Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

There is a version of AI SOC that most security teams are familiar with. It summarizes alerts. It surfaces recommendations. It tells an analyst what to look at next. It is useful in the way a well-organized report is useful: it saves time reading, but the work still happens at a human pace. That version of AI is not what this blog is about. For MSSPs and SecOps teams operating at scale, advisory AI is not a destination. In fact, it presents a bottleneck in a different form.

Picture a SOC that investigates its own alerts, hunts threats across customer tenants, isolates compromised endpoints, and writes its own detection rules. Envision the same SOC attacking itself every morning to find the gaps it missed, all before your analysts arrive for the day. This is not a roadmap item, but an operational reality on LimaCharlie. It’s what agentic AI security looks like on a platform built to support it.

The agentic AI security standards your enterprise will adopt in the next 18 months are being written right now, inside working groups most CISOs have never heard of. The Coalition for Secure AI (CoSAI), an OASIS Open Project with more than 45 sponsor organizations, including Google, Microsoft, NVIDIA, IBM, and Meta, is producing the frameworks, reference architectures, and secure design patterns that will define how autonomous agents operate inside enterprise environments.

A few weeks ago the world was exposed to Mythos, Anthropic's new frontier model and the Project Glasswing announcement that came with it. The reaction across the industry was immediate. Cybersecurity stocks fell sharply. The Treasury Secretary convened an emergency meeting with major bank CEOs. 250 CISOs produced a response playbook over a single weekend. That is not a typical announcement or a PR "leak". That is a reckoning. Then, about a week later, I came across MOAK.

Security compliance audits can feel intimidating, especially if your team has never been through one before. For many organizations, an audit feels like a high-pressure project with a hard deadline, a long list of evidence requests, and a lot of manual work spread across security, IT, legal, and compliance teams. For vendors and companies in highly regulated industries, audits and risk assessments may already be a routine part of doing business.

A new research report from Reach Security reveals that misconfigured security controls, configuration drift, and unused capabilities across an organization’s existing security technology stack are a primary driver of cybersecurity risk.

Most organizations treat AI security as a finishing touch: A policy written after an incident or a product category evaluated after the core stack is already in place. That sequencing is the problem. AI has fundamentally changed how sensitive data moves inside an organization, through prompts, agents, summarization tools, and third-party models that operate entirely outside traditional security perimeters.

In the rapidly evolving landscape of cloud-native infrastructure, collaboration is the engine of innovation. Today, we are thrilled to share a major milestone in our journey: Trilio has officially achieved Premier Partner status within the Red Hat partner ecosystem. This elevation isn’t just a badge of honor; it is a testament to years of deep technical integration and a shared vision for the future of the open hybrid cloud.

Your fraud detection agent scores 30,000 transactions per hour. Your KYC agent processes identity verifications against government watchlists. Your customer service chatbot resolves disputes and initiates balance transfers. Each agent runs on Kubernetes with inherited service account permissions that span payment APIs, customer databases, and compliance systems. Now imagine one of those agents is compromised through a prompt injection embedded in a customer support ticket.

Razorthorn has worked with wide range of technically savvy clients who are confident they would spot a fake, but confidence is exactly what makes deepfake fraud so effective. In 2024, a finance manager at engineering firm Arup transferred $25 million to fraudsters after taking part in a video call with what appeared to be his CFO and several colleagues. Every person on that call was fabricated. None of it was real.