Defense-in-Depth for Generative AI: An Architectural Evaluation and Comparison of LLM Guardrails - Lima, Caroline Miranda Pereira; Piantoni, Jane; Zambelli, Felipe Cajaiba; Silva, Javier Martinez; Braga, Alexandre Melo (Anais Estendidos do Simpósio Brasileiro de Cibersegurança (SBSeg); 2026: Anais Estendidos do XXVI Simpósio Brasileiro de CibersegurançaDO - 10.5753/sbseg_estendido.2026.29281, 2026)
This paper analyzes multi-layered guardrail architectures designed to secure LLMs at runtime. By systematically comparing five frameworks (Prompt Guard, Llama Guard, Llama Firewall, NeMo, and Amazon Bedrock), the study evaluates their structural designs and operational trade-offs through a qualitative architectural systematization. Ultimately, it concludes that selecting the appropriate architecture requires a systematic approach to balance security rigor and model utility.