Deepfake Threats: When You Cannot Trust What You See or Hear

Imagine this: your CFO receives a video call from the CEO, who is traveling abroad. The CEO's face is on screen, the voice sounds right, and the request seems reasonable — transfer $250,000 to a new vendor account to close a time-sensitive deal. The CFO processes the transfer. The problem? It was not the CEO at all. It was a deepfake.

flowchart LR
    A["AI Generates Deepfake"] --> B["Impersonates Executive"]
    B --> C["Requests Wire Transfer"]
    C --> D["Employee Deceived"]
    D --> E["Funds Transferred"]
    E --> F["Financial Loss"]
  

This is not science fiction. Incidents like this have already happened, with losses reaching into the tens of millions of dollars. Deepfake technology — AI-generated audio, video, and images that convincingly impersonate real people — has evolved from a novelty into a genuine business threat.

And the technology is getting cheaper, faster, and more accessible every month. You no longer need a Hollywood studio to create a convincing fake. A few minutes of audio from a podcast, earnings call, or social media video is enough to clone someone's voice. A handful of photos can generate a realistic video of their face.

What Are Deepfakes and How Do They Work?

Deepfakes are synthetic media created using artificial intelligence, specifically deep learning algorithms. The technology analyzes real audio, video, or images of a person and generates new content that mimics their appearance, voice, and mannerisms.

There are several types of deepfakes relevant to business threats:

• Audio deepfakes (voice cloning): AI generates speech that sounds like a specific person. Modern voice cloning can produce convincing results from as little as three seconds of sample audio. The cloned voice can say anything the attacker wants.
• Video deepfakes (face swapping): AI maps one person's face onto another person's body in video. This can be done in real-time during video calls, making it possible to impersonate someone during a live conversation.
• Image deepfakes: AI generates realistic photos of people who do not exist, or places real people in situations that never happened. These can be used for fake profiles, forged documents, or social engineering.
• Text deepfakes: Large language models generate written communications that mimic a specific person's writing style, tone, and vocabulary.

The barrier to creating deepfakes has dropped dramatically. Tools that were only available to researchers two years ago are now available as consumer-grade applications. Any motivated attacker can access them.

How Deepfakes Are Used Against Businesses

Deepfakes are not just a theoretical risk. Here are the ways attackers are already using them against businesses.

CEO fraud and executive impersonation

The most common business deepfake attack is voice cloning for CEO fraud. An attacker clones the CEO's voice using publicly available audio — earnings calls, conference presentations, podcast interviews, or social media videos. They then call an employee (typically in finance) posing as the CEO and request an urgent wire transfer, a change in payment details, or the release of sensitive information.

This is an evolution of traditional social engineering attacks. The difference is that the employee now hears the CEO's actual voice, making the deception far more convincing than a text-based email or message.

Video call impersonation

Real-time video deepfakes allow attackers to impersonate executives during video calls. An attacker joins a video conference as the CEO, CFO, or other authority figure, complete with their face and voice. They use the meeting to authorize transactions, share sensitive information, or direct employees to take specific actions.

In one widely reported incident, an employee at a multinational company was tricked into transferring $25 million after a video call with what appeared to be the company's CFO and several other colleagues — all of whom were deepfakes.

Vendor and client impersonation

Deepfakes are not limited to impersonating your own executives. Attackers can also impersonate your vendors, clients, or business partners. A cloned voice call from a "vendor" requesting a change to their payment account details, or a video call with a "client" approving a change to project scope, can be just as damaging.

Social engineering enhancement

Deepfakes supercharge traditional social engineering. A phishing email becomes far more convincing when followed by a voice call from the "CEO" confirming the request. An AI-powered phishing attack combined with a deepfake voice call creates a multi-channel deception that is extremely difficult for employees to detect.

Recruitment fraud

A growing trend involves attackers using deepfakes during job interviews to get hired under false identities. Once inside the organization, they have legitimate access to systems, data, and networks. This is particularly concerning for remote-hire positions where in-person verification never occurs.

Why Small Businesses Are Vulnerable

You might think deepfake attacks target only large corporations. In reality, small businesses face unique vulnerabilities.

Less formal verification processes. Large companies often have multi-step approval processes for financial transactions. In a small business, a single phone call from the CEO might be all it takes to authorize a wire transfer — because that is how things have always been done.

Public availability of source material. Business owners post videos on LinkedIn, appear on podcasts, speak at local events, and have their voices recorded on company YouTube channels and voicemail greetings. This provides ample material for voice cloning.

Flat organizational structures. In a small business, employees are more likely to interact directly with the CEO or owner, making impersonation of that person more impactful. An employee who regularly takes direction from the CEO by phone will not question a voice call that sounds like the CEO.

