This guide explains the major risks associated with large language models based on OWASP’s Top 10 for LLMs. The grid layout highlights threats such as prompt injection, model denial of service, sensitive data exposure, insecure output handling, supply chain risks, and excessive agent autonomy. It also covers risks like training data poisoning, insecure plugin design, overreliance on AI outputs, and model theft. Each section includes mitigation strategies such as least privilege, input/output validation, rate limiting, and data verification. The key takeaway is that LLM security requires treating AI systems like untrusted inputs and applying traditional security controls alongside new AI-specific protections.

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