Disruptor
Beyond Detection, Or Not: The New Frontier in Social Engineering Scam Prevention
Imagine a scenario where your client’s CEO joins a call—and it turns out to be a deepfake. With generative AI making fakes nearly undetectable, social engineering attacks are escalating, as seen in multimillion-dollar losses across industries. The quality, scale and complexity of these attacks are growing exponentially—leaving traditional content-based defenses struggling to keep pace.
Consider recent high-profile incidents: the sophisticated attack on MGM costing $30 million, a video-based deepfake assault on Arup's Hong Kong finance team, resulting in a $25 million loss, and impersonation schemes posing as new hires to compromise critical systems. As GenAI evolves, the challenge is clear: how do we effectively block these advanced threats from the get-go?
Leaders in mission-critical industries are beginning to assess solutions that address the prevention of AI-driven impersonation and classic social engineering scams. Let’s envision a defense framework that integrates seamlessly across all collaboration tools and communication channels—calls, video conferences, messaging, SMS, emails—providing real-time, first-encounter verification without cumbersome pre-registration, and doing so with rigorous privacy safeguards.
This session will explore what to do when content based filtering is no longer enough to protect organizations from the escalating risks posed by advanced social engineering generated threats.
