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Recent research highlights severe security flaws in commercially available embodied AI systems, specifically Unitree humanoid and quadruped robots. Vulnerabilities including undocumented backdoors, hard-coded cryptographic keys, and unauthenticated APIs enable remote attackers to hijack devices, exfiltrate sensitive multimodal telemetry, and pivot across physical fleets via wireless interfaces.
TrendAI presented research at RSAC 2026 highlighting the dual emergence of autonomous, agentic AI-driven cybercrime and systemic vulnerabilities in cyber-physical systems like EV charging infrastructure. The findings emphasize the necessity for organizations to adopt machine-speed, AI-driven defenses and comprehensive frameworks like NIST IR 8473 to mitigate these rapidly evolving threats.
