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Surfshark claims deepfake-related fraud has caused at least $3.7 billion in financial losses globally, with social media accounting for 47% of those losses, or $1.73 billion.
A comprehensive investigation by the cybersecurity firm reveals that while the technology is being deployed across various communication channels, social media has emerged as the primary battlefield for these sophisticated scams.
According to the data, social media platforms account for 47% of all recorded losses, totalling $1.73 billion. Luís Costa, Research Lead at Surfshark, emphasises that the scale of this threat is unique because of the viral nature of these platforms.
He notes that scammers gain instant access to billions of users, allowing a single fraudulent video to reach millions of potential victims within hours, often before security teams can detect or remove the content. No other channel offers this level of reach at zero cost to the criminal.
Nor is the financial damage limited to viral social posts. The study identifies a hierarchy of threats where criminals exploit human trust to bypass security. Impersonation fraud – cases where deepfakes are used to mimic real people and bypass identity checks – is the second-largest threat, accounting for $911 million, or 25% of total losses.
Additionally, fake job recruitment schemes have siphoned off another $100 million. Even routine communications have become high-risk, with phone calls, video platforms and messaging apps contributing a combined $174 million in losses.
The UK is particularly badly affected, currently ranking fourth globally for deepfake-related financial damage, with losses reaching $176.8 million. Approximately 78% of these British losses originated on social media.
As these deceptive tactics expand into everyday life, experts warn that technical defences alone are no longer enough. Costa insists that a fundamental shift in user mindset is required, as awareness is the only truly effective defence when a familiar voice or face can no longer be trusted.
To mitigate risk, he advises implementing practical safeguards: establish a private family “safe word” to verify identities, perform a “glitch test”, such as asking a caller to wave their hand across their face to reveal AI distortions, and move away from SMS-based authentication in favour of biometric or hardware security keys.
Finally, users are urged to audit their privacy settings and limit the public sharing of high-resolution personal media, which provides the training data necessary for these AI-driven attacks.
https://surfshark.com/research/chart/deepfake-fraud-origins
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Chris Price
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