The Open Network (TON) blockchain employs an asynchronous execution model that introduces unique security challenges for smart contracts, particularly race conditions arising from unpredictable message processing order. While previous work established vulnerability patterns through static analysis of audit reports, dynamic detection of temporal dependencies through systematic testing remains an open problem. We present BugMagnifier, a transaction simulation framework that systematically reveals vulnerabilities in TON smart contracts through controlled message orchestration. Built atop TON Sandbox and integrated with the TON Virtual Machine (TVM), our tool combines precise message queue manipulation with differential state analysis and probabilistic permutation testing to detect asynchronous execution flaws. Experimental evaluation demonstrates BugMagnifier's effectiveness through extensive parametric studies on purpose-built vulnerable contracts, revealing message ratio-dependent detection complexity that aligns with theoretical predictions. This quantitative model enables predictive vulnerability assessment while shifting discovery from manual expert analysis to automated evidence generation. By providing reproducible test scenarios for temporal vulnerabilities, BugMagnifier addresses a critical gap in the TON security tooling, offering practical support for safer smart contract development in asynchronous blockchain environments.

翻译：开放网络（TON）区块链采用异步执行模型，这为智能合约引入了独特的安全挑战，特别是由于消息处理顺序不可预测而引发的竞态条件。尽管先前研究通过审计报告的静态分析建立了漏洞模式，但通过系统化测试动态检测时序依赖仍然是一个未解决的问题。我们提出了BugMagnifier，这是一个通过受控消息编排系统化揭示TON智能合约漏洞的交易模拟框架。该工具构建于TON沙箱之上，并与TON虚拟机（TVM）集成，结合了精确的消息队列操控、差分状态分析和概率置换测试，以检测异步执行缺陷。实验评估通过对专门构建的漏洞合约进行广泛的参数化研究，证明了BugMagnifier的有效性，揭示了与理论预测相符的消息比例依赖型检测复杂度。该量化模型实现了可预测的漏洞评估，同时将发现过程从手动专家分析转向自动化证据生成。通过为时序漏洞提供可复现的测试场景，BugMagnifier填补了TON安全工具链的关键空白，为异步区块链环境中更安全的智能合约开发提供了实用支持。