Behind the Refusal: Determining Guardrail Activation via Behavioral Monitoring
As Large Language Models (LLMs) and agentic systems become integrated into real-world applications, ensuring their safety and security is critical. Guardrail systems that detect and block malicious instructions sent to and from an LLM are an essential component of AI security. However, researchers conducting black-box adversarial emulation against production AI systems often struggle to determine whether a guardrail block or an LLM rejection has occurred. This distinction is important because th
Record details
Published: 2 July 2026
Source: arXiv
Category: Research
Topics: Safety & alignment · Agents & autonomy
Retrieved: 14 July 2026
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ethics.ai (2 July 2026), “Behind the Refusal: Determining Guardrail Activation via Behavioral Monitoring,” evidence record 315, https://ethics.ai/record/315 (originally published by arXiv).
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