Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

We recently released The Rise of Agentic AI, our API ThreatStats report for Q1 2025, finding that evolving API threats are fueled by the rise of agentic AI systems, growing complexity in cloud-native infrastructure, and a surge in software supply chain risks, and uncovered patterns and actionable insights to help organizations prioritize risks and harden their defenses. Keep reading to find out more.

API security is no longer just a concern; it’s a critical priority for businesses. With APIs serving as the backbone of modern applications, they’ve become a primary target for attackers. While automated security testing tools help detect vulnerabilities, their limitations leave organizations exposed to evolving threats. Here’s where Threat Replay Testing (TRT) comes into play.

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.

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.

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.