Intent-based cross-chain bridges have emerged as an alternative to traditional interoperability protocols by allowing off-chain entities (\emph{solvers}) to immediately fulfill users' orders by fronting their own liquidity. While improving user experience, this approach introduces new systemic risks, such as solver liquidity concentration and delayed settlement. In this paper, we propose a new class of attacks called \emph{liquidity exhaustion attacks} and a replay-based parameterized attack simulation framework. We analyze 3.5 million cross-chain intents that moved \$9.24B worth of tokens between June and November 2025 across three major protocols (Mayan Swift, Across, and deBridge), spanning nine blockchains. For rational attackers, our results show that protocols with higher solver profitability, such as deBridge, are vulnerable under current parameters: 210 historical attack instances yield a mean net profit of \$286.14, with 80.5\% of attacks profitable. In contrast, Across remains robust in all tested configurations due to low solver margins and very high liquidity, while Mayan Swift is generally secure but becomes vulnerable under stress-test conditions. Under byzantine attacks, we show that it is possible to suppress availability across all protocols, causing dozens of failed intents and solver profit losses of up to \$978 roughly every 16 minutes. Finally, we propose an optimized attack strategy that exploits patterns in the data to reduce attack costs by up to 90.5\% compared to the baseline, lowering the barrier to liquidity exhaustion attacks.

翻译：意图型跨链桥通过允许链下实体（求解器）利用自身流动性即时满足用户订单，已成为传统互操作性协议的一种替代方案。尽管提升了用户体验，这种方法也引入了新的系统性风险，例如求解器流动性集中和结算延迟。本文提出了一类新型攻击——流动性枯竭攻击，并构建了一个基于重放的参数化攻击模拟框架。我们分析了2025年6月至11月期间，在三个主要协议（Mayan Swift、Across和deBridge）上跨九个区块链发生的350万笔跨链意图交易，转移了价值92.4亿美元的代币。针对理性攻击者，我们的研究结果表明，在现行参数下，求解器盈利能力较高的协议（如deBridge）具有脆弱性：210个历史攻击实例的平均净利润为286.14美元，其中80.5%的攻击实现盈利。相比之下，Across因求解器利润空间小且流动性极高，在所有测试配置中均保持稳健；Mayan Swift在一般情况下安全，但在压力测试条件下会显现脆弱性。在拜占庭攻击场景下，我们证明了可能抑制所有协议的可用性，导致每约16分钟出现数十笔失败的意图交易，并使求解器利润损失高达978美元。最后，我们提出了一种优化的攻击策略，该策略利用数据中的模式，将攻击成本较基线降低高达90.5%，从而降低了实施流动性枯竭攻击的门槛。