Cybersecurity AI: Hacking Consumer Robots in the AI Era (2026)

[2603.08665] Cybersecurity AI: Hacking Consumer Robots in the AI Era Support arXiv on Cornell Giving Day! We're celebrating 35 years of open science - with YOUR support! Your generosity has helped arXiv thrive for three and a half decades. Give today to help keep science open for ALL for many years to come. Donate! --> Computer Science > Cryptography and Security arXiv:2603.08665 (cs) [Submitted on 9 Mar 2026 ( v1 ), last revised 10 Mar 2026 (this version, v2)] Title: Cybersecurity AI: Hacking Consumer Robots in the AI Era Authors: Víctor Mayoral-Vilches , Unai Ayucar-Carbajo , Olivier Laflamme , Ruikai Peng , María Sanz-Gómez , Francesco Balassone , Lucas Apa , Endika Gil-Uriarte View a PDF of the paper titled Cybersecurity AI: Hacking Consumer Robots in the AI Era, by V\'ictor Mayoral-Vilches and 6 other authors View PDF HTML (experimental) Abstract: Is robot cybersecurity broken by AI? Consumer robots -- from autonomous lawnmowers to powered exoskeletons and window cleaners -- are rapidly entering homes and workplaces, yet their security remains rooted in assumptions of specialized attacker expertise. This paper presents evidence that Generative AI has fundamentally disrupted robot cybersecurity: what historically required deep knowledge of ROS, ROS 2, and robotic system internals can now be automated by anyone with access to state-of-the-art GenAI tools spearheaded by the open source CAI (Cybersecurity AI). We provide empirical evidence through three case studies: (1) compromising a Hookii autonomous lawnmower robot, uncovering fleet-wide vulnerabilities and data protection violations affecting 267+ connected devices, (2) exploiting a Hypershell powered exoskeleton, demonstrating safety-critical motor control weaknesses and credential exposure including access to over 3,300 internal support emails, and (3) breaching a HOBOT S7 Pro window cleaning robot, achieving unauthenticated BLE command injection and OTA firmware exploitation. Across these platforms, CAI discovered in an automated manner 38 vulnerabilities that would have previously required months of specialized security research. Our findings reveal a stark asymmetry: while offensive capabilities have been democratized through AI, defensive measures often remain lagging behind. We argue that traditional defense-in-depth architectures like the Robot Immune System (RIS) must evolve toward GenAI-native defensive agents capable of matching the speed and adaptability of AI-powered attacks. Subjects: Cryptography and Security (cs.CR) Cite as: arXiv:2603.08665 [cs.CR] (or arXiv:2603.08665v2 [cs.CR] for this version) https://doi.org/10.48550/arXiv.2603.08665 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Víctor Mayoral Vilches [ view email ] [v1] Mon, 9 Mar 2026 17:40:47 UTC (984 KB) [v2] Tue, 10 Mar 2026 20:35:50 UTC (984 KB) Full-text links: Access Paper: View a PDF of the paper titled Cybersecurity AI: Hacking Consumer Robots in the AI Era, by V\'ictor Mayoral-Vilches and 6 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.CR < prev | next > new | recent | 2026-03 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... 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