Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI agents are finally moving past cute demos and into actual production workflows. With AWS AgentCore, teams can build agents that write tickets, call APIs, deploy infrastructure, invoke external tools, and make changes faster than any human operator ever could. That’s powerful, but it also introduces a brand-new operational and security surface. And here’s the uncomfortable truth: most organizations have no idea what their agents are actually doing. Agentic AI isn’t magic.

This blog kicks off our new series, Inside the Agent Stack, where we take you behind the scenes of today’s most widely adopted AI agent platforms and show you what it really takes to secure them. Each installment will dissect a specific platform, expose realistic attack paths, and share proven strategies that help organizations keep their AI agents safe, reliable, and compliant.

The internet’s fragility was evident again during the recent Cloudflare outage. A single internal fault rippled outward and disrupted major websites and business applications. X, ChatGPT, media platforms, dashboards and thousands of other services simultaneously showed 5xx errors. And this is not new.

A major publicly traded CPG company wanted to adopt LLM to improve performance marketing, analytics, and customer experience. However, the IT team blocked AI usage and uploads to external AI tools as interacting with public AI models could expose sensitive brand, consumer, and financial data. This isn’t an isolated problem. It’s a pattern across enterprises: business agility collides with security requirements.

Gmail has always been a common target for cybercriminals, and with the arrival of advanced AI tools, the threat level has increased significantly. Now, attackers no longer rely on generic phishing emails or scam methods. They are using AI to create convincing messages and imitate real support agents to make attacks look more genuine. This change in attack patterns has made Gmail users more vulnerable because they can’t differentiate between real and fake messages.

It seems as though we’ve been talking about the zero trust model for years. Although it isn’t a new concept, only now has it really managed to transition from theory to practice. This cybersecurity framework ‒ based on implicit distrust ‒ used to seem somewhat abstract, more like a strategic idea than an actual strategy. Today, however, we’re witnessing a paradigm shift that’s making it possible to implement zero trust effectively.

Ransomware attacks target your backups before anything else. Recent data shows that two-thirds of organizations faced ransomware in the past two years, with attackers specifically hunting backup infrastructure to eliminate recovery options. Once your backups are gone, you’re left with two choices: Pay up or lose your data permanently.

From secure service mesh rollouts to AI cluster hardening, see how KubeCon + CloudNativeCon NA 2025 redefined identity, trust, and governance in Kubernetes environments.

Let’s catch up on the more interesting vulnerability disclosures and cyber security news gathered from articles across the web this week. This is what we have been reading about on our coffee break! Heard of this thing called rate limiting on API? Perhaps not.

We are reducing the number of supported major versions of Teleport from three to two. We are extending the support for each major version to 24 months. New major versions will come out once per year in August. The most recent major version of Teleport, referred to as the Current Version, is the only major version of Teleport that will receive new features. The previous major version, referred to as the Stable Version, will only receive bug fixes and security patches.