Common Examples of Voice Deepfake Attacks

Deepfake voice attacks leverage AI to clone or mimic a real person’s voice with such precision that distinguishing between a real and a fake audio file is becoming increasingly difficult for humans. As a result, voice deepfake attacks pose significant risks to organizations, individuals, and even entire industries.

Voice deepfakes can be used for social engineering attacks, financial fraud, cybercrime, extortion, and even political manipulation. The potential for financial and reputational damage is vast, and knowing how these attacks work is crucial in protecting oneself and one’s organization.

Potential risks of voice deepfake attacks

Between 2016 and 2020, phone channel fraud increased by 350%¹. In 2022, fraud rates in contact centers increased by 40% compared to the previous year.¹

Deepfake cyber attacks can erode trust within companies, as employees may be less confident in the authenticity of communications. For organizations, this uncertainty can lead to financial losses, security breaches, and long-term reputational harm.

Financial institutions, in particular, face serious risks from deepfake technology. Fraudsters can use deepfake audio files to deceive bank employees into authorizing transactions or granting access to sensitive accounts.

Fraudsters are also using deepfakes to pose as job candidates. Deepfake job candidates are applicants who are either completely generated by AI or have significantly altered their appearance or voice with AI. When deepfake candidates infiltrate companies, they can create significant financial, operational, security, and reputational risks.

Examples of voice deepfake attacks

Over the past few years, there has been a significant increase in deepfake attacks, which range from fabricated images to highly realistic manipulated video and audio. High-profile deepfakes typically feature celebrities or politicians and are aimed at causing reputational damage or spreading misinformation.

But fraudsters have evolved and are now deploying sophisticated schemes using deepfake technology to target organizations of all sizes.

Financial fraud and scams

One of the most common uses of deepfake technology is to impersonate high-ranking executives or business partners to commit financial fraud. Scammers are using AI to create audio deepfakes that mimic real people, convincing unsuspecting employees to authorize large financial transfers or share confidential information.

A widely reported incident involved the CEO of a UK-based energy company who was tricked into transferring $243,000 to a fraudulent account. The fraudsters used a deepfake voice of the company’s parent firm CEO to call and instruct the victim to make an urgent payment.

The audio deepfake was so convincing that the CEO did not doubt its authenticity until after transferring the funds. This example of a deepfake cyber attack highlights the vulnerability of organizations to real-time voice deepfakes targeting unsuspecting employees.

Another troubling attack took place in July 2024 when Elon Musk “went live” on YouTube. Upon careful inspection, Pindrop^® technology determined the “live stream” was a 6:42-minute generated audio loop that mimicked Elon Musk’s voice. At one point, “Elon” urges viewers to scan a QR code to access a cryptocurrency website.

The request may have served as a red flag for those well-versed in tech. But otherwise, there were few signs the video was fake. The account posting seemed legitimate, having a verification badge and over 100k subscribers, and the video included a famous person discussing current topics like politics and the US election. The case is a perfect example of how convincing and dangerous such attacks can be.

Cybercrime and extortion

Deepfake technology has also fueled a new breed of cybercrime, with attackers using it to carry out extortion attempts, often targeting high-profile individuals or organizations.

There are growing concerns about ransomware attacks that use deepfake audio to extort money from victims. Many have already heard about people who receive panicked calls from relatives claiming they are in trouble or hurt and need money urgently.

Experts expect these types of scams to grow in number and escalate, targeting even high-profile individuals. Because they exploit emotions and create a sense of urgency, they have a high success rate, despite many campaigns to increase awareness.

Some are even more pessimistic, explaining how deepfake voice attacks could be easily used in blackmail and extortion attempts. Fraudsters could replicate someone’s voice to create fake conversations or incriminating audio clips involving the victims.

These fabricated audio files are then used in blackmail attempts, with attackers threatening to release the content unless a ransom is paid.

Corporate espionage and intellectual property theft

Voice deepfakes are a growing concern in corporate espionage, where attackers seek to access trade secrets and proprietary information.

Impersonating key employees or partners, attackers use deepfake audio to request transfers of funds or confidential information, such as trade secrets, intellectual property, or corporate strategies.

Such an attack occurred at the beginning of 2024 when a scammer walked away with US$25 million. The incident took place at the Hong Kong office of a multinational company. The attack involved a sophisticated deepfake scam with a digitally recreated version of the company’s CFO, along with several other employees.

The victim was requested to join a “video call,” during which he was met with deepfake versions of his employers who requested he transfer $25 million. While the employee found the request strange, the video call, during which multiple people were present, including the CFO, convinced him it couldn’t be a phishing attempt, and he transferred the funds.

Political manipulation and disinformation

In 2024, a robocall imitating President Joe Biden circulated online. Soon enough, the media and the public realized the audio was a deepfake, with many noting that distinguishing a difference between a person’s real voice and a synthetic one was extremely difficult.

The incident was one of several deepfake attacks in 2024, highlighting how difficult it is to distinguish between a real person’s voice and a synthetic one. In July of the same year, a deepfake video parody involving Kamala Harris circulated on the social media platform X.

While the person responsible admitted the video was nothing but a parody and the voice appearing to be Kamala Harris’ was AI-generated, the incident serves as a reminder of how hard it is to spot fact from fiction.

Another gross attempt at disinformation took place in 2022 when, soon after the conflict between Ukraine and Russia started, a deepfake video of President Zelenskyy telling his soldiers to surrender circulated online. It first appeared on social media and was shared by a Ukrainian news website before being taken down.

Each of these deepfakes was quickly debunked, but their rapid dissemination online adds to the challenge of mitigating these threats.

Social engineering and phishing attacks

Voice deepfakes are a powerful tool for social engineering attacks, which exploit human trust and relationships to gain access to sensitive information.

An example we previously saw, with an employee transferring $25 million to attackers, shows just how sophisticated AI-backed phishing attempts can be. The victim was well-versed in these types of attacks and was suspicious from the moment he received the invite to the video call. However, once he joined the call and saw not just the CFO but several other employees were present, his suspicions dissolved.

Detecting voice deepfake attacks

Deepfake attacks are fueled by AI technology that is only advancing and evolving. A few methods and tools can help identify deepfakes, such as analyzing inconsistencies in audio files or using deep learning algorithms trained to detect voice manipulation.

For instance, AI-based tools can detect deepfakes as they analyze various characteristics of the audio, such as voice pitch, tone, and cadence, looking for subtle anomalies that signal manipulation. They can identify small inconsistencies in speech patterns or unnatural fluctuations in tone that would be challenging for a human to notice.

Another method that can help detect voice deepfakes is speech pattern analysis. Every individual has a unique way of speaking, including subtle idiosyncrasies like timing, emphasis on certain syllables, or habitual pauses.
Deepfakes, no matter how well-produced, often struggle to replicate these specific patterns consistently. Detection systems analyze these natural variations to flag possible deepfakes. For example, slight timing irregularities or unnatural shifts in emphasis can indicate that an audio clip is fake.

Start combating voice deepfake attacks

Combating voice deepfake attacks requires a combination of advanced technology and strong organizational awareness. With all the new deepfake technologies, comprehensive strategies are vital in defending against these threats.

One effective solution is Pindrop^® Pulse, our deepfake detection technology designed to identify deepfake audio in real time. Pindrop^® Pulse analyzes voice signals for subtle inconsistencies that even some of the most sophisticated deepfakes cannot hide.

With its advanced AI and machine learning techniques, Pindrop liveness detection technology helps organizations differentiate between human voice interactions and potential deepfake attacks. This tool is particularly useful for financial institutions and businesses that rely on voice channels to secure sensitive transactions.