As large language models (LLMs) are widely deployed, identifying their vulnerability through jailbreak attacks becomes increasingly critical. Optimization-based attacks like Greedy Coordinate Gradient (GCG) have focused on inserting adversarial tokens to the end of prompts. However, GCG restricts adversarial tokens to a fixed insertion point (typically the prompt suffix), leaving the effect of inserting tokens at other positions unexplored. In this paper, we empirically investigate \emph{slots}, i.e., candidate positions within a prompt where tokens can be inserted. We find that vulnerability to jailbreaking is highly related to the selection of the \emph{slots}. Based on these findings, we introduce the \textit{Vulnerable Slot Score} (VSS) to quantify the positional vulnerability to jailbreaking. We then propose SlotGCG, which evaluates all slots with VSS, selects the most vulnerable slots for insertion, and runs a targeted optimization attack at those slots. Our approach provides a position-search mechanism that is attack-agnostic and can be plugged into any optimization-based attack, adding only 200ms of preprocessing time. Experiments across multiple models demonstrate that SlotGCG significantly outperforms existing methods. Specifically, it achieves 14\% higher Attack Success Rates (ASR) over GCG-based attacks, converges faster, and shows superior robustness against defense methods with 42\% higher ASR than baseline approaches. Our implementation is available at \href{https://github.com/youai058/SlotGCG}{https://github.com/youai058/SlotGCG}

翻译：随着大语言模型（LLM）的广泛部署，通过越狱攻击识别其脆弱性变得日益重要。基于优化的攻击方法（如贪婪坐标梯度GCG）通常将对抗性token插入到提示的末尾。然而，GCG将对抗性token限制在固定插入点（通常是提示后缀），而忽略了在其他位置插入token的影响。本文通过实验研究提示中可插入token的候选位置（即“槽位”）。我们发现越狱脆弱性与“槽位”的选择高度相关。基于这些发现，我们提出“脆弱槽位评分”（VSS）以量化越狱攻击的位置脆弱性。随后提出的SlotGCG方法通过VSS评估所有槽位，选择最脆弱的槽位插入token，并针对这些槽位执行定向优化攻击。该方法提供了一种与攻击无关的位置搜索机制，可嵌入任何基于优化的攻击策略，仅增加200毫秒预处理时间。跨多个模型的实验表明，SlotGCG显著优于现有方法：相比GCG基攻击，其攻击成功率（ASR）提升14%，收敛速度更快，且对防御方法的鲁棒性更强（ASR较基线方法提高42%）。我们的实现代码已开源至\href{https://github.com/youai058/SlotGCG}{https://github.com/youai058/SlotGCG}。