LLM Security Guide for CIOs: Strategy, Governance, and Securing Agentic AI

In the heat of the AI race, many enterprises deploy LLM applications without robust security hardening, turning a massive productivity gain into a potential liability. Your role as CIO is to establish a clear security playbook that ensures your AI initiatives are not only innovative but also secure and resilient. This guide provides the strategic framework needed to transform LLM security from a theoretical concern into a proactive, integrated part of your cybersecurity program.

Report Snapshot

The New Threat Landscape: Understand the unique risks of LLMs, including those defined by the OWASP Top 10 (like Prompt Injection, Data/Model Poisoning, and sensitive data leakage).
Operationalizing AI Security: Implement a foundational, five-step framework to reduce risk, including getting ahead of Shadow AI and building deeper security expertise across your teams.
Securing Agentic AI: Examine the next class of threats introduced by autonomous LLM agents—where vulnerabilities can be exploited in tools, memory, permissions, and planning logic.

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