Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Cursor and Claude Code now read source code, install packages, and push commits with much of the access a senior engineer has, and often with less oversight. Give an agent a prompt to fix a bug, and it may pull a private API key from a config file, pass a customer record into its context window, or send a snippet of proprietary logic to a third-party model provider to reason about the fix. Security teams built policy for developers typing code by hand.

Every SaaS tool your organization onboards now carries a hidden layer of AI risk. The chatbot on your CRM, the transcription service your sales team runs, the code assistant embedded in your IDE. Each one processes company data through models you did not build, in ways your vendor questionnaire was not written to catch. Traditional third-party risk management was designed to evaluate infrastructure, access controls, and data handling.

Author: Alexander Ivanyuk, Senior Director, Technology For many MSPs, AI still looks like an extra tool outside the real workflow: open a chatbot, paste in a ticket, ask for help, copy the answer back and continue working. It may save a few minutes, but it also creates more steps and more places where context can be lost.

Monitoring AI agents in production is a fundamentally different problem from monitoring traditional software or even generative AI models. Because agents run autonomously, chain multi-step reasoning across tools and systems, and change behavior as their underlying models evolve, standard software metrics like uptime and CPU utilization miss almost everything that matters. ‍

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.

A leaked n8n API key is only the start. GitGuardian's research traces the full chain, from exposed tokens and weak keys to CVE-2026-25053 and the N8N_ENCRYPTION_KEY that protects every stored credential, then lays out a hardened configuration to break it.

For the last several months, we have run AI agents against real production applications across industries. Two questions drove the work: what does AI-powered vulnerability analysis and pentesting surface at scale, and what does protection have to look like to keep pace. The vulnerability discovery side confirmed what Mythos made impossible to ignore.