{
  "id": 6812,
  "url": "https://arxiv.org/abs/2603.23117v2",
  "title": "TRAP: Hijacking VLA CoT-Reasoning via Adversarial Patches",
  "summary": "By integrating Chain-of-Thought (CoT) reasoning, Vision-Language-Action (VLA) models have demonstrated strong capabilities in robotic manipulation, particularly by improving generalization and interpretability. However, the security of CoT-based reasoning mechanisms remains largely unexplored. In this paper, we show that CoT reasoning introduces a novel attack vector for targeted behavior hijacking--for example, causing a robot to mistakenly deliver a knife to a person instead of an apple--witho",
  "authors": "Zhengxian Huang, Wenjun Zhu, Haoxuan Qiu, Xiaoyu Ji, Wenyuan Xu",
  "category": "research",
  "topics": "safety-alignment,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-03-24T12:14:12.000Z",
  "fetched_at": "2026-07-14T16:32:45.894Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/6812",
  "original_url": "https://arxiv.org/abs/2603.23117v2",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}