Deepfakes have moved from novelty to a serious security threat for any organization connected to the internet. Increasingly weaponized by nation-states and cybercriminals, synthetic media is reshaping fraud, social engineering, and identity abuse at scale.

“When people think about deepfakes, they often picture fake videos or voice-cloned calls,” said Arif Mamedov, CEO of Regula Forensics, a global developer of forensic devices and identity verification solutions. “But the real danger goes much deeper. Deepfakes attack identity itself, which is the foundation of digital trust.”

Unlike traditional fraud that relies on stolen or leaked data, deepfakes allow criminals to recreate existing people or invent entirely new ones, complete with faces, voices, documents, and believable behavior. “These identities can look legitimate from the very first interaction,” Mamedov explained.

According to Regula’s research, deepfakes introduce three major risks:

Authentication failure: Facial recognition, voice authentication, and document checks often rely on static or replayable signals that deepfakes can spoof.
Massive scalability: AI enables the creation of thousands of fake identities at once, turning fraud into an industrial operation.
False confidence: Because deepfakes frequently pass existing controls, organizations believe they are protected while fraud quietly escalates.

“Our 2025 data shows that deepfakes don’t replace traditional fraud, they amplify it,” Mamedov added. “They expose long-standing weaknesses and make them far more costly.”

How Deepfakes Undermine Human Judgment

Traditional security models assume that once someone is authenticated, they are legitimate. “Deepfakes break that assumption,” said Mike Engle, chief strategy officer at 1Kosmos, a digital identity verification and passwordless authentication firm.

“AI can convincingly impersonate executives, employees, job candidates, or customers using synthetic voices, faces, and documents,” Engle explained. “That allows attackers to bypass onboarding, help desks, and approval workflows that were never designed to detect manufactured identities.”

Once a fake identity is successfully enrolled, Engle warned, every downstream control — MFA, VPNs, SSO — may end up protecting the attacker rather than the organization.

Deepfakes don’t break systems first, they break people, added David Lee, Field CTO at Saviynt, an identity governance and access management provider.

“When a voice or video sounds right, people move quickly, skip verification, and assume authority is legitimate,” Lee said. “That’s what makes deepfakes so effective. A believable executive voice can authorize payments, override processes, or create urgency that short-circuits rational decision-making before security controls ever engage.”

James E. Lee, president of the Identity Theft Resource Center, noted that while any business can be targeted, smaller or thin-margined organizations are especially vulnerable. “The financial impact can be disproportionate and, in some cases, threaten the viability of the business,” he said.

Deepfake-driven attacks can lead to data breaches, loss of control over systems and processes, and significant unplanned expenses in addition to direct financial losses.

Deepfake Attacks Are Accelerating

The rapid spread of AI tools has dramatically lowered the barrier to entry for attackers. “Cybersecurity reports and regulatory warnings point to an exponential rise in deepfake activity,” observed Ruth Azar-Knupffer, co-founder of VerifyLabs, a developer of deepfake detection technology.

“Threat actors are increasingly using accessible AI tools, including open-source generators, to produce convincing fakes efficiently,” she said. The widespread use of video calls and social media has further expanded the attack surface, making deepfakes a powerful vector for scams and disinformation.

Mamedov added that the acceleration is driven by simple economics. “The tools are cheap or free, the models are widely available, and the output quality now exceeds what many verification systems were designed to handle.”

“What used to be a manual, one-off effort is now a plug-and-play ecosystem,” he said. “Fraudsters can buy complete persona kits on demand: synthetic faces, cloned voices, and digital backstories. That marks a shift from small-scale fraud to industrial-scale identity fabrication.”

Regula data shows that roughly one in three organizations has already encountered deepfake fraud, placing it on par with long-standing threats like document fraud and classic social engineering.

New Technology, Old Deception

Many organizations are responding with training. This week, KnowBe4, a cybersecurity training provider, launched new programs focused on defending against deepfakes.

Perry Carpenter, KnowBe4’s chief human risk management strategist, said the training emphasizes how employees should respond emotionally and behaviorally, not visually.

“If you feel fear, urgency, authority, or hope being pulled as a lever, that’s a signal to slow down,” Carpenter explained. “Analyze what’s being asked and ask whether it raises red flags.”

He cautioned against relying on visual or audio “tells.” “Those cues will disappear within months as the technology improves,” he said. “The most important question is not ‘Does this look real?’ but ‘Is this trying to manipulate me, and how can I verify it through another channel?’”

“Deepfakes are just the newest tool in the attacker’s toolbox,” Carpenter added. “The emotional manipulation behind them is as old as fraud itself.”

Never Trust, Always Verify

Rich Mogull, chief analyst at the Cloud Security Alliance, agreed that employees should stop trying to visually spot deepfakes.

“Instead, focus on behavioral signals and process controls,” he said. Mogull recommends multi-step approvals for sensitive actions like wire transfers, hard blocks against bypassing controls, and mandatory out-of-band verification for executive requests.

Saviynt’s Lee stressed that training alone is not enough. “Awareness helps people pause, but it doesn’t replace verification,” he said. “Organizations need to stop asking ‘Is this real?’ and start asking ‘What confirms this?’”

That means callback procedures, secondary approvals, and removing voice or video as standalone trust signals. “If your control depends on someone recognizing a fake, you don’t have a control, you have a gamble,” Lee warned.

“Deepfakes aren’t the root problem. They’re a stress test,” he concluded. “They expose how many organizations still rely on recognition instead of verification. When identity is continuously validated and trust is no longer implicit, deepfakes lose their power.”

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