Trajectory-Level Redirection Attacks on Vision-Language-Action Models
Vision-language-action (VLA) policies bring natural language into closed-loop robot control, enabling robots to execute manipulation tasks directly from text instructions. The same interface gives text a recurring role in control because the prompt is reused at every replanning step, and each prompt-conditioned action changes the future observations on which the policy acts. Existing VLA attacks study adversarial prompts that elicit targeted low-level actions or make such actions persist across changing images. We identify a stronger trajectory-level failure mode: a prompt that still $\textit{appears}$ to specify the intended task but redirects the final physical outcome. We mathematicall...
| Authors | Gokul Puthumanaillam, Vardhan Dongre, Pranay Thangeda et al. |
|---|---|
| Primary category | cs.RO |
| Published | 11 June 2026 |
| Last updated at source | 13 June 2026 |
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