Enterprise AI Security: 12 Best Practices for Deploying LLMs in Production

The guide provides 12 actionable security practices for deploying Large Language Models (LLMs) in production, addressing a range of threats not covered by traditional security frameworks, such as prompt injection, data exfiltration, and agent goal hijacking. These practices are mapped to the OWASP LLM Top 10 (2025) and Agentic Top 10 (2026) to offer a comprehensive threat model for secure AI infrastructure. Each practice includes implementation guidance, threat context, and code examples, emphasizing the importance of input validation, output filtering, access control, and runtime monitoring. The guide highlights the necessity for enterprise AI security to go beyond basic measures by maintaining a multi-layered defense strategy that incorporates human oversight for critical actions, comprehensive logging, rate limiting, and supply chain security to mitigate risks associated with model vulnerabilities and embedding weaknesses.