Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Wallarm Research has just released a powerful new Nuclei template targeting a new kind of exposure: the Model Context Protocol (MCP). This isn’t about legacy devtools or generic JSON-RPC pinging. It’s about the protocol fueling next-gen LLM applications — and it’s already showing up exposed in the wild.

In today’s dynamic digital landscape, applications are the backbone of modern businesses. They drive operations, facilitate customer interactions, and manage critical data. However, the intricate web of rules and processes that govern these applications – the business logic – often presents a significant, yet frequently overlooked, attack surface.

On March 25, 2025, NIST released the initial public draft of NIST SP 800-228, "Guidelines for API Protection for Cloud-Native Systems." The document provides a comprehensive framework for securing APIs in cloud-enabled environments. However, for organizations looking to align with these objectives, the tooling requirements may seem initially overwhelming. Fortunately, Wallarm helps streamline the process by integrating many of these recommendations into a single, cloud-native solution.

Securing PCI and PII data is at the core of what we do at Protegrity. You can try out Protegrity’s capabilities today, through our API Playground. This section walks you through some sample scenarios of de-identifying PCI data, so that it is removed from your environment and only reversed once it leaves it. To run this example, you have to be signed up to the Protegrity API Playground.

Agentic AI is transforming business. Organizations are increasingly integrating AI agents into core business systems and processes, using them as intermediaries between users and these internal systems. As a result, these organizations are improving efficiency, automating routine tasks, and driving innovation. But these benefits come at a cost. AI agents rely on APIs to access data and functionality from underlying systems. Without APIs, AI agents are useless.