Demystifying RCE Vulnerabilities in LLM-Integrated Apps
Tong Liu, Zizhuang Deng, Guozhu Meng, Yuekang Li, Kai Chen

TL;DR
This paper systematically investigates RCE vulnerabilities in LLM-integrated frameworks and apps, developing novel detection and exploitation techniques, uncovering 20 vulnerabilities, and proposing mitigation strategies to enhance security.
Contribution
It introduces LLMSmith, a novel system combining static analysis and prompt-based exploitation to identify and verify RCE vulnerabilities in LLM-integrated applications, filling a significant research gap.
Findings
Discovered 20 RCE and arbitrary file read/write vulnerabilities in 11 frameworks.
Successfully exploited RCE vulnerabilities in 17 out of 51 tested apps.
17 vulnerabilities confirmed by developers, with 11 assigned CVE IDs.
Abstract
LLMs show promise in transforming software development, with a growing interest in integrating them into more intelligent apps. Frameworks like LangChain aid LLM-integrated app development, offering code execution utility/APIs for custom actions. However, these capabilities theoretically introduce Remote Code Execution (RCE) vulnerabilities, enabling remote code execution through prompt injections. No prior research systematically investigates these frameworks' RCE vulnerabilities or their impact on applications and exploitation consequences. Therefore, there is a huge research gap in this field. In this study, we propose LLMSmith to detect, validate and exploit the RCE vulnerabilities in LLM-integrated frameworks and apps. To achieve this goal, we develop two novel techniques, including 1) a lightweight static analysis to examine LLM integration mechanisms, and construct call chains to…
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Taxonomy
TopicsWeb Application Security Vulnerabilities · Software Engineering Research · Advanced Malware Detection Techniques
