When Seeing Isn’t Believing: The Deepfake Threat

tzahi gavrieli
Jul 16
3 min read

Updated: Aug 28

Deepfake technology has advanced rapidly, and with it, the threat to corporate reputation has grown more immediate and more confusing. In an era where AI-generated content can imitate voices, faces, logos, and even media broadcasts, companies are learning the hard way that disinformation doesn't need to be believable—it just needs to spread.

U.S. institutions alone may face up to $40B in deepfake-related losses by 2027—over triple the 2023 total, with many paying over $1M per deep fake incident.

At Repshield, we recently encountered a striking example of this risk in action.

The Deepfake Incident: How a Fake TV Show Fooled a Real Company

A global company headquartered in the U.S. and known for manufacturing home decor products had a presence in Europe. Yet due to geographical and operational distance, their European monitoring was less rigorous. That gap proved costly.

An AI-generated deepfake video began circulating online, showing one of the company's senior leaders appearing on a popular European show to launch a "new" product. The broadcast looked authentic, the company logo was prominently displayed, and the speaker's face and voice appeared convincingly real. But nothing in the video was real.

The show had never aired such a segment. The senior executive had never said those words. And the "product"? well, It didn’t exist.

The video was shared by suspicious Facebook users whose behavior patterns should have triggered internal alerts, but it was bewildered employees in the European office who saw the footage first and sent urgent emails to HQ: "Why weren't we told about this new launch?"

Within hours, internal confusion turned into strategic concern. Some shoppers in Australia began asking about the new product. The show denied airing any such segment. It took the company a full day to contact Meta and have the content removed. Though no direct harm was caused, the incident triggered uncertainty across departments, disrupted sales teams, and left customers in a haze of conflicting information.

It was a wake-up call. One that could have easily been worse.

Deepfakes Don’t Always Cost Millions. But They Always Cost Trust. Not all deepfake incidents lead to million-dollar wire transfers, like the infamous case in Hong Kong where an employee was tricked by a deepfake online meeting into transferring millions to fraudsters. But not all threats need to be catastrophic to be dangerous.

Today, the more realistic scenario is small-scale mayhem: a misled team, a confused customer base, a distracted executive suite. When the very fabric of corporate communication becomes questionable, reputational damage becomes inevitable. And if you're not ready to spot deepfakes fast, you might not even realize the damage until it’s too late.

Repshield's Detection Framework: Fast, Accurate, Scalable

At Repshield, we deploy state-of-the-art tools capable of identifying deepfake content. Using advanced technology platforms, we analyze visual inconsistencies, facial motion artifacts, and image metadata anomalies to detect manipulated content.

In the case above, once the video reached our system, it took just three minutes to confirm it was AI-generated. Our internal system flagged the video’s anomalies and correlated it with external source inconsistencies, triggering an alert.

It Starts at the Source: Tracking the Origin of Deepfake Networks

One of the most important parts of our response protocol is identifying the first publication point of deepfake material. Our systems monitor social networks, message boards, and fringe content sites, looking for suspicious users—often bots or coordinated inauthentic actors—that initiate or amplify these videos.

Finding the source of a deepfake isn't just about taking down one video. It's about mapping a network. By tracing the digital footprints of the original posters, we often uncover entire clusters of accounts involved in repeated deepfake or disinformation campaigns. These insights allow us to anticipate future attacks, warn affected companies, and maintain higher vigilance in targeted regions or sectors.

Final Thought: Prevention May Still Be Out of Reach, But Rapid Response Isn't

We may not yet be able to prevent every deepfake before it surfaces, but we can outpace the confusion. With the right tools, expertise, and vigilance, companies can defend their brand integrity, inform their teams, and remove dangerous content before the damage spreads.

Deepfakes are here to stay. But so are we—and we're ready.

Oh, and also – the images in this post? Totally fake. Generated by AI. But at least we admit it.

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