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PhantomTac: Hijacking Robotic Tactile Systems with Deploy-and-forget Tags

Binbin Zhang, Yifeng Zhang, Xiaomeng Chen, Dongyao Chen · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.26174 · cited by 0 works (OpenAlex) · open-access PDF

Chinese

极限触摸机械攻击控制设备是95%的密封机器人操作的关键,为精密的、封闭环节力量控制提供了重要基础。在各种触摸传感技术中,磁触摸传感器直接脱颖而出,由于其精细的、三维的反触摸力感知能力和强大的感官对视觉封闭的强度。在本研究中,我们发现一个名为PhantomTac的物体磁触摸传感器的物体表面上的物理漏洞,因此,攻击者可以轻松地改变磁场,从而破坏磁触摸传感器所解释的力量。攻击者可以通过简单地附加一个薄(厚度大约为 0.5 毫米)的物理漏洞来隐藏这种攻击。因此,攻击标签可以通过基于线条码

Machine translation (Meta M2M100); the English original follows.

Abstract

Tactile perception is crucial for precise robotic manipulation, providing an important foundation for dexterous, closed-loop force control. Among various tactile sensing techniques, magnetic tactile sensors stand out thanks to their fine-grained, three-dimensional force perception capability and strong robustness against visual occlusion. In this study, we discover a physical loophole called PhantomTac in magnetic tactile sensors. The attacker can alter the magnetic field, thus spoofing the force interpreted by magnetic tactile sensors. The attacker can stealthily deploy such an attack by simply attaching a thin (the thickness is around 0.5 mm), battery-free magnetic tag to the surface of an object. Hence, the attack tag can be easily concealed by a barcode sticker. Such an attack scheme is "deploy-and-forget" -- the attacker can deploy the tag and leave. When a robotic hand is picking up an object, it may severely damage the object. Specifically, spoofing the normal force can crush the object, whereas spoofing the shear force can lead to a loose grip, thus dropping the object. Compared with directly sabotaging the robotic hand, PhantomTac is much more concealed as the attacker does not need access to the device. We performed extensive reverse-engineering efforts to characterize the sensing mechanism of commercial-off-the-shelf tactile sensors and proposed a practical tag design. End-to-end evaluations conducted on real robots and robotic arms demonstrate that our attack can bypass existing anti-interference mechanisms and effectively hijack their closed-loop control processes, achieving an attack success rate exceeding 95% when the grasping-position offset is bounded within 8 mm. Finally, based on the limitations of existing anti-magnetic interference mechanisms, we propose a multimodal-consistency defense mechanism to mitigate such physical-layer security threats.

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Topics: Spoofing attack, Robustness (evolution), Computer science, Robot, Tactile perception, Tactile sensor

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