Agentic software reverse engineering systems are vulnerable to prompt injection attacks placed into the source code of executable binary files. This research demonstrates defensive tactics for detecting the presences of prompt injection strings in the decompiler output of adversarial example programs. Methods for obfuscating these attacks and subsequent methods for defending against these obfuscations are also explored. This research advances the understanding of risk and security of agentic software analysis systems necessary for their deployment into production-level cyber workflows.

翻译：基于智能体的软件逆向工程系统易受可执行二进制文件源码中植入的提示注入攻击威胁。本研究展示了在对抗性示例程序的反编译器输出中检测提示注入字符串存在的防御策略，同时探讨了针对此类攻击的混淆方法及后续应对混淆的防御技术。该研究深化了对智能体软件分析系统在实际网络工作流部署中所需风险与安全机制的理解。