Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI agents need to authenticate with numerous systems, making AI authentication a crucial security boundary that determines blast radius, revocability, and long-term governance risk.

Sophos analysts are investigating the active abuse of QEMU, an “open-source machine emulator and virtualizer,” by threat actors seeking to hide malicious activity within virtualized environments. Attackers are drawn to QEMU and more common hypervisor-based virtualization tools like Hyper-V, VirtualBox, and VMware because malicious activity within a virtual machine (VM) is essentially invisible to endpoint security controls and leaves little forensic evidence on the host itself.

For years, conversations about AI security risks were framed as forward-looking. Organizations were told to prepare for a future where autonomous agents would act on their behalf, access sensitive systems, and make consequential decisions without human intervention at every step. That future, it turns out, is now.

For many engineering and security teams, NIST SP 800-218 (Secure Software Development Framework, or SSDF) compliance feels like a hurdle that is too difficult to overcome. To meet these and other emerging regulations and be effective in today’s DevSecOps environment, organizations are moving toward codifying these standards into machine-readable rules, also known as Policy as Code (PaC).

Proofpoint DLP and Trellix DLP are two notable data loss prevention solutions. In this blog, we’ll analyze both platforms in depth and see how they compare. We’ll also introduce Teramind as a compelling alternative that combines the best aspects of Proofpoint and Trellix, while offering additional tools that could increase your workforce’s safety and productivity.

SAST, or Static Application Security Testing, is a method of analyzing source code to find vulnerabilities before the application is deployed. It's a type of white box testing that scans the code without executing it, looking for weaknesses that could be exploited. SAST helps developers identify and fix security issues early in the Software Development Life Cycle (SDLC), potentially reducing costs and improving the overall security posture of the application.

What began as reports about Anthropic’s Mythos model has now moved into a gated research preview called Mythos Preview. For cybersecurity, that immediately raises an important question: what happens when advanced AI can accelerate offensive workflows such as vulnerability analysis, exploit development, and attack planning? In a recent Cato blog post, we addressed the broader strategic shift this represents.

In a world where technology, threats, and business priorities evolve constantly, the real challenge is not predicting the future, but choosing an architecture that can adapt to it.