Benchmarking Jailbreak Guardrails for Embodied Agents
Embodied agents powered by large language models and vision-language models are increasingly deployed in physical environments, but jailbreak attacks can induce these agents to perform physically harmful actions. A growing number of guardrail methods have been proposed to intercept dangerous behavior before it is executed, yet existing safety benchmarks evaluate the embodied models themselves, leaving it unclear how well these guardrails actually defend an embodied agent in practice. We present the first systematic evaluation of jailbreak guardrails for embodied agents. To compare guardrails under identical conditions, we build a pluggable evaluation framework that treats the embodied age...
| Authors | Xunguang Wang, Qingyue Wang, Yuguang Zhou et al. |
|---|---|
| Primary category | cs.AI |
| Published | 5 October 2026 |
| Last updated at source | 5 October 2026 |
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