Lee Rossey argues that most enterprise security teams would fail a real cyber crisis because they prepare for audits rather than operational readiness. Drawing on military cyber doctrine, he contrasts the military’s continuous, high-fidelity training and mission rehearsals with the corporate world’s reliance on annual tabletop exercises that rarely reflect modern attack conditions. As AI accelerates the sophistication and speed of cyber threats, organizations must shift from a prevention-first mindset to one focused on detection, containment, recovery, and continuous validation. Rossey advocates for realistic cyber simulations that test people, processes, tools, and AI agents together under adversarial conditions before deployment. He introduces the concept of AI Proving Grounds—environments where organizations can safely train and validate both human operators and autonomous AI systems. His central message is that cyber resilience is not achieved through policies or assumptions but must be continuously proven through realistic practice that exposes weaknesses before attackers do.

We knew this day would come. June 2026 Patch Tuesday broke the record, and July blew the record out of the water. July is the first time in Patch Tuesday’s history that over 500 CVEs were patched in a single month, with a staggering 569 CVEs patched, breaking last...

As AI transitions from personal assistant to business identities, traditional cybersecurity controls are too insufficient to manage risk. Organisations must adapt their security strategies to account for a new category of privileged identity: the AI agent. 

The traditional cybersecurity landscape—dominated by legacy firms with massive, proprietary datasets of past attacks—is undergoing a disruptive shift. According to recent Gartner research, the future of defense belongs to agile companies leveraging Hyper-Synthetic Data (HSD). HSD is entirely synthetic data generated by LLMs and machine-learning models to simulate highly specific, realistic cyber environments and advanced adversary behaviors. As threat actors deploy sophisticated AI automation, such as token exhaustion attacks, organizations must move from proactive response to preemptive mitigation. Because testing unproven autonomous agents in live production systems poses severe risks, HSD acts as a safe, cost-effective “proving ground” for national security, finance, and healthcare sectors. While legacy vendors struggle to model complex IT infrastructures, HSD enables continuous validation and high-fidelity testing against novel, never-before-seen threats. Gartner predicts HSD usage in vital sectors will skyrocket from 15% to 80% by 2030.The traditional cybersecurity landscape—dominated by legacy firms with massive, proprietary datasets of past attacks—is undergoing a disruptive shift. According to recent Gartner research, the future of defense belongs to agile companies leveraging Hyper-Synthetic Data (HSD). HSD is entirely synthetic data generated by LLMs and machine-learning models to simulate highly specific, realistic cyber environments and advanced adversary behaviors. As threat actors deploy sophisticated AI automation, such as token exhaustion attacks, organizations must move from proactive response to preemptive mitigation. Because testing unproven autonomous agents in live production systems poses severe risks, HSD acts as a safe, cost-effective “proving ground” for national security, finance, and healthcare sectors. While legacy vendors struggle to model complex IT infrastructures, HSD enables continuous validation and high-fidelity testing against novel, never-before-seen threats. Gartner predicts HSD usage in vital sectors will skyrocket from 15% to 80% by 2030.