AI systems are fully capable of carrying out nightmare attacks against infrastructure and nobody's ready

Autonomous AI systems are fully capable of carrying out a nightmare cyberattack scenario – finding and attacking critical operational technology and industrial equipment, and shutting down access to water, power, and other daily life necessities.

If this happens, defenders may only have minutes to detect and block it, according to a Booz Allen Hamilton report.

The consulting firm’s operational technology (OT) lab tested eight scenarios to examine advanced models’ capabilities within an autonomous, AI-enabled OT attack chain.

The models achieved the objectives across all eight scenarios, turning digital access into physical actions – in one case finding and moving a robotic arm in just minutes.

In another test, the models progressed from a perimeter compromise to actions inside an industrial control network in just over 16 minutes.

“Our testing showed that AI agents can operate with a speed, persistence, and engineering-level precision that may outpace organizations that have not implemented foundational OT cybersecurity practices,” Kyle Miller, VP of infrastructure cybersecurity at Booz Allen, told The Register.

“While there's not a defined timeline for a nightmare scenario per se, we've observed and continue to see the growing use of AI in real-world attacks.

As the capabilities of available models grow, the risk becomes far greater,” he added.

In addition to reporting on its findings, the consulting firm wants to see more industry testing, development, and increased deployment of cyber defenses across OT and other critical infrastructure networks.

OT test lab Booz Allen declined to identify the models it tested, describing them as two of the “latest frontier models from the leading AI providers.” The tests were designed to “better understand the potential impacts of the most advanced models on real-world OT systems,” Miller told us.

“We configured our test system to mimic close to, if not, exact systems we commonly see across a variety of industries.” To this end, the testers constructed a multi-vendor environment, modeled after a general manufacturing facility, and used a layered network architecture divided into separate enterprise, industrial DMZ, plant operations, and production zones.

Firewalls and switches defined the intended pathways between them.

The lab included programmable logic controllers (PLCs), human-machine interfaces (HMIs), engineering and operator workstations, a supervisory control and data acquisition (SCADA) platform, plant services, network infrastructure, a variable-frequency drive (VFD), a robotic arm, sensors, and other physical equipment.

“Mixed vendors, firmware, control logic, and imperfect segmentation reproduced the complexity and technical debt common in long-lived OT environments,” according to the report.