Blog Posts

AI is reshaping the modern SOC, accelerating detection, triage and response, but it hasn’t changed the core truth that the hardest problems in cybersecurity are still human problems. Automation can process the noise, enrich signals and execute playbooks at machine speed, yet breaches continue to stem from judgement, context and behaviour that no model can fully interpret. This piece explains why AI-powered operations must keep human decision-making firmly in charge, and how to design an AI-accelerated SOC where technology amplifies analysts instead of replacing them.

Artificial intelligence has shifted from a supporting tool to a defining force in cybersecurity. Recent incidents, from indirect prompt injection attacks to state-sponsored groups using LLMs for reconnaissance and phishing, reveal how AI is accelerating both offence and defence. Organizations deploying AI-driven detection and response are cutting breach lifecycles dramatically, yet new vulnerabilities, governance challenges, and machine-speed attacks demand equally rapid adaptation. As experts like Ken DSouza note, the security landscape is now defined by acceleration: attackers are faster, defenders are faster, and the organizations that evolve will determine whether AI becomes an advantage or a liability.

AI hasn’t solved cybersecurity, but it’s delivering real gains where it’s used with purpose. From faster detection and response to sharper vulnerability prioritisation, automation is quietly transforming SOC workflows. This piece breaks down what’s actually working today, what’s still hype, and how security leaders can measure true ROI.

AI is transforming cyber risk management, not by replacing humans, but by amplifying their impact. This post explains how AI improves pattern recognition, prioritization, and analyst efficiency within trusted frameworks like NIST AI RMF and ISO/IEC 23894 without ceding control to automation.

In today’s fast-moving threat landscape, having a complete inventory of assets isn’t enough, you need context as it relates to your business. Cloud instances spin up and vanish in minutes, SaaS sprawl hides critical exposures, and vulnerabilities go from “known” to “exploited” overnight. This article explores how Continuous Threat Exposure Management (CTEM) and AI-driven tools like Autnhive SAMI’s Strategic Priority Index (SPI) are transforming security from static asset tracking to dynamic, business-aware exposure management. By linking every asset to the business service it supports, and prioritizing based on financial, operational, and compliance impact, security teams can finally answer the question that matters most: What’s the real cost of not fixing this now?

Compliance doesn’t equal security. ISO certificates and NIST checklists may look impressive on paper, but real protection comes from proving your controls actually work continuously. This article explores why checkbox compliance creates a false sense of safety and how continuous validation, automation, and real-world testing turn frameworks like NIST, ISO, and NIS2 into living, defensible systems.