Detecting Hardware Trojans in High-Level Synthesis-Generated RTL using Large Language Models

High-Level Synthesis (HLS)-based VLSI design flows allow designers to start from high-level specifications in a general-purpose programming language like C/C++ and automatically generate an optimized hardware design in a hardware description language (HDL) like Verilog or VHDL. Supply of compromised computer-aided design (CAD) tools by an electronic design automation (EDA) vendor to the chip designers is a great threat that adversely affects the horizontal semiconductor business model. Recent works have examined the potential for security issues induced by a compromised HLS CAD tool and demonstrated how HLS is a prime candidate for hardware Trojan (HT) insertion into any underlying design since it is hard to correlate the high-level description to the generated register-transfer level (RTL) code. Further, it has been shown that the use of compiler-generated intermediate representation (IR) as a likely attack vector for inserting HT in the RTL during an HLS-based IC design flow, taking advantage of the lack of automated methods to analyse logic inside a complex LLVM IR. In this work, we propose, implement, and evaluate a novel HLS security verification framework by leveraging the modern large language models (LLMs). Specifically, we focus on detecting the HTs introduced using Black-Hat HLS and HLS-IRT toolchain by performing functional verification using LLM. The experimental results show that LLMs have an impressive ability to analyse and automatically identify these hardware security anomalies.