Adversarial machine learning (AdvML), a discipline that delves into the interaction of machine learning (ML) with ‘adversarial’ elements, has embarked on a new era propelled by the ever-expanding capabilities of artificial intelligence (AI). This momentum has been fueled by recent technological breakthroughs in large multimodal models (LMMs), particularly those designed for vision and language applications. The 3rd AdvML-Frontiers workshop at NeurIPS’24 continues the success of its predecessors, AdvML-Frontiers’22-23, by delving into the dynamic intersection of AdvML and LMMs. The rapid evolution of LMMs presents both new challenges and opportunities for AdvML, which can be distilled into two primary categories: AdvML for LMMs and LMMs for AdvML. This year, in addition to continuing to advance AdvML across the full theory-algorithm-application stack, the workshop is dedicated to addressing the intricate issues that emerge from these converging fields, with a focus on adversarial threats, cross-modal vulnerabilities, defensive strategies, multimodal human/AI feedback, and the overarching implications for security, privacy, and ethics. Join us at AdvML-Frontiers'24 for a comprehensive exploration of adversarial learning at the intersection with cutting-edge multimodal technologies, setting the stage for future advancements in adversarial machine learning. The workshop also hosts the 2024 AdvML Rising Star Award.