On a Tuesday morning earlier this month, an executive from Ferrari NV, CEO by Benedetto Vigna He started receiving a series of unexpected messages claiming to be from him. In these messages, information was given about a major purchase and the manager was asked to help with this. However, the facts emerged at the last moment. So how did the fraudster get caught? How dangerous is deepfake? Here are the details…
Ferrari executive caught the deepfake fraudster impersonating the CEO with a security question
The number and profile photo from which the messages came were not the number and photo Vigna usually used. The Ferrari senior executive realized something was wrong after receiving the messages. This fraud attempt, using deepfake technology, was made by perfectly imitating the CEO’s voice. The person impersonating Vigna said he was calling from another mobile number and wanted to talk about a secret agreement.
However, the manager became suspicious and took a trip to verify who Vigna really was. security question asked: “Benedetto, I’m sorry, but I need to describe you. Can you tell me the name of the book you recommended a few days ago?” When the next answer was an irrelevant book title, the manager who heard the question immediately hung up the phone and reported the situation to the authorities.
Ferrari launched an internal investigation after this deepfake incident. The incident became a prominent example of how AI-based deepfake technologies can be used in fraud. Such fraud attempts are carried out by impersonating high-profile executives.
In May, Mark Read, CEO of advertising giant WPP Plc, was the target of a similar deepfake scam attempt. This year, there appears to be an increase in attempts by scammers to clone voices using AI. Although few, some companies are taking precautions against such threats and teaching their managers how to detect fraud attempts.
What are you thinking? What do you think are the best precautions against such AI-based scams? You can share your opinions in the comments section below.
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