The demand for Large Language Models (LLMs) is skyrocketing across sectors like healthcare, finance, and customer service, critical for text analysis, chatbots, and decision-making. The global LLM market is projected to expand from $1.59 billion in 2023 to $259.8 billion by 2030, demonstrating a robust CAGR of 79.80%. However, LLMs face significant security risks, including data poisoning and prompt injection attacks. Organizations must prioritize LLM security through strategies focused on data governance, model integrity, infrastructure resilience, and ethical practices. Key practices include using clean datasets, implementing strong access controls, and conducting regular audits. The OWASP Top Ten highlights crucial risks like insecure output handling and model theft, underscoring the need for continuous monitoring and robust incident response plans. By adopting comprehensive security measures, businesses can protect their LLM investments and maintain user trust. For enhanced LLM security, consider tools like Qualys for real-time visibility and protection.
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