Securing Embodied AI: A Deep Dive into LLM-Controlled Robotics Vulnerabilities
Published:Jan 7, 2026 05:00
•1 min read
•ArXiv Robotics
Analysis
This survey paper addresses a critical and often overlooked aspect of LLM integration: the security implications when these models control physical systems. The focus on the "embodiment gap" and the transition from text-based threats to physical actions is particularly relevant, highlighting the need for specialized security measures. The paper's value lies in its systematic approach to categorizing threats and defenses, providing a valuable resource for researchers and practitioners in the field.
Key Takeaways
Reference
“While security for text-based LLMs is an active area of research, existing solutions are often insufficient to address the unique threats for the embodied robotic agents, where malicious outputs manifest not merely as harmful text but as dangerous physical actions.”