.

GARTNER RESEARCH

68%

of respondents lack identity security controls for AI.

CYBERARK 2025 IDENTITY SECURITY LANDSCAPE

Injection attacks threaten identity verification

Injection attacks manipulate live data streams with fake images, videos, or voice recordings to trick biometric systems. Fraudsters use virtual cameras, emulators, and network interception to evade security checks. These sophisticated attacks put the integrity of biometric security and identity verification at risk.

Why identity verification defenses need to evolve.

Organizations that depend on digital identity verification face increasingly advanced fraud tactics. Traditional presentation attacks use fake images or documents shown to a camera, a threat mitigated by liveness detection. Injection attacks are more dangerous with fraudsters inserting synthetic or pre-recorded content into the data stream to bypass biometric checks and other verification steps. Stopping them requires real-time, AI-driven security beyond standard defenses.

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THE RISK

How fraudsters exploit injection attacks

Injection attacks power sophisticated identity fraud schemes, allowing attackers to impersonate legitimate users and bypass traditional security controls. When combined with threats like deepfakes, they enable the creation of fake accounts, exploitation of synthetic identities, and execution of account takeovers (ATO). These tactics drive financial fraud and erode trust in digital identity verification, making advanced, real-time detection critical for organizations staying ahead of evolving threats.

the mitek solution

How Mitek detects injection attacks

Mitek delivers a multi-layered approach to injection attack detection. Our advanced technology monitors both digital content and data streams, detecting injection attacks by looking for visible and invisible artifacts of injected fraudulent content.

The solution performs multiple AI checks specifically designed for identity verification and biometric systems.

Mitek key capabilities

Virtual camera presence detection

Duplicated frames detection

Virtual camera usage detection

Capture vs server evidence mismatch detection

Suspicious resolution detection

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Adopt a defense-in-depth approach

Detect key injection points

Block fraud delivery methods like virtual cameras, emulators, third party browser plug-ins, and hardware exploits used to bypass verification.

Prevent fraudulent, non-live media

Detect deepfakes, face morphs, face swaps, and rendered video.

Improve defenses with layered defenses

Adopt a comprehensive solution that combines deepfake, injection, template, and presentation attack detection.

Mitek delivers advanced fraud detection for advanced threats

AI-powered threat detection

Leverage AI and deep learning to identify complex, evolving fraud patterns with speed, accuracy, and adaptability.

Holistic fraud protection

Defend against multiple attack vectors, whether used individually or in combination.

Future-proof security

Built on a multi-layered detection framework, Mitek rapidly adapts to emerging threats, recognizing and neutralizing new attacks.

Frictionless user experience

Deploy powerful defenses that work imperceptibly in the background, reducing fraud risks without slowing or frustrating users.

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“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.

Learn more about fighting injection attack prevention

Injection attack detection helps businesses significantly mitigate the risk of fraudulent account creation and access. Mitek injection attack detection is available as part of our Digital Fraud Defender suite and as our IDLive Face Plus SDK.

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FREQUENTLY ASKED QUESTIONS

What is an injection attack?

Injection attacks are a sophisticated form of fraud where fraudsters manipulate digital verification systems by injecting pre-created or altered video content. This method bypasses traditional presentation methods, such as showing a photo or video directly to a camera, by directly inserting the fake content into the data stream sent to the verification system.

What is virtual camera detection?

Virtual cameras appear as additional cameras in the operating system. They can provide virtual backgrounds, video filters, and other manipulations, which can be exploited for video injection attacks. Software and AI-based approaches can be employed for detecting virtual cameras. These techniques are based on identifying discrepancies between the virtual and physical camera.

Standard systems commonly identify cameras using device names or identifiers from the operating system. But they often can’t differentiate between a real physical camera and a skillfully configured virtual one.

What is Javascript injection detection?

One potential attack vector for injection is through Javascript used in the process of biometric capturing. Mitigation methodologies must be comprehensive, covering different browsers, and plugins. Techniques include code obfuscation to increase the difficulty of hacking and using specific libraries to binary-encode the Javascript code.

How do injection attacks on identity systems work?

Identity verification and authentication techniques that use facial recognition rely on liveness detection to ensure that a live human face is in front of the camera during biometric capture. While presentation attacks involve “presenting” non-live imagery to the camera, such as photos on paper or digital screens, injection attacks use hardware and software hacks to bypass the camera altogether. Instead the image or video is injected using a virtual camera, a hardware USB stick, or even a JavaScript code that hijacks the video stream from the camera.

How accurate is Mitek’s injection attack detection?

On known deepfake generation engines, the image injection detection rate is 99.9% accurate, and the deepfake injection detection rate (including face swaps, diffusion techniques, image animations) is greater than 99%.

Is Mitek’s solution adaptable to new injection attacks?

Our multi-layered approach—an innovative AI layer trained to detect a wide range of injection artifacts—combined with traditional software-based checks makes it more robust and adaptable to new and evolving threats. However, we always recommend using this solution with other cybersecurity measures for comprehensive protection.

Injection attack detection in digital ID verification