A recent paper discusses the challenges faced by Vision Language Action Models (VLAMs) in robotic manipulation tasks, particularly focusing on their physical vulnerabilities. As advancements in Multimodal Large Language Models (MLLMs) continue, ensuring the safety and robustness of these models during real-world interactions becomes increasingly important. This research is crucial as it addresses the potential risks associated with robotic systems operating in dynamic environments, highlighting the need for improved safety measures.