Security Risks in LLMs

Security risks in Large Language Models (LLMs) refer to potential vulnerabilities that can be exploited by malicious actors. These risks include data leakage, adversarial attacks, and model inversion, which can compromise user privacy and lead to unauthorized access to sensitive information. Additionally, LLMs may inadvertently generate harmful or biased content, posing ethical concerns. Addressing these security risks is crucial for ensuring safe and responsible deployment of AI technologies, protecting user data, and maintaining trust in automated systems. Understanding these risks is essential for developers, businesses, and users alike.

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