Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Enterprise AI adoption is accelerating rapidly, with organizations deploying large language models and AI agents to access sensitive corporate data and automate critical business processes.

It’s no secret that the software development life cycle is becoming more complex. With a plethora of libraries, frameworks, and now AI coding agents and assistants, we can build far more ambitious software in a fraction of the time. This is fantastic! But with it come greater opportunities for accidental or malicious security bugs and vulnerabilities to sneak in undetected, with potentially devastating consequences for your users and their trust in your company.

Modern infrastructure is increasingly run by automated systems, not people. Bots push code. Runners deploy to prod. Agents orchestrate cloud resources. And increasingly, AI models trigger actions directly through prompt-driven automation. Welcome to the era of non-human identities (NHIs): the invisible workforce operating behind modern digital systems.

Back in 2024, Amazon Web Services (AWS) engaged Trail of Bits (ToB) to perform a comparative assessment between several authorization and access management policy languages. If you're unfamiliar with the concept of a policy engine, it's essentially a fully-featured engine that offloads authorization decisions in an application.

Insights from Chris Dugan, Manager, Enterprise Account Development at Teleport If you're just starting out in sales, chances are you've come across the title “SDR” (Sales Development Representative) more times than you can count. But here at Teleport, we’ve rebranded our entire SDR function to something that better reflects the real work being done: Enterprise Account Development.

When I speak to customers across EMEA, one thing is clear: regulations like the EU's Digital Operational Resilience Act (DORA) are becoming very real, very fast. Financial institutions and their service providers are being asked to do more than ever before to demonstrate secure operations, especially when it comes to managing access to infrastructure. That's exactly why we hosted a recent webinar in partnership with Falx. The goal?

Modern infrastructure is already complex, characterized by distributed environments, multi-cloud deployments, and dynamic change. Now add Large Language Models (LLMs) to the mix, and the challenge grows exponentially. Engineering leaders are under pressure to deliver innovation fast, while also safeguarding against breaches, misconfigurations, and human error. That’s why initiatives like eliminating static credentials, enforcing just-in-time access, and reducing SSH key sprawl are gaining traction.

Just-in-time (JIT) access isn’t easy. This Reddit thread of cybersecurity pros surfaces many of the most common JIT headaches — and you may be encountering those same challenges yourself. As noted in the thread, no users should be “swimming in access”, especially as standing privileges and over-permissioned accounts continue to be a major source of breaches. The truth is, many JIT models struggle to keep up with today’s fast-moving, cloud-native environments.

The standout themes at KubeCon + CloudNativeCon Europe 2025 in London strongly centered on how identity is rapidly becoming the linchpin for securing cloud-native infrastructure. The recurring theme I saw wasn’t just Kubernetes innovation—it was the rising urgency of securing the who behind every action across platforms, clusters, services, and tools.