Beyond Deepfakes: Why Injection Attacks Are the Next Major Threat

As artificial intelligence becomes more widespread, digital fraud is also evolving and increasing. Jumio, the leader in AI-powered identity intelligence anchored in biometric authentication, automation and data-driven insights, warns about the rise of injection attacks as one of the most sophisticated and difficult-to-detect threats in identity verification processes.

Unlike conventional identity spoofing methods — such as showing a printed photo, wearing a silicone mask, or playing a video from a screen — injection attacks work differently. Attackers use hacking tools or virtual cameras to directly inject fake content into systems, such as AI-generated videos or synthetic biometrics, without needing a physical camera or presence.

This technique relies on camera emulators and specialized software that simulate live streams, allowing attackers to seamlessly inject fake data into systems that do not validate the video source. As a result, attackers can bypass security checks, impersonate legitimate identities, and compromise financial services platforms.

“Injection attacks are becoming increasingly hard to detect, pushing technology to its limits, raising the risk level for fraud, and challenging trust in digital systems. At Jumio, we believe AI must be fought with AI. In identity verification, it’s essential to identify signals invisible to the human eye and detect threats before they even surface,” says Samer Atassi, vice president for Latin America at Jumio.

With the proliferation of deepfake technology, this type of attack has become more common. Jumio has seen an 88% increase in injection attack attempts over the last year, driven by easy access to manipulation tools available on the dark web. Their spread is already affecting companies in Latin America, which are reporting increasingly complex fraud attempts.

Why are they so dangerous?

Injection attacks bypass traditional fraud detection methods by manipulating the input channel itself. Instead of presenting an image or video in front of the camera, attackers alter the system at its source, compromising the integrity of the digital process. Their effectiveness can result in financial fraud, creation of fake identities, evasion of regulatory controls, and loss of user trust and strategic partner confidence.

Given this scenario, liveness detection is no longer a value-added feature — it is now an essential component of security. To combat injection attacks, systems must be able to distinguish between a real person in front of a camera and a manipulated video source.

Effective identity verification technologies against injection attacks should:

1. Differentiate between a legitimate source and an emulated one, identifying whether the video comes from a real camera or software emulator.
2. Accurately match the presented face with the ID document, ensuring biometric consistency.
3. Detect invisible clues such as synthetic artifacts, repetitions, or inconsistencies in lighting, textures, and depth.
4. Recognize suspicious patterns, like reused backgrounds in multiple attempts or pre-recorded videos presented as live input.

“We’re entering a new era of digital fraud, where attackers no longer improvise. They use artificial intelligence, synthetic faces, and video injection techniques to breach even the most advanced systems — better, faster, and at scale. At Jumio, we not only understand this threat — we’re ready to face it. We give businesses the ability to detect and stop these attacks in real time,” concludes Samer Atassi, vice president for Latin America at Jumio.

To learn more about Jumio and its award-winning, AI-powered solutions, visit jumio.com.