arXiv:2605.10807v3 Announce Type: replace-cross Abstract: The integration of Large Language Models (LLMs) into Electronic Design Automation (EDA) and hardware security is rapidly reshaping the semiconductor industry. While LLMs offer unprecedented capabilities in generating Register Transfer Level (RTL) code, automating testbenches, and bridging the semantic gap between high-level specifications and silicon, they simultaneously introduce severe vulnerabilities. This comprehensive review provides an in-depth analysis of the state-of-the-art in LLM-driven hardware design, organized around key ad
The rapid advancement and integration of LLMs into critical design processes like Electronic Design Automation (EDA) is forcing an immediate reckoning with their inherent security vulnerabilities, especially in hardware design.
This development highlights a growing and critical intersection between AI capabilities and foundational hardware security, directly impacting semiconductor reliability and national security.
The paradigm for secure hardware design must now account for LLM-introduced vulnerabilities and incorporate new methodologies to mitigate these risks.
- · Hardware security firms
- · AI robustness companies
- · Semiconductor companies investing in secure EDA
- · Unprepared semiconductor manufacturers
- · EDA tool vendors without robust security features
Increased investment in research and development of secure LLM-driven hardware design methodologies.
New regulatory standards and certifications for AI-assisted hardware design processes and products.
The emergence of 'AI-native' hardware attacks and defenses, fundamentally reshaping cyber warfare at the silicon level.
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Read at arXiv cs.LG