In an age where embodied AI systems are moving from concept to reality, security teams face an urgent need to address the unique risks associated with these cyber-physical entities. Unlike traditional software, when AI takes on a physical form, it incurs a variety of vulnerabilities that aren’t immediately apparent during vendor demonstrations. These demos often showcase simplistic tasks executed flawlessly, disguising the complex security challenges that arise when such systems are operational.
Security professionals are increasingly recognizing that these systems can no longer be evaluated solely on their demonstration capabilities. The transition to procurement has changed the game, making it essential for security teams to have a clear picture of what they’re approving. Vendors often provide limited insight into the actual security contexts of their products, making it difficult to assess potential risks accurately.
Understanding Embodied AI
Embodied AI involves integrating robust models into physical machines — whether they be robots, automated arms, or humanoids. This model starts as software but upon gaining hardware components, it becomes part of a larger cyber-physical system. Each unit now includes a variety of control elements, sensors, and potentially insecure pathways that invite scrutiny. It’s not just software anymore; it’s a complex system that unites hardware and software under a common operational umbrella.
Five Key Evaluation Questions
Security teams must pivot to five essential questions to evaluate the integrity and safety of embodied AI systems:
1. Provenance
Questions of provenance arise because buyers often lack insight into the components that make up a humanoid robot or any embodied AI system. These machines are often constructed from parts sourced from various suppliers — firms that buyers might not even know exist. Without thorough vetting of these components, risks multiply. Just as the software industry adopted the Software Bill of Materials to enhance transparency, the same approach should be applied here. Buyers should demand a detailed hardware and firmware bill for any system being considered.
2. Access
Controlling who can access these systems is pivotal. Operators install and maintain these machines, and vendors remotely push updates. Any remote-access capabilities should be regarded as privileged entry points rather than simple conveniences. Past experiences in Operational Technology (OT) signal a clear trend: unmanaged remote access is a significant risk factor. Thus, understanding every channel of connectivity becomes essential to securing these systems against potential threats.
3. Integrity
Integrity concerns focus on a machine’s susceptibility to misperception or erroneous behavior — especially with systems relying on critical sensors. Issues like Lidar spoofing can lead to severe operational failures. Unlike traditional software errors, which can often be diagnosed through logs, physical misbehaviors of embodied systems pose new challenges. Buyers must ask vendors about their approaches to modeling threats and validating sensor outputs, asking specifically how they would ensure transparency and accountability if deceptive behavior occurs.
4. Evidence
What substantiates the vendor’s performance claims? Buyers typically find themselves relying on metrics provided by vendors without independent verification. To mitigate this risk, it’s necessary to insist on concrete evidence regarding uptime, incidence of failures, and reliability metrics from established deployments. The performance data should be auditable and verifiable through independent sources.
5. Accountability
When systems fail, who bears the risk? The cloudy notion of shared responsibility remains unresolved for many embodied AI deployments, particularly since physical injury can occur. Contracts must clearly delineate the divisions of responsibility between vendors and buyers, covering incident response timelines, auditing rights, and liability for damages. Exploring how vendors intend to address accountability can reveal a lot about their commitment to effective security strategies.
The Path Forward
The pressures of rapid technological advancement have made the assessment of embodied AI a pressing issue. When these systems enter an organization, security teams must confront the implications of their deployment in real-world settings. Today’s robot demo merely hints at what lies beneath the surface — the complex security architecture that every team must evaluate meticulously.
It's imperative that security teams approach potential vendors with a comprehensive list of demands concerning provenance, access, integrity, evidence, and accountability. Only then can the risks associated with these advanced embodied systems be adequately managed and mitigated.
Published as part of the Foundry Expert Contributor Network.
Want to join?
