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The paper examines the risks of prompt-to-SQL (P2 SQL) injection attacks in LLM-integrated web applications, highlighting their vulnerability due to unsanitized user input leading to SQL injections. It evaluates seven state-of-the-art LLMs and identifies P2 SQL vulnerabilities in five real-world applications, proposing four effective defense techniques to mitigate these risks. The study emphasizes the need for robust defenses in LLM-integrated frameworks like LangChain and LlamaIndex to safeguard against th

Author

somprajapati24

Language

EN