Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The rules of cyber defense have shifted. Threat actors are increasingly using advanced automation to accelerate reconnaissance, evade static signatures, and orchestrate rapid intrusions across critical infrastructure, software supply chains, and insider pathways. This has created a critical velocity gap: when adversaries compress attack timelines from days to minutes and defenders rely on manual triage across fragmented legacy tools, the defense falls behind.

The future of policing depends on more than changing force structures or investing in AI. It depends on making data work across boundaries. Policing is being asked to change at pace.

As autonomous AI reshapes cyber risk, financial institutions need the visibility and context to detect unusual behavior and respond at machine speed. AI agents are changing more than just how financial services companies operate. They are also changing the speed and scale of cyber risk.

On August 20, 2026, the Cybersecurity and Infrastructure Security Agency (CISA) published its Logging Reference Architecture (LRA), the implementation guidance federal civilian executive branch (FCEB) agencies have been waiting for since the Office of Management and Budget's Memorandum M-26-14 reset the requirements for enterprise logging.

Elastic sits at the very top of this year’s AV-Comparatives' CyberRisk Quadrant within the 2026 Endpoint Prevention and Response (EPR) test with the only protection scores at 100%, combined with both the lowest modelled operational footprint of any tested product and zero false alerts.

How teams are leaving value on the table and what it costs when they do It's 3:00 a.m. Your on-call engineer gets paged that the central processing unit (CPU) is at 97% on payment-processor-01. They open their observability platform, look at the metric spike, reboot the host, and close the ticket.

Social engineering has always been the softest edge of enterprise defense, and AI is sharpening adversaries’ attacks. Phishing, business email compromise, and impersonation still dominate the initial-access playbook, but AI has stripped out the cost, time, and skill barriers that once forced attackers to choose between reach and precision.

Frontier AI has handed attackers something they have never had before: the ability to move at machine speed. Attacks that once took days to craft now take minutes. Threats have not just evolved to be automated, adaptive, and operational around the clock. They have also changed category. We surveyed more than 850 IT and cybersecurity professionals across Australia and New Zealand to understand how organisations are keeping up. What the data reveals is not a capability problem. It is a pace problem.

Adversaries are using AI to launch cyber attacks in record time, forcing security teams to measure responses in minutes instead of months. Phishing campaigns built with large language models (LLMs) achieve click-through rates 4.5 times higher than traditional methods,1 and the average time between initial compromise and lateral movement has fallen to just 29 minutes.2 This is a 65% increase from the prior year.2 State and local governments and higher education institutions are at an inflection point.

The gap between attacker speed and defender readiness is widening. Attackers can now move from initial access to full domain control in less than a minute using AI.1 Large language model-generated phishing campaigns are achieving click-through rates 4.5 times higher than traditional methods.2 Most enterprise SOCs weren't built for this tempo and fidelity.