Cyber attacks have changed, and quietly, so have the attackers behind them. What used to be manual, time-consuming work is now increasingly handled by artificial intelligence. Modern attacks don’t rely on luck or effort alone. They analyse, adapt, and persist, often without any human involvement once they’re launched. For businesses,

Cybersecurity is entering a new phase of sorts, but it may not be quite what you might expect that to mean.  The industry is not dealing with a reinvention of risk, which remain mostly the same, but more an acceleration of familiar problems.  Ransomware, phishing, third-party exposure, and litigation are

As AI is more prevalently used in high-security environments, cybersecurity can no longer rely on static defenses like application logins or network boundaries. Instead, the focus must shift toward securing the data itself.  Current frameworks remain rooted in legacy thinking, where security models still rely on traditional perimeter security, even

Most security teams have more data than they know what to do with. Alerts, dashboards, telemetry feeds—all of it pointing at things that need attention. The problem isn’t that they can’t see the risks. It’s that seeing them and actually fixing them are two completely different things. Known vulnerabilities sit

The cybersecurity industry has spent the better part of two years trying to figure out how to secure AI agents. Most of that energy has pointed upstream: model governance, configuration hardening, intent-based policy layers, guardrails. Those things aren’t wrong. But they’re not enough, and focusing too heavily on them means