Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The AI revolution is moving at breakneck speed. Every week, new tools, frameworks, and integrations hit the market. Developers eager to harness the power of large language models and automation platforms are spinning up assets with little thought to long-term security. The result is a wave of exposed services — chatbots, APIs, orchestration tools, and workflow systems — that anyone on the internet can stumble upon. Attackers see this as an open invitation.

APIs are the foundation of modern applications, and attackers know it well. A single misconfigured endpoint or exposed token can give adversaries a direct path into sensitive systems and data across your environment. Your already overburdened security teams can’t afford to miss what may be their fastest-growing attack surface. How fast-growing is the threat?

North Korean threat actor Kimsuky has escalated its social engineering tactics by leveraging military ID deepfakes to deceive South Korean targets. According to a recent analysis by South Korean cybersecurity firm Genians, the group is now using AI-generated images to impersonate military personnel, making phishing campaigns more convincing and harder to detect.

CrowdStrike is unveiling groundbreaking innovations across Counter Adversary Operations. Threat AI, a system of AI-powered agents built on the CrowdStrike Falcon platform, is the industry’s first agentic threat intelligence system. It provides mission-ready agents to reason, hunt, and take action against any stage of adversary activity. In addition, the new Threat Intelligence Browser Extension for Google Chrome extends intelligence everywhere analysts work.

AI is transforming how organizations operate, from automating workflows to fueling innovation and competitive advantage. It’s the backbone of the modern enterprise. But while the opportunities AI presents are enormous, they come with new risks: models can be stolen, cloud workloads can be hijacked, and data can be poisoned. Every layer of the AI stack — from GPUs and training data to inference pipelines and SaaS apps — is a new target.

The healthcare industry, despite being highly regulated, is one of the most targeted for breaches, necessitating tight measures. While these measures are necessary, they often restrict the free flow of information, critical for analysing patient outcomes and improving internal operations. Tokenization has long been a reliable method for masking protected health information (PHI). But not all tokenization is created equal.

Financial cybersecurity has never been a static discipline. Over two decades in this industry, I’ve seen it transform from a compliance checkbox to a cornerstone of business resilience—usually after a painful lesson. Today, we’re heading into the most significant paradigm shift for financial security since online banking: the convergence of artificial intelligence and machine identity governance.