LMFO (LLM-assisted Hardware Fuzzing Orchestrator) presents a pioneering approach to hardware fuzzing, aiming to leverage the maturity of software fuzzing techniques to efficiently explore the state space of hardware designs. The proposal outlines a multifaceted framework comprising three core thrusts. The first thrust introduces a novel LLM-assisted data augmentation framework, integrating advanced techniques such as Verilog code completion and repair augmentation to enhance the efficacy of hardware fuzzing. The second thrust focuses on finetuning large language models using state-of-the-art methodologies to optimize hardware fuzzing performance. Finally, the third thrust delves into the evaluation of different LLMs across various hardware designs to provide comprehensive insights into their effectiveness in bug discovery and characterization. By addressing the pressing need for automated and efficient hardware fuzzing tools, LMFO endeavors to reduce the time required for security testing while maintaining high security coverage. Through a meticulous evaluation plan encompassing bug metrics and diverse hardware benchmarks, LMFO aims to establish itself as a versatile and indispensable tool for identifying both known and unknown hardware bugs, thereby contributing to the advancement of hardware security testing practices.