2023

Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection

Greshake, Kai, Abdelnabi, Sahar, Mishra, Shailesh et al.

Understand

Large Language Models (LLMs) are increasingly being integrated into various applications.

  • The functionalities of recent LLMs can be flexibly modulated via natural language prompts.
  • This renders them susceptible to targeted adversarial prompting, e.g., Prompt Injection (PI) attacks enable attackers to override original instructions and employed controls.
  • So far, it was assumed that the user is directly prompting the LLM.

Reading the bibliography…