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From "Be Careful" to "Here's Why": Investigating User Reasoning with Context-Specific SMS Scam Warnings

Elijah Robert Bouma-Sims, Enze Liu, Alexandra Xinran Li, Lorrie Faith Cranor

2026Year

Abstract

SMS-based scams continue to pose a persistent security threat, yet today's mobile warning interfaces often provide generic alerts that users may overlook. In other domains, context-specific explanations have improved users' ability to evaluate malicious content, and advances in generative AI (GAI) make it feasible to generate such explanations at scale. While service providers are now exploring similar approaches for SMS, it remains unclear how to best present contextual information so that users can act on it appropriately. We conducted a task-based interview study (n=20n=20) with US-based Android users in which participants assessed SMS messages using an inbox-style interface. Participants viewed both current Google Messages warnings and hypothetical contextual warnings. Among other results, our findings indicate that users value the concrete direction and evidence provided by context-specific warnings, which helped them reason about the legitimacy of the message. However, participants had differing preferences on the level of detail necessary or the extent to which AI involvement should be disclosed. We conclude by discussing design implications of our results for integrating context-specific warnings into mobile messaging interfaces, with relevance for both SMS and other scam domains.

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