Cybersecurity Expert

The recent decision by the U.S. administration to lift restrictions on Anthropic’s frontier AI models has generated plenty of debate. Some have questioned whether the original restrictions were justified, while others argue they reflected legitimate concerns about the cybersecurity capabilities of increasingly powerful AI systems. Regardless of where you stand, I believe the real story lies elsewhere. This is one of the clearest examples yet of governments treating AI models as technologies with potential national security implications rather than simply another software product. That should make every cybersecurity leader take notice. AI Security Is Different For decades, cybersecurity has focused on protecting systems from attack. Today, we are entering an era where AI itself can influence the speed, scale and sophistication of those attacks. Modern frontier models can assist with code analysis, vulnerability discovery, malware understanding and offensive research. While t...

When Anthropic abruptly pulled Mythos 5 and Fable 5 from circulation , the move sent a jolt through the AI and cybersecurity communities. These were not minor point releases. They were widely regarded as among the most capable models the company had ever shipped, and watching them withdrawn, even temporarily, raised an uncomfortable question: if the frontier itself can be paused over a safety concern, what exactly are we securing, and how would we know if it failed? At the time of writing, much of the detail remains disputed. Anthropic and government officials appear to hold very different views about how serious the issues really were, and until more technical evidence is made public, nobody outside the organisations directly involved can say with confidence what happened. What we can do is step back and ask why an episode like this matters at all, because the answer says a great deal about where AI security is heading. A bigger jump than the version number suggests Part of what made ...

Written by Sean Tilley, Senior Sales Director EMEA at  11:11 Systems   Artificial intelligence is no longer a future ambition for UK organisations. It is already shaping how decisions are made, how services are delivered, and how quickly businesses can respond to change. From automation and analytics to customer engagement and operational optimisation, AI is becoming an integral part of the modern enterprise. AI Governance and Cyber Resilience: A Boardroom Imperative  As adoption accelerates, however, a quieter risk is emerging, and it is one that boards and executive teams cannot afford to treat solely as a technical issue. AI is not simply another tool for innovation. It is altering the cyber risk landscape and unsettling long held assumptions about security, governance, and resilience.   Recent   research by 11:11 Systems   highlights the scale of that concern. In a global survey of more than 800 senior IT leaders, nearly three quarters (7...

This is Part 2 of a 2-part series.  Read Part 1:  Your AI Agent Doesn’t Care About Your Controls If AI agents change how execution happens, they also expose a fundamental limitation in how most security controls operate. Many control models assume there is sufficient time to detect, assess, and respond to events before they result in material impact. That assumption no longer holds. Traditional detection models follow a sequence in which an event occurs, is logged, analysed, and then acted upon. This approach works at human speed, where actions are spaced out and intervention is possible. In automated environments, particularly those involving AI agents, that sequence is compressed to the point where response often occurs after the outcome has already been realised. The Speed Problem AI agents operate at a pace that removes the window for meaningful intervention. They do not pause between actions or wait for approval cycles. Once triggered, they execute tasks rapidly across sy...

This is Part 1 of a 2-part series on AI agents and control assurance.   Read Part 2: Controlling AI Agents: Why Detection Is Too Late The cybersecurity industry has spent years investing in visibility. Dashboards have improved, detection tooling has matured, and the volume of telemetry available to security teams has increased significantly. Most organisations can now see more of their environment than at any point in the past. However, one of the most important emerging risks is not hidden malware or an unknown vulnerability. It is the rapid introduction of AI agents operating across environments that organisations do not fully understand, cannot clearly inventory, and often cannot meaningfully govern. This is not simply another software category. It represents the introduction of autonomous digital actors interacting with identity systems, APIs, SaaS platforms, cloud environments, and business processes. These agents are not constrained by the same assumptions that underpin tr...

The cybersecurity industry has spent years focusing on visibility. Dashboards expanded. Detection tooling improved. Telemetry volumes exploded. Yet one of the biggest emerging risks in 2026 is not hidden malware or an unknown zero-day. It is the rapid deployment of AI agents that organisations barely understand, cannot fully inventory, and often cannot meaningfully govern. AI agents are moving beyond chat interfaces and simple copilots. They are increasingly capable of reasoning, planning, accessing systems, invoking tools, retrieving information, and taking autonomous actions with limited human involvement. That changes the security conversation entirely. This is not simply another software category. It is the emergence of autonomous digital workers operating across identity systems, APIs, SaaS platforms, cloud environments, and business processes. And most organisations are deploying them faster than they can secure them. Research and industry reporting throughout 2026 s...