BugWhisperer: Fine-Tuning LLMs for SoC Hardware Vulnerability Detection
This addresses security verification challenges for SoC hardware designers, though it appears incremental as it applies existing fine-tuning methods to a new domain.
The paper tackles the problem of manual and inflexible security verification for system-on-chips (SoCs) by proposing BugWhisperer, a framework that uses a fine-tuned large language model to automate vulnerability detection, resulting in improved efficiency and flexibility.
The current landscape of system-on-chips (SoCs) security verification faces challenges due to manual, labor-intensive, and inflexible methodologies. These issues limit the scalability and effectiveness of security protocols, making bug detection at the Register-Transfer Level (RTL) difficult. This paper proposes a new framework named BugWhisperer that utilizes a specialized, fine-tuned Large Language Model (LLM) to address these challenges. By enhancing the LLM's hardware security knowledge and leveraging its capabilities for text inference and knowledge transfer, this approach automates and improves the adaptability and reusability of the verification process. We introduce an open-source, fine-tuned LLM specifically designed for detecting security vulnerabilities in SoC designs. Our findings demonstrate that this tailored LLM effectively enhances the efficiency and flexibility of the security verification process. Additionally, we introduce a comprehensive hardware vulnerability database that supports this work and will further assist the research community in enhancing the security verification process.