A Cross-Lingual Security Evaluation of Prompt Injection Defenses in Small Language Models - Fuziwara Filho, Pedro; Aguiar, Erikson J. de; Traina, Agma J. M. (Anais Estendidos do Simpósio Brasileiro de Cibersegurança (SBSeg), 2026)
Although language models are increasingly deployed in multilingual settings, the literature offers limited insight into the robustness of optimization-based defenses trained in a single language. In this paper, we investigate whether, and in what ways, the language used to construct a prompt influences its effectiveness against prompt injection in small language models. We also examine a defensive strategy against prompt injection, called DefensiveTokens, which can generalize to languages not observed during training. Our findings show that DefensiveTokens provide a robust defense against prompt injection attacks in multilingual applications.