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Three men charged in US with using AI to impersonate CEOs and steal millions

Men allegedly impersonated voices and images of executives to convince employees to send large payments Three foreign nationals were arrested and charged with using AI to allegedly impersonate corporate CEOs and attorneys to steal over $100m, according to an indictment that was newly unsealed by the US Department of Justice. According to a press release from the United States attorney’s office…

Three men charged in US with using AI to impersonate CEOs and steal millions

Three men from foreign countries have been charged by the U.S. Department of Justice with using artificial intelligence to impersonate corporate executives and attorneys in order to defraud over $100 million from various companies, according to a newly unsealed indictment. Jacob Soall, Sharon Hazan, and Guy Sheetrit were arrested in the United Kingdom, Spain, and the United States, respectively.

The alleged scheme took place between 2024 and 2026. The fraudsters allegedly convinced employees to transfer large sums of money by pretending to be high-level executives and lawyers. They stole more than $129 million from companies worldwide, including $5 million from a Missouri hospital, $2.7 million from a Rhode Island bank, $3 million from a California hospital, over $4.6 million from a Massachusetts mutual fund, and $5 million from a Florida pet food company.

The men directed employees to wire money to various bank accounts across the globe, including the United States, Spain, Portugal, Greece, the United Arab Emirates, Singapore, Austria, Slovakia, and China. After receiving the funds, they converted them into cryptocurrency to conceal their source and ownership. Soall and Hazan used multiple aliases during the operation.

The FBI and the U.S. Attorney's office for the Southern District of New York are investigating the case, emphasizing the potential misuse of AI for criminal purposes.

Written by urgent.news from Guardian Technology's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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