Deepfakes

Deepfake fraud is fast becoming one of the most serious cybersecurity threats, undermining the reliability of biometric authentication methods like Face ID and voice recognition. Cybercriminals are increasingly using AI-generated deepfakes to bypass security protocols, steal sensitive information, and execute unauthorized transactions—creating major risks for both consumers and businesses.

With over 187 million Americans shopping via mobile devices last year, mobile commerce now accounts for half of all e-commerce transactions. But this surge in usage has made mobile platforms a prime target for attackers. Biometric authentication, once seen as a robust line of defense, is proving vulnerable as deepfake technology evolves at a startling pace.

AI-generated deepfakes can convincingly replicate a person’s face or voice, tricking systems into granting access. These attacks are fueling large-scale fraud, identity theft, and account takeovers across retail, finance, and other sectors. Appdome, a mobile security firm specializing in AI-driven threat prevention, has reported a sharp rise in deepfake biometric bypasses, with some breaches costing businesses up to $10,000 an hour in losses.

Despite the growing danger, many users still place complete trust in biometric verification, unaware of how easily it can be spoofed by deepfakes. According to Brian Reed, SVP at Appdome, businesses need to shift from reactive, fragmented security approaches to a comprehensive, platform-based model. This means embedding AI-native protection directly into mobile applications to deliver real-time, adaptive defense.

The vulnerability lies in the very convenience that makes biometrics so popular. Features like Face ID, Face Unlock, and voice authentication offer frictionless access, but attackers have spent years analyzing and exploiting their weak points. They now use stolen social media images to create synthetic faces, generate hyper-realistic videos, and employ voice cloning to bypass identity checks, gaining access to user accounts and executing fraudulent transactions.

Reed notes that user misconceptions about the reliability of biometrics are fueling the issue. While these tools are convenient, they are no longer foolproof. Mobile businesses must begin integrating advanced detection tools, such as liveness detection and anti-spoofing technologies, to stay ahead of increasingly sophisticated fraud tactics.

Unlike conventional tools, autonomous defense systems powered by AI continuously monitor and adapt to new threats in real time. These systems are embedded within the mobile app during development, providing on-device protection that evolves with the threat landscape. This proactive approach helps stop deepfake attacks before they cause harm, offering a significant upgrade over traditional, reactive models.

Regulatory frameworks such as KYC and PCI-DSS were created before the rise of AI-driven threats and are not equipped to address deepfake-related fraud. As a result, there are significant gaps in fraud prevention protocols. Reed emphasizes that businesses can’t afford to wait for regulations to catch up—they must act now to protect their platforms and users.

To help address these issues, Appdome recently expanded its Account Takeover Protection suite with 30 new deepfake detection modules for iOS and Android apps. These tools are designed to ensure the integrity of biometric authentication systems like Apple Face ID and Google Face Unlock. They offer granular, real-time detection and control, preventing deepfakes and spoofed biometric data from compromising security.

Appdome’s tools combat advanced attacks, including virtual camera injections, real-time image manipulation, and voice cloning. These hyper-realistic spoofs are designed to fool biometric systems, and without advanced protection, they can succeed. According to Appdome CEO Tom Tovar, while the creation of deepfakes can’t be stopped, their use within mobile apps can—and that’s where the focus should be.

As deepfake technology becomes more powerful and accessible, the stakes for mobile commerce continue to rise. Reed recommends that mobile platforms embed AI-native deepfake detection, enforce on-device biometric checks, monitor emerging threats continuously, and deploy autonomous defenses capable of stopping attacks before they escalate.

The integrity of mobile commerce depends on the ability to adapt and defend against this new generation of AI-powered fraud. Businesses that act decisively now will be best positioned to secure user trust, maintain compliance, and stay competitive in an increasingly hostile digital environment.