LLM-Assisted Detection and Repair of Hardware Security Vulnerabilities in Verilog Designs

2026-08-05

AI Summary

This work addresses the critical challenge of detecting security vulnerabilities in hardware designs, which become nearly impossible to fix once fabricated into silicon. To enable early and efficient identification of such flaws, the study introduces a novel approach that leverages large language models (LLMs) for automated hardware security analysis directly from Verilog code. Specifically, the method identifies hardware weaknesses aligned with the Common Weakness Enumeration (CWE) standard by integrating LLMs with domain-specific hardware semantic understanding. Evaluated on a single-module design dataset, the proposed technique demonstrates promising capabilities in early-stage, automated vulnerability detection. Experimental results highlight significant improvements in both automation and scalability, thereby validating the potential of LLMs as a powerful tool for enhancing hardware security assurance during the design phase.

Abstract

Hardware designs, like software, are susceptible to bugs that can introduce security vulnerabilities and create opportunities for malicious exploitation. Unlike software vulnerabilities, however, hardware flaws become permanently embedded in silicon after fabrication, making them difficult or impossible to patch. Many of these weaknesses are categorized under the Common Weakness Enumeration (CWE) framework and include improper access control, exposure of sensitive information, and unintended privilege escalation. To improve the detection of such vulnerabilities, we propose a methodology that leverages a Large Language Model (LLM) to identify potential hardware CWEs directly from hardware designs in Verilog. The proposed approach is evaluated iteratively on a dataset of single-module Verilog designs to assess its effectiveness in detecting hardware security weaknesses. Our results demonstrate the potential of LLMs to augment traditional hardware security analysis by providing automated, scalable assistance for identifying security vulnerabilities during the hardware design process.

Problem

• hardware security vulnerabilities
• Verilog designs
• Common Weakness Enumeration
• security flaw detection
• silicon-level bugs

Innovation

• Large Language Model
• Hardware Security
• Verilog
• CWE
• Vulnerability Detection