Deepfake Phishing: What It Is, How It Works, and How to Protect Yourself

Quick Overview

• Deepfake phishing uses AI-generated or manipulated voices, videos, or images to impersonate trusted people and trick victims into sharing sensitive information, transferring money, or granting access.
• Attackers collect publicly available information, create convincing impersonations, and use urgent or confidential requests to pressure victims into acting.
• Common types include voice-cloning scams, fake video calls, AI-generated executive impersonations, and manipulated images used to support fraudulent identities.
• The safest way to detect these attacks is to verify unusual requests through a separate, trusted communication channel instead of relying on a familiar face or voice.
• This guide covers how deepfake phishing works, common attack types, real-world examples, warning signs, and practical ways to prevent these scams.

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What is deepfake phishing?

Deepfake phishing is a type of cyberattack that uses AI-generated audio, video, images, or messages to impersonate a real person. Attackers use this false identity to trick victims into sharing confidential information, clicking malicious links, or making fraudulent payments.

Deepfake phishing is a combination of deepfake and phishing techniques where deepfake means creating or changing digital content and phishing means manipulating individuals.

Also Read: What Are Adversarial AI Attacks?

How does a deepfake phishing attack work?

Deepfake phishing attack follows five steps. However, the process may differ from case to case depending on the target and desired information.

1. Collecting information about the target

In this step, attackers collect publicly available information including pictures, videos, audio recordings, job title, company, etc. Sometimes they may find out useful information by analyzing social media accounts and company's websites.

2. Creating the deepfake

With the help of AI techniques, the attackers are able to clone a person's voice and manipulate video footage or produce high-quality realistic images. They may develop convincing texts by matching it with a person’s usual tone and language.

3. Contacting the victim

Attackers establish connection with the target by phone, e-mail, messaging app, or video conferencing tool posing as a familiar person like a boss, co-worker, relative, or business partner.

4. Manipulating the victim

Attackers can put pressure on the victim by making use of their fake position. This encourages a victim not to check the authenticity of the demand.

5. Executing the fraud

After gaining trust the attacker asks the victim to transfer funds, reveal passwords or OTPs, provide sensitive data, or click on a harmful link.

What are the common types of deepfake phishing?

The type of attack is determined by the target and can be in one of the following forms.

1. Voice cloning attacks (AI voice phishing)

Voice cloning attacks use AI for imitating somebody's voice. Scammers may call a company employee pretending to be their manager or call a family member pretending to be someone they know who is in trouble. The victim may recognize the voice but act without verifying the identity of the caller.

2. Deepfake video call scams

These scams use AI-generated video to pretend that the attacker is actually a real person in the video call. Attackers may impersonate company executives to request payments, approve transactions, or obtain confidential information.

3. Face-swapping and identity impersonation attacks

Attackers substitute an individual’s face with someone else’s in images and videos. The manipulated media is used for creating fake identities and sending fraudulent messages pretending to be a trustworthy person.

4. Lip-sync and AI-generated video messages

Attackers might manipulate a recording of an individual in order to make their lip movements look like he or she is saying something new. These kinds of videos can be used to give the instructions or make fraud attempts more convincing.

5. Text-based deepfake phishing

The text generated by artificial intelligence can imitate an individual’s writing style or make a message using the information about the target. The text itself cannot be considered deepfake but may be used for supporting impersonation attacks.

6. Hybrid deepfake phishing attacks

Hybrid attacks involve the combination of various methods such as fake executive profile, cloned voice, targeted message, and fraudulent payment request. Multi-channel usage can make the scam harder to recognize.

Understanding how these attacks work starts with understanding how generative AI works. Professionals who want to learn how AI tools create text, voice, and images, and how to use them safely at work, can explore the Generative AI and Prompt Engineering Course.

Real-world examples of deepfake phishing attacks

The following two examples show how far the issue has gone.

