The article emphasizes the importance of securing AI agents and their underlying infrastructure. It outlines various vulnerabilities that can arise from trusting these AI systems implicitly. For instance, over 17,000 MCP servers are highlighted as potential points of attack, where unverified tool execution can lead to significant security breaches. Specific threats include chat history exfiltration, where attackers can bypass data loss prevention tools, and tool poisoning, where malicious actors manipulate outputs to trick AI into executing harmful actions. Several examples illustrate the risks involved. The article mentions prompt injection attacks that can lead to unauthorized data leaks, including sensitive emails and repository data. It also points out logic flaws that allow cross-organizational data visibility and excessive permissions granted to agents, which can result in damaging actions based on misleading triggers. These vulnerabilities can escalate through methods like OAuth command injection, insecure plugins, and lateral movement, where compromised agents access private infrastructures. To address these issues, the article presents a comprehensive security platform designed to map AI agents and their connections while ensuring compliance and governance. Features include a verified registry of servers and skills, real-time policy enforcement, and integration with existing tools. The approach combines security, platform capabilities, and governance into one system, allowing teams to implement AI securely without starting from scratch.