Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Agents let you build software faster than ever, but securing your environment and the code you write — from both mistakes and malice — takes real effort. Open Web Application Security Project (OWASP) details a number of risks present in agentic AI systems, including the risk of credential leaks, user impersonation, and elevation of privilege.

We have thousands of internal apps at Cloudflare. Some are things we’ve built ourselves, others are self-hosted instances of software built by others. They range from business-critical apps nearly every person uses, to side projects and prototypes. All of these apps are protected by Cloudflare Access. But when we started using and building agents — particularly for uses beyond writing code — we hit a wall. People could access apps behind Access, but their agents couldn’t.

In automotive and manufacturing, digital transformation is no longer a future ambition—it’s operational reality. Connected vehicles, smart factories, and increasingly complex supply chains have introduced a new dependency: trusted device identity and secure key management at scale. And yet, many organisations are still: This gap is no longer just a technical issue—it’s a business risk.

The revolution is here, but it’s not what we expected. AI coding assistants have transformed software development, with developers shipping code faster than ever before. GitHub Copilot, Amazon CodeWhisperer, and Claude Code have become as essential to modern development as Git itself. The productivity gains are undeniable; what once took hours now takes minutes. But there’s a dangerous blind spot in this revolution: security.

Anthropic just released Claude Mythos Preview. They did not make it publicly available. That decision alone should tell you everything you need to know about what this model can do. During internal testing, Mythos autonomously discovered and exploited zero-day vulnerabilities across every major operating system and web browser. It found a 27-year-old bug in OpenBSD. A 16-year-old vulnerability in a widely used media codec.

In the fifth installment of SafeBreach’s AI-First series, VP of Development Yossi Attas explores how the development team’s AI-First philosophy is being extended to the customer frontier and improved upon through the Anti-Hallucination Protocol.

By Roger A. Grimes and Matthew Duren AI agents can deliver incredible productivity gains, but their operational complexity makes effective threat modeling harder than ever, including for developers, administrators and especially end users. At the same time, both developers and non-developers are increasingly vibe-coding, or using AI to generate functional software from natural language prompts.

Today, we’re introducing Justification Coach, a new AI-powered capability that helps users write better access request justifications in real time, so admins get the context they need for audits and investigations without having to chase people down after the fact.

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.