When Prompts Become Payloads: A Framework for Mitigating SQL Injection Attacks in Large Language Model-Driven Applications
Natural language interfaces to structured databases are becoming increasingly common, largely due to advances in large language models (LLMs) that enable users to query data using conversational input rather than formal query languages such as SQL. While this paradigm significantly improves usability and accessibility, it introduces new security risks, particularly the amplification of SQL injection vulnerabilities through the prompt-to-SQL translation process. Malicious users can exploit these mechanisms by crafting adversarial prompts that manipulate model behavior and generate unsafe queries. In this work, we propose a multi-layered security framework designed to detect and mitigate LL...
| Authors | Farzad Nourmohammadzadeh Motlagh, Mehrdad Hajizadeh, Mehryar Majd et al. |
|---|---|
| Primary category | cs.CR |
| Published | 11 May 2026 |
| Last updated at source | 11 May 2026 |
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