Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

In our last post, we introduced the Model Context Protocol (MCP), the "brain" or "mission briefing" that guides an AI agent's actions. Most security teams are just getting familiar with prompt injection, the equivalent of tricking an AI with a single, misleading command. But that's like stopping a pickpocket at the door when a master spy is already inside, rewriting the mission plans. As AI agents become autonomous, the attacks become more profound.

In this series, we examined the vital connection between AI and APIs, highlighting what makes a leader in the API security market through the 2025 KuppingerCole Leadership Compass. Now, we turn to the core strategy of true API security: the full-lifecycle approach, where security is a continuous, integrated process rather than a single action.

In our previous post, we highlighted a key insight from the 2025 KuppingerCole Leadership Compass: securing AI depends on securing APIs first. The report emphasizes that as AI use grows, the attack surface for APIs becomes more complex and risky. With many solutions available, navigating vendor claims can be challenging, making independent expert analysis extremely valuable.

Over the last year, I’ve spent countless hours with CISOs, CTOs, and security architects talking about a new wave of technology that’s changing the game faster than anything we’ve seen before: Agentic AI and Model Context Protocol (MCP) servers. If you think AI is still in the “cool demos and pilot projects” stage, think again. We’re already seeing autonomous agents reasoning, remembering, and taking actions in live production environments.

The release of a new KuppingerCole Leadership Compass is always a significant event for the cybersecurity industry, offering a vendor-neutral view of the market's current state. The 2025 edition, focusing on API Security and Management, is critical as it arrives at a pivotal moment for technology. It clearly presents a fact many organizations are just beginning to understand: the crucial connection between the rise of Artificial Intelligence and the necessity for robust API security.

Imagine an autonomous AI agent tasked with a simple job: generating a weekly sales report. It does this reliably every Monday. But one week, it doesn't just create the report. It also queries the customer database, exports every single record, and sends the file to an unknown external server. Your firewalls saw nothing wrong. Your API gateway logged a series of seemingly valid calls. So, what happened? The agent wasn't hacked. Its mind was changed.

APIs are essential in today's digital landscape, supporting everything from mobile apps to vital backend systems. As their importance grows, they also become attractive targets for advanced attackers who bypass traditional security methods. These adversaries do not simply exploit API flaws; instead, they mimic normal user behavior to launch subtle, slow-and-low attacks that are difficult for conventional tools to detect.

Your API attack surface is larger and more exposed than you realize. In today's complex, cloud-native environment, APIs are deployed at an astonishing rate. While this rapid pace fuels innovation, it also creates a significant visibility gap. The APIs you are aware of and manage are only the tip of the iceberg. Your actual risk exists beneath the surface, in the undocumented, unmanaged, and forgotten APIs that traditional security tools completely overlook.

I’ve spent my career building solutions to protect the API fabric that powers modern businesses. I founded Salt because I saw that traditional security tools such as WAFs, gateways, and CDNs weren’t designed to see or secure APIs. That gap led to breaches, blind spots, and billions in risk. Today, we’re facing a new wave of risk that’s even bigger than the last. The rise of Agentic AI has brought us to a true inflection point. Agentic AI isn’t just another software layer.