Security and Privacy in Large-Model-Driven Embodied Agents: Attacks, Defenses, and Future Directions
cs.CR
Submitted: 2026-08-19
Updated: 2026-08-19
Terminology
Sources
- The Safety Challenge of World Models for Embodied AI Agents: A Review
- CHAI: Command Hijacking against embodied AI
- SafeMind: Benchmarking and Mitigating Safety Risks in Embodied LLM Agents
- HazardArena: Evaluating Semantic Safety in Vision-Language-Action Models
- Manipulation Facing Threats: Evaluating Physical Vulnerabilities in End-to-End Vision Language Action Models
- MinD: Learning A Dual-System World Model for Real-Time Planning and Implicit Risk Analysis
- SafeGen-LLM: Enhancing Safety Generalization in Task Planning for Robotic Systems
- LIBERO-Plus: In-depth Robustness Analysis of Vision-Language-Action Models
- From Words to Safety: Language-Conditioned Safety Filtering for Robot Navigation
- Learning from Mistakes: Post-Training for Driving VLA with Takeover Data
- State Backdoor: Towards Stealthy Real-world Poisoning Attack on Vision-Language-Action Model in State Space
- VLSA: Vision-Language-Action Models with Plug-and-Play Safety Constraint Layer
- SafeManip: A Property-Driven Benchmark for Temporal Safety Evaluation in Robotic Manipulation
- Trust in LLM-controlled Robotics: a Survey of Security Threats, Defenses and Challenges
- A Framework for Benchmarking and Aligning Task-Planning Safety in LLM-Based Embodied Agents
- ANNIE: Be Careful of Your Robots
- Propagating Unsafe Actions in LLM Controlled Multi-Robot Collaboration via Single Robot Compromise
- Can We Trust Embodied Agents? Exploring Backdoor Attacks against Embodied LLM-based Decision-Making Systems
- Adversarial Attacks on Robotic Vision Language Action Models
- Constrained Decoding for Safe Robot Navigation Foundation Models
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