Author

Matheus Azevedo de Sá

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Preprint Oct 2026

Combining Long-Term Memory and LLMs Comes at a High Cost: From Prompt Injection to Persistent Compromise

The widespread adoption of generative artificial intelligence in recent years has brought a parallel rise in prompt injection and jailbreak attacks. By embedding malicious instructions, these exploits manipulate language models to bypass intended behavior and operational boundaries. In traditional chatbots, such attack...

Pedro H. Barcha Correia, Matheus Azevedo de Sá, P. D. de Senna et al. · 0 citations

Review Open access Sep 2026

UnifiedBench: Toward a Unified Dataset for Red-Teaming Language Models

Adversarial prompting constitutes one of the principal threats to deployed Large Language Models, yet the evaluation of alignment robustness against such attacks is hindered by the fragmentation of existing benchmark datasets. AdvBench, HarmBench, and JailbreakBench — the three most adopted adversarial prompt datasets...

Matheus Azevedo de Sá, P. D. de Senna, M. P. Pagliuso et al. · Anais Estendidos do XXVI Sim... · 0 citations