AI Agent Security Audit: How to Assess Your LLM Application Risks
AI agents now operate with extensive system access—reading files, executing commands, and accessing production systems through MCP tools. Enterprises increasingly encounter risky AI agent behaviors including improper data exposure and unauthorized system access, yet few have formal AI governance frameworks. Without proper security audits, organizations cannot see what agents access or control their actions. An MCP Gateway provides the essential visibility and control that transforms shadow AI into sanctioned AI—complete with authentication, permissions, and audit trails.
This article outlines a comprehensive approach to assessing security risks in LLM applications, covering agent security audit frameworks, monitoring strategies, access controls, compliance requirements, and ongoing governance to prevent costly breaches and ensure regulatory adherence.