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LLM security involves practices and measures to protect LLMs from misuse, attacks, or vulnerabilities that can compromise their integrity.

LLM security tools protect large language models from threats, mitigating risks like data breaches, unauthorized access, and AI misuse.

The OWASP Top 10 for Large Language Models (LLMs) is a set of security risks specifically identified for LLM applications.

Training data poisoning occurs when malicious actors intentionally alter or corrupt the data used to train machine learning models LLMs.