Test-time Adversarial Takeover: A Real-time Hijacking Interface against Robotic Diffusion Policies
Diffusion-based action generation has become a foundational component of embodied AI, but its reliance on visual conditioning leaves deployed visuomotor policies vulnerable to adversarial manipulation. Most prior attacks focus on disruption: they perturb the observation stream to reduce task success or induce erratic behavior. We study a stronger threat, Test-time Adversarial Takeover (TAKO), in which an attacker obtains a real-time steering interface over a frozen robot policy and turns it into a remotely piloted instrument. TAKO learns a small vocabulary of reusable universal patches through differentiable diffusion inference; at test time, the attacker switches among these patches in t...
| Authors | Zi Yin, Peilin Chai, Siyuan Huang et al. |
|---|---|
| Primary category | cs.RO |
| Published | 9 June 2026 |
| Last updated at source | 9 June 2026 |
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