The OWASP Top 10 for LLM applications: What developers shipping AI features need to know

In 2023, significant incidents involving large language models (LLMs) underscored their unique security vulnerabilities, prompting the creation of the OWASP Top 10 for LLM Applications, a guide specifically addressing these risks. Key events included Samsung engineers inadvertently feeding proprietary source code to ChatGPT, leading to its integration into the training data, and a tampered open-source model on Hugging Face that spread misinformation across applications. These cases highlighted the broader attack surface and faster exploitation paths associated with LLMs, which traditional application security measures did not anticipate due to their reliance on deterministic code and validated inputs. The OWASP list, updated in 2024, identifies specific vulnerabilities such as prompt injection, sensitive information disclosure, and supply chain threats, emphasizing the need for robust security practices. The unpredictability of LLMs, due to their probabilistic behavior and interaction with untrusted inputs, necessitates treating them as untrusted components, implementing strict controls, and ensuring comprehensive logging and authorization measures to mitigate risks.