Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Today, we’re excited to announce a few developer experience improvements to Cloudflare AI Search to make it easy to manage a search solution out of the box. Previously, you had to stitch together components of the Cloudflare primitives (Workers AI, AI Gateway, Vectorize, R2, Browser Run) but now, AI Search can do this automatically, and better. Our goal is to give your agents their own search engine, where they can easily find data to provide better answers for themselves and their humans.

Ask most security tools what an AI coding agent just built, and they can tell you. Ask what it was allowed to consume before it started, and far fewer have an answer. That gap, between watching agentic development and controlling it, is what securing it actually comes down to. Securing agentic development means stopping risk before it enters a build, not flagging it after. And risk prevention has a prerequisite most approaches skip: you can only account for the assets you actually hold and manage.

Agentic AI governance is about keeping powerful, autonomous AI systems aligned, safe, and accountable as they act on our behalf. It’s now a certainty that AI agents will be deployed enterprise-wide. So, we need to look more deeply into those agents, figure out where they are, how to find them, and fully understand what they are doing in deployment so we can prevent attacks. The most dangerous agentic attacks will not look like attacks at the layer where they originate.

It's 6:30am and you hear the door of the nightclub you've spent the last 8 hours inside shriek as it closes behind you. You watch bleary-eyed as an overly bright sunrise illuminates the business-suited people as they glide effortlessly along the sidewalk, their obnoxiously well-rested faces talking about work on their fully charged phones. You wonder, "Where did all the fun people go? And what happened to my wallet?".

We studied what happens when Large Language Models (LLMs) generate vulnerability patches for recently disclosed, complex vulnerabilities. Our data shows that LLMs produce Fix-Like Artifacts with Embedded Defects (FLAWED) 53.9% of the time when complex patches are required.

AI has changed the calculus of a credential attack. Before, finding and exploiting credentials in an enterprise environment required time, patience, and human judgment. An attacker had to decide which accounts were worth testing and which systems were worth reaching. Many credentials never made the list.

This year National Social Engineering Day falls on Aug. 6. This day is designed to give us an opportunity to remind people that cybercriminals do not always need sophisticated malware, an undisclosed vulnerability or a dark room filled with glowing monitors, sometimes, all they need is a good story. Social engineering existed long before computers. Confidence tricks, impersonation, false authority and appeals to greed or fear have been used for centuries.

Construction firms have invested heavily in technology to connect project information. Drawings, specifications, RFIs, submittals, BIM models, photos, and field reports are increasingly accessible from anywhere, helping office and field teams work from the same information. Connecting project information is a critical first step. It improves collaboration, reduces rework, and helps office and field teams work from the same information.