This Is Where We Are……

It pains me to see society slowly but predictably corrode. We’ve had scammers and thieves long before the age of technology, but there’s just something uniquely dark about Deepfake technology, where many people can’t decipher the difference between the deepfake and the real person. Visual deception was the limit with deepfakes for a while; it was possible to mimic a face with a near 1:1 accuracy but as soon as voice came into play, the jig was up. Now, with the vast improvement in AI models and audio generation, voice deception is more accurate than ever, and it’s extremely worrying. The Baby boomer generation was typically the demographic scammed by phone salesmen or offshore scammers via phone or email, but now, with deepfakes being able to mimic voices of your loved ones, that opens the door for many of the younger generations to be scammed as well.

So I want to educate as many folks as I can to help them combat the rise of deepfake scams, as well as give a quick overview of what deepfakes are in general and the problems around the tech.

What Are Deepfakes?

Deepfakes are images, videos, or audio that have been edited or generated using artificial intelligence, AI-based tools, or audio-video editing software. They may depict real or fictional people and are considered a form of synthetic media, that is, media that is usually created by artificial intelligence systems by combining various media elements into a new media artifact.

That’s a general definition and should give you an idea of where we are headed. The faster and more intelligent we make AI, the better these deepfakes and scams will get.

For a bit of history, an early project called the "Video Rewrite" program was published in 1997. The program modified existing video footage of a person speaking to depict that person mouthing the words from a different audio track.[34] It was the first system to fully automate this kind of facial reanimation, and it did so using machine learning techniques to make connections between the sounds produced by a video's subject and the shape of the subject's face.

Fast forward some years, the deepfakes we know today stem from generative adversarial networks (GANs). It was developed in 2014 and published in a research paper by researcher Ian Goodfellow and his colleagues. A GAN is a machine learning model designed to generate realistic data by learning patterns from existing training datasets. It operates within an unsupervised learning framework by using deep learning techniques, where two neural networks work in opposition—one generates data, while the other evaluates whether the data is real or generated.

The “Generator” creates synthetic content, and the “Discriminator” evaluates whether the content is real. This back and forth eventually makes the fake content look as real as possible. Think of it like sharpening a sword against a steel block. Every time the sword (the Generator) is run against the steel block (the Discriminator), the sword gets sharper.

Deepfakes entered the mainstream in 2018, with the release of accessible open-source deepfake tools like DeepFaceLab. In 2023, the deepfake tool market skyrocketed, with a 44% increase in the development of these tools.

It’s Pretty Messed Up Tech

Deepfakes are f’d up….. Not much more to elaborate on there lol. While deepfakes could be used to make appropriate parodies, 9 times out of 10 it’s used for things like creating synthetic media of world leaders or creating content combining copyrighted media, along with other nefarious purposes. There is a huge concern amongst academics around deepfakes promoting disinformation, violence, and hate speech.

Unfortunately, the creation of non-consensual explicit content of women has served as a motivating factor for the rising popularization of deepfake tools. The problem is rampant, with Security Hero reporting that in 2023, approximately 98% of deepfake videos online are explicit in nature, and only 1% of targets in that category are male.

Researchers have also shown that deepfakes are expanding into other domains such as medical imagery. In this work, it was shown how an attacker can automatically inject or remove lung cancer in a patient's 3D CT scan. The result was so convincing that it fooled three radiologists and a state-of-the-art lung cancer detection AI. To demonstrate the threat, the authors successfully performed the attack on a hospital in a white hat penetration test.[37]

Another example is a sophisticated scam using AI-generated video and voice that nearly compromised a well-known crypto developer linked to the Cardano ecosystem. The attacker impersonated Pierre Kaklamanos, Head of Digital Assets Adoption at the Cardano Foundation, during what appeared to be a legitimate Microsoft Teams call. The target, developer Big Pey, said the scam almost succeeded after he followed instructions during the fake meeting.

There are plenty of other domains that this can have a negative impact on, escpecially is we continue down the line of tokenization. We’d then be faced with deepfake contracts and deeds, getting people to sign away assets and funds to the attacker without even knowing it.

How to Protect Yourself

Protecting yourself is going to be the best way to avoid being scammed or caught up in a deepfake scheme. So it’s good to know a handful of the things to look out for and the best practices to follow to not be a victim of fraud.

Verify Before You Trust

If you receive an unexpected call, video, or message from someone claiming to be a family member, colleague, or authority figure — especially one asking for money or sensitive information — verify their identity through a separate channel. Call them back on a known number, or reach out via text/email independently. Example: If "your son" calls saying he's broke and needs some funds wired immediately, hang up and call his actual phone number before doing anything.

Establish a Family Safe Word

One of the most practical defenses against voice deepfakes is creating a secret code word with close family and friends. If someone calls claiming to be them in an emergency, ask for the safe word. No legitimate loved one will be offended. Example: A family could agree that the word "pineapple" must be said if any family member ever calls asking for urgent financial help.

Slow Down — Urgency Is the Red Flag

Deepfake scammers rely on panic and urgency to short-circuit your critical thinking. If any call, video, or message is pressuring you to act right now, that's your cue to pause. Scammers don't want you to have time to verify. Legitimate emergencies almost always have a moment to double-check.

Use Multi-Factor Authentication (MFA) Everywhere

Even if a scammer uses a deepfake to impersonate you to a bank or service provider, MFA adds a critical extra barrier. A voice or face alone shouldn't be enough to authorize anything sensitive — and if a service is relying solely on those for verification, that's a concern worth raising with them.

Facing This Issue Head On

Deepfakes are here and here to stay. The threat and its consequences are very real and present. Deepfakes today are at the point of undermining trust in the online identity verification process that many organizations, especially in the financial sector, have come to rely upon. With more people than ever authenticating themselves using biometrics across all their devices, the growth in the malicious use of deepfakes can lead to a dire need to rethink authentication security within the next five years, or sooner.

As shown in the examples, the barrier to entry for creating realistic deepfakes has dramatically decreased. From cloned voices to full video impersonations, deepfakes empower scammers and fraudsters in ways that are harder to detect and defend against.

Understanding the threat is the first step to defending against it. With more end-user security training and by leveraging emerging deepfake detection tools, organizations and individuals can begin to fight back against this new threat. We also have to help our elders and loved ones who aren’t tech-savvy get up to speed with this rising threat, so they too can be prepared to combat deepfakes.

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