The recent supply chain attack involving Mercor and the LiteLLM vulnerability serves as a massive wake-up call for enterprise security teams. While the security industry has spent the last year fixating on prompt injections and model jailbreaks, this breach highlights a far more systemic vulnerability.The weakest link in enterprise AI ... Read More

TL;DR: Key TakeawaysThe Agentic Shift: APIs have evolved into the "Agentic Action Layer," serving as the operational backbone for autonomous AI agents.A Massive Visibility Crisis: Nearly half of organizations (48.9%) are entirely blind to machine-to-machine traffic and cannot monitor their AI agents.The Boardroom Mandate: While 78.6% of security leaders report ... Read More

Executive SummaryThe Agentic Stack consists of three layers: The Brain (LLM), The Hands (MCP Servers), and The Action Layer (APIs).AI Agents differ from chatbots because they don't just talk; they autonomously execute multi-step workflows through these layers.Security Risk propagates across the stack, meaning a "healthy brain" can still execute malicious ... Read More

When cybersecurity teams talk about risk, they usually speak in technical terms like vulnerabilities, exploits, and attack vectors. But when they walk into the boardroom, they need to speak a different language. They need to speak about cost. In the era of AI, the cost of insecure APIs has shifted ... Read More

For the past two years, the adoption of Generative AI has felt like a gold rush. Organizations raced to integrate Large Language Models and build autonomous agents to assist employees. They often bypassed standard governance processes in the name of speed and innovation. That era of unrestricted experimentation is rapidly ... Read More

The "Engineering" TrapIn many organizations, there is a dangerous unspoken rule: The SOC handles endpoints and networks; Engineering handles APIs.This silo creates a massive blind spot. We recently spoke with the Senior Manager of Security Engineering at a major insurance provider, who described this exact pain point. Before bringing in ... Read More

HighlightsThe Perimeter is Porous: Modern Agentic AI and the Model Context Protocol (MCP) have effectively turned internal data centers inside out, making the "internal API" security model obsolete.The "Confused Deputy" Risk: Legitimate AI agents act as trusted internal entities but can be exploited to bypass Data Loss Prevention (DLP) policies, ... Read More

We are witnessing the end of the "Human-in-the-Loop" era and the beginning of the "Agent-to-Agent" economy. Until recently, most AI interactions were hub-and-spoke models where a human user prompted a central model, reviewed the output, and then took action. That model provided a natural safety brake. If the AI hallucinated ... Read More

The "Good Enough" TrapIf you ask most organizations how they protect their APIs, they point to their WAF (Web Application Firewall). They have the OWASP Top 10 rules enabled. The dashboard is green. They feel safe.But attackers know exactly how your WAF works, and, more importantly, how to trick it.We ... Read More

In cybersecurity, we live by our metrics. We measure Mean Time to Respond (MTTR), Dwell Time, and Patch Cadence. These numbers indicate to the Board how quickly we respond when issues arise.But in the era of Agentic AI, reaction speed is no longer enough. When an AI Agent or an ... Read More