Limited awareness. Many small business employees have never heard of deepfakes or do not realize the technology has advanced to the point of being a practical threat. They are not looking for it, so they will not spot it.

How to Spot a Deepfake

Detecting deepfakes is getting harder as the technology improves, but there are still telltale signs to watch for.

Audio deepfakes

• Slightly robotic or unnatural speech patterns, especially at the beginning and end of sentences
• Unusual pauses, breathing patterns, or lack of normal verbal fillers
• Background noise that sounds artificial or inconsistent
• The voice sounds "too clean" — real phone calls have ambient noise and compression artifacts
• Emotional tone that does not match the content or situation

Video deepfakes

• Inconsistent lighting or shadows on the face versus the body or background
• Blurring or distortion around the edges of the face, hairline, or ears
• Unnatural eye movement or blinking patterns
• Lip movements that do not perfectly match the audio
• Teeth that look blurred or lack detail
• Skin texture that appears too smooth or uniform
• Head movements that seem slightly delayed or disconnected from body movements

However, do not rely solely on visual or audio detection. The technology is improving rapidly, and the best deepfakes are already nearly indistinguishable from real media. Process-based defenses are more reliable than trying to spot fakes with the naked eye.

How to Protect Your Business

The best defense against deepfake attacks is not technology — it is process. Here are practical steps every business can take.

Establish verification protocols

Create a rule: any request involving money, sensitive data, or account changes must be verified through a separate, pre-established communication channel. If someone calls requesting a wire transfer, hang up and call them back on a known number. If someone requests a change via video call, confirm via a separate email or in-person conversation.

Create code words or challenge phrases

Establish secret code words or challenge-response phrases that can be used to verify identity during phone or video calls. If the caller cannot provide the code word, the request should be treated as suspicious regardless of how convincing they sound.

Implement multi-person approval

Require at least two people to approve any financial transaction above a defined threshold. This eliminates the single point of failure that deepfake attackers exploit. The second approver should verify independently — not on the same call or channel as the original request.

Limit publicly available audio and video

The less source material available, the harder it is to create a convincing deepfake. Consider the trade-off between public visibility and security. You do not need to stop all public appearances, but be aware that every video and audio recording is potential source material.

Train your team

Make deepfake awareness part of your regular security training. Employees need to know that this threat exists, how it works, and — most importantly — what verification processes to follow when they receive unexpected requests. Show them examples of deepfake audio and video so they understand the quality of current technology.

Use technology carefully

Some video conferencing platforms are beginning to offer deepfake detection features. These can be helpful but should not be relied upon as a sole defense. Detection technology is in an arms race with creation technology, and detection often lags behind.

Building a Deepfake Response Plan

Even with good prevention measures, your team should know what to do if they suspect a deepfake attack is in progress or has already succeeded.

1. Stop the transaction. If a suspicious request is in progress, pause immediately. Do not complete any transfers, data sharing, or account changes until the request is verified through a separate channel.
2. Verify independently. Contact the supposed sender through a known, pre-established communication channel — a phone number you have on file, an in-person visit, or a separate email thread. Do not use contact information provided during the suspicious communication.
3. Report immediately. If the request appears to be fraudulent, report it to your manager, IT team, or security contact immediately. Time is critical — especially for financial transactions, which may be recoverable if caught quickly.
4. Preserve evidence. Save any recordings, messages, call logs, or emails associated with the incident. This evidence will be important for investigation, insurance claims, and potential law enforcement involvement.
5. Notify relevant parties. If money was transferred, contact your bank immediately to attempt recovery. Notify your cyber insurance carrier. If the attack involved impersonation of a specific person, notify them as well.

Your Next Steps

Deepfake attacks are here, and they are growing more sophisticated every month. The good news is that the defenses are straightforward and affordable — they are primarily about process, not technology. Here is your action plan.

1. This week: Brief your finance team and anyone who processes payments or handles sensitive data about deepfake threats. Make sure they understand that voice and video can be faked.
2. Next week: Establish a verification protocol for all financial transactions and sensitive requests. Define the threshold, the verification channel, and the approval process.
3. Within 30 days: Create and distribute code words or challenge phrases to key personnel. Make deepfake awareness part of your security training program.
4. Within 60 days: Review and limit publicly available audio and video of executives and key personnel where possible. Implement multi-person approval for financial transactions above your defined threshold.
5. Ongoing: Update your training as deepfake technology evolves. Test your verification processes periodically. Stay informed about new attack methods and detection tools.

The era of trusting a phone call because it "sounds like" the right person is over. In a world where voices and faces can be synthesized on demand, verification processes — not sensory perception — are your line of defense. Build those processes now, before you need them.