Consumer cyber safety is rapidly evolving, with humans increasingly becoming the primary attack surface. In today’s online environment, users face a constant barrage of scams that are growing in sophistication. Keeping up with the changing tactics of threat actors is a challenge even for experienced users, and traditional security solutions are often not enough to prevent manipulation through social engineering.

This presentation introduces a user-centric threat advisory tool designed to bridge this gap. Acting as standalone anti-scam feature and a second-opinion assistant, it helps users interpret potentially dangerous content such as suspicious messages or websites by offering clear, contextual explanations. Rather than replacing existing endpoint protection, it complements it by enhancing user awareness and supporting better decision-making in real time.

We will explore the core functional elements of the tool and evaluate its potential to reduce the impact of impersonating scams and social engineering attacks, an area where traditional AV solutions can struggle.

A key question raised is whether AI-driven solutions can operate effectively on their own, or whether human expertise remains essential to ensuring accuracy and usability. The presentation will examine how the combination of expert input and AI that goes beyond traditional detection methods by knowing context and/or analyzing the intent across SMS, email, and web can improve threat interpretation and user trust, particularly in edge cases where nuance matters.

Finally, we will touch on the implications for testing methodologies. When human interaction significantly influences the outcome, how should such tools be evaluated? This remains an open question, and the audience will be invited to contribute their perspective after the session.