On the Security and Privacy Implications of Large Language Models: In-Depth Threat Analysis

Large Language Models (LLMs) have gained popularity since the release of ChatGPT in 2022. These systems utilize Artificial Intelligence (AI) algorithms to analyze natural language, enabling users to have sophisticated real-time conversations with them. The existing literature on LLMs is mostly focused on system design and lacks dedicated research on investigating privacy and security issues. To safeguard the interests of various stakeholders, it is crucial to understand the associated security and privacy risks of these models. Our study utilized STRIDE and LINDDUN methodologies to investigate security and privacy threats of LLMs. We presented a detailed system model of LLMs and analyzed the potential threats, vulnerabilities, security considerations, and mitigation tactics intrinsic to the design and deployment of various system components. Our comprehensive threat assessment showcases potential threats imminent to the current generation of LLMs, such as unintentional data leakage or system misuse by malicious actors. Furthermore, our study discusses the importance of proactive security measures in LLM development, deployment, and maintenance.