Pair-Aware Optimization: Coordinating Exploration and Refinement for Jailbreaking LLM Agents
Large Language Model (LLM) agents are vulnerable to adversarial inputs that induce attacker-specified malicious behaviors, commonly referred to as jailbreaking. Existing optimization-based jailbreak attacks primarily employ first-order (FO) methods that leverage gradient information or zeroth-order (ZO) methods that rely on function-value feedback. However, their complementarity and optimization ordering remain underexplored. We systematically investigate four strategies: pure ZO, pure FO, ZO->FO, and FO->ZO, and develop a ZO-FO framework that explores adversarial prefixes through ZO optimization and refines their corresponding suffixes through FO optimization. To coordinate the two proce...
| Authors | Juanyang Xu, Zheng Wang, Xingyu Zhao et al. |
|---|---|
| Primary category | cs.LG |
| Published | 17 October 2026 |
| Last updated at source | 17 October 2026 |
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