1. Arup: Fake executives on a video call (Hong Kong, 2024)

In 2024, an employee of engineering company Arup was deceived during a video conference featuring AI-generated representations of company colleagues. The employee was persuaded to transfer approximately HK 200 million, or USD25.6 million, to fraudulent accounts.

Hong Kong authorities reported that the video conference had been created using publicly available video clips and voices. The incident shows why seeing familiar faces during a meeting is not enough to confirm someone's identity.

2. U.S. government officials: Deepfake voice messages and malicious links (2025)

In May 2025, the FBI issued warnings of an attack in which fraudsters would pose as U.S. government officials through text messages and AI- generated voice messages. These messages were used for the purpose of gaining trust and luring the victims to websites that could potentially steal their credentials.

This case clearly demonstrates the criminal ability to mix voice phishing attacks with regular phishing techniques.

How to identify deepfake phishing attempts

Deepfake media is hard to spot even if you know the impersonated individual well. Rather than trying to detect any unusual physical appearance, pay attention to odd behavior and verify the identity behind them.

1. Watch for unusual visual and audio cues

Some deepfakes may contain subtle flaws, such as:

• Poor lip synchronization
• Unnatural blinking
• Distorted facial movements
• Robotic speech patterns
• Strange pauses or pronunciation

While these signs are not always present, they can indicate manipulation.

2. Be cautious of urgent or confidential requests

Many deepfake phishing attacks create pressure. Urgency is one of the most common tactics used by attackers. Be especially careful when someone requests:

• Immediate payments
• Login credentials
• Verification codes
• Confidential documents
• Secrecy from coworkers or managers

3. Look for unusual communication patterns

Ask yourself whether the communication feels normal. Even a convincing deepfake may not perfectly match a person's normal communication habits.

Red flags include:

• Contact through an unfamiliar platform
• Changes in writing style
• Requests outside the person's normal responsibilities
• Odd meeting behavior

4. Verify links, attachments, and payment details

Many attackers combine deepfake phishing with traditional phishing techniques. Never assume information is legitimate simply because it comes from a familiar face or voice.

Always verify:

• Email addresses
• Website URLs
• Attachments
• Bank account details
• Invoice changes

5. Confirm identities through a separate channel

This is often the most effective defense. If a request involves money, credentials, or sensitive data, independently contact the person using a known phone number, email address, or communication platform. A quick verification can prevent a costly mistake.

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How can you prevent deepfake phishing attacks?

Preventing deepfake phishing requires a combination of careful communication, strong security controls, and clear verification procedures.

1. Verify requests through a separate communication channel

Any unusual request should be always verified through an independent communication channel, which is different from the first one. For instance, when your manager asks about an urgent payment on a video call, call his/her mobile phone and verify the request.

2. Follow established approval procedures

The company must have authorization policies for high-value transactions, changes of bank accounts of suppliers, and requests for confidential information. With dual authorization, one tricked employee will not be able to make a transaction.

3. Train employees to recognize AI-powered social engineering

Security awareness training must include training in recognizing false voice calls, AI-manipulated videos, suspicious messages, and manipulation attempts. Employees must understand how to raise an alert if they suspect something without being punished for their actions.

4. Strengthen authentication and access controls

Multifactor authentication and phishing-resistant solutions such as passkeys or hardware security keys should be implemented along with access control measures that would allow determining which users have access to the sensitive information. This will offer you security of your account but not verification of the payment.

5. Create a culture of verification

Employees should feel encouraged to ask for more information about unusual instructions, regardless of whether they receive such instructions from top-level executives or not. It should be a normal practice to ask for proof of identity.

Conclusion

Deepfake phishing makes scams harder to recognize by using AI-generated voices, videos, and images to impersonate trusted people. Even a convincing video call or familiar voice should not be treated as proof of identity, especially when a request involves money, passwords, or confidential data.

Verifying requests through a separate channel and following approval procedures can help prevent costly mistakes. With regular employee training and strong security controls, individuals and organizations can reduce the risk of deepfake phishing attacks.

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