Deepfake fraud is rapidly emerging as one of the most dangerous cyberthreats, eroding consumer trust in biometric authentication. AI-generated attacks manipulate Face ID and voice authentication to gain unauthorized access, steal payment details, and bypass traditional security measures, putting both retailers and consumers at increasing risk.
With 187.5 million people in the U.S. shopping on mobile devices last year, mobile transactions now account for half of all e-commerce sales. But as their popularity grows, so does their appeal to cybercriminals. Biometric authentication, such as iOS Face ID and Android Face Unlock, has long been a cornerstone of mobile security.
However, deepfake attacks have evolved at an alarming pace. They use AI-generated voices, videos, and facial animations to bypass these defenses, fueling large-scale identity theft, payment fraud, and unauthorized transactions.
According to Appdome, a mobile security platform specializing in AI-driven threat defense, cybercriminals increasingly use deepfake biometric bypass techniques to take over accounts, steal sensitive data, and initiate fraudulent transactions. Moreover, attackers have compromised banking apps, leading to financial losses of $10,000 per hour for some organizations. Without real-time defense, businesses and consumers face mounting financial harm and risks to brand reputations.
Biometric Security Alone Isn’t Enough
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Most shoppers trust biometric authentication without realizing how vulnerable these methods are to deepfake manipulation. As AI-powered fraud tactics become more sophisticated, e-commerce brands, payment platforms, and retailers must stay ahead of the threats before consumer trust and retailer revenue suffer even more significant damage.
Appdome SVP Brian Reed suggested that retailers, financial institutions, and mobile developers have another option to constantly playing catch-up. They can take the lead with autonomous mobile defense strategies.
If he could give one crucial piece of advice to mobile commerce businesses today on protecting their customers from deepfake subterfuge, it would be to stop the fragmented, piecemeal approach of layering different security and fraud tools into their tech stack and hoping they work together.
“The only way to truly protect mobile commerce from deepfake fraud and millions of other threat vectors is to shift to a platform-based approach with an AI-native engine at the core,” he told the E-Commerce Times.
Why Mobile Transactions Are Vulnerable to Deepfake Fraud
According to Reed, mobile commerce depends on biometric authentication for frictionless user access. Because Face ID, Face Unlock, and voice authentication are now universal features across mobile banking and retail apps, attackers have spent years probing for vulnerabilities. AI-generated deepfakes now provide them with a powerful tool to impersonate users, take over accounts, and commit fraud at scale.
Cybercriminals leverage AI-powered deepfakes to bypass facial recognition, voice authentication, and identity verification. They generate deepfake videos and images to trick Face ID, often using stolen social media photos to create synthetic identities for fraudulent Know Your Customer (KYC) verification. Voice cloning technology enables attackers to impersonate users in phone-based banking authentication, making it easier to gain unauthorized access.
As these tactics become more advanced and widely available, traditional biometric defenses are proving insufficient to stop the growing threat of AI-driven fraud.
Reed observed that consumers’ misconceptions about biometric security drive a wedge between their trust and cyber realities. While many still trust biometric authentication as foolproof, deepfake attacks are changing the game.
“Hyper-realistic biometric spoofs can now bypass Face ID, voice authentication, and other biometric security measures. To maintain trust, mobile businesses must strengthen their security with AI-driven deepfake protections, liveness detection, and anti-spoofing technology,” he urged.
Updating Policies and Regulations for AI-Powered Fraud
Unlike traditional security, autonomous defense operates with continuous vigilance, adapting in real time using AI, machine learning, and large-scale threat intelligence. This proactive approach detects and stops deepfake fraud — and millions of other attacks and threats — before it happens, ensuring mobile businesses stay ahead of evolving AI-powered threats instead of reacting to them.
This type of mobile defense platform integrates security directly into mobile apps during development. It delivers real-time, in-app, on-device protection against evolving threats and continuously monitors and responds to new attacks throughout the mobile app lifecycle.
“AI-powered fraud and threats aren’t slowing down, and neither should your defense. Move from reactive security and fraud protection to AI-native protection built directly into your mobile app,” Reed urged.
Existing regulations were not designed for AI-powered fraud. Compliance policies like KYC and PCI-DSS predate deepfake AI attacks, leaving dangerous gaps in fraud prevention, he reasoned. Cybercriminals are now using AI to manipulate biometric authentication, bypass identity verification, and commit large-scale fraud, exploiting the fact that regulations haven’t caught up.
“The industry can’t wait for policymakers to act. Mobile businesses must take the lead by deploying AI-native defenses now, ensuring deepfake attacks are detected and blocked in real-time before they cause harm,” Reed said about deploying a better option.
Appdome’s Deepfake Defense for Mobile Security
In late February, Appdome announced an extension to its Account Takeover Protection suite with 30 new dynamic defense plugins for Deep Fake Detection in Android and iOS apps. These plugins better ensure the integrity of Apple Face ID, Google Face Recognition, and third-party face and voice recognition services against AI-generated and other deepfake attacks.
“The mobile economy depends on the integrity of facial recognition, Face ID, and other biometric authentication methods to reduce friction,” said Eric Newcomer, principal analyst and CTO at Intellyx. “However, attackers are constantly finding new ways to bypass biometric authentication,” he noted.
Appdome’s approach provides mobile businesses with granular detection and control defenses to stop these attacks inside the mobile app, he explained. This prevents attack data from passing to other systems, combating account takeover and open directory forgery attacks quickly and efficiently.
According to Appdome, deepfake attacks generate hyper-realistic, adversarial replications or manipulations that can fool facial and voice verification systems. Sometimes, attackers use virtual cameras to inject pre-recorded or live video streams into the facial recognition process. Other times, image buffer attacks manipulate face data processing in real time to bypass detection processes.
Hyper-realistic biometric spoofs can bypass Face ID, voice authentication, and other biometric security measures. Reed insisted that mobile businesses must strengthen their security with AI-driven deepfake protections, liveness detection, and anti-spoofing technology to maintain trust.
“Everyone, from mobile app developers to enterprises to Face ID and facial recognition vendors, is struggling with the technical challenges of detecting AI-generated deepfakes and Face ID bypass techniques,” said Tom Tovar, CEO of Appdome.
“While no one can stop the creation of deepfakes, we’ve succeeded in stopping their use inside mobile applications, and we’re making our innovations available to mobile app developers and face recognition vendors alike,” he offered.
How Mobile Businesses Can Fight Deepfake Fraud
The future of mobile commerce is at risk if cybersecurity cannot stop the deepfake damage. AI-powered fraud and deepfake attacks are growing more sophisticated, making them harder to detect. In the coming years, cybercriminals will continue to target biometric authentication, identity verification, and financial transactions with enhanced e-commerce theft powered by increasingly advanced AI-generated attacks, warned Reed.
He recommended the following measures for mobile commerce platforms to combat deepfake fraud:
- Integrate AI-native deepfake detection directly into their mobile apps
- Enforce real-time, on-device biometric verification
- Monitor emerging attack vectors and continuously adapt to new threats
- Deploy autonomous mobile defenses that detect and neutralize AI-generated fraud before damage occurs
Implementing these strategies can help them stay ahead of evolving threats and protect businesses and consumers from fraud.
