What is LLM Security?
LLM security entails safeguarding large language models (LLMs) and their infrastructure against unauthorized access, data breaches, and adversarial manipulation throughout the AI lifecycle. This security practice enhances traditional cybersecurity with AI-specific defenses, targeting vulnerabilities unique to generative AI systems. Essential components include securing model endpoints, prompts, and data layers, as well as managing cloud security and user permissions.
Key threats include prompt injection, training data poisoning, model theft, and insecure output generation, which can lead to data leaks and compliance violations. Enterprises must adopt comprehensive strategies addressing these risks.
Best practices for LLM security encompass input validation, content moderation, data integrity monitoring, and implementing robust access controls. Tools like Wiz AI Security Posture Management (AI-SPM) enhance visibility and risk assessment. By applying frameworks like the OWASP Top 10 for LLMs, organizations can effectively secure their LLM deployments, facilitate compliance, and protect sensitive data.
