Formalizing and Benchmarking Prompt Injection Attacks and Defenses

The recent study on prompt injection attacks addresses a critical gap in the understanding of how these attacks manipulate LLM-integrated applications. By proposing a formal framework, the researchers not only categorize existing attacks but also introduce a novel attack method. Their systematic evaluation of five prompt injection attacks and ten defenses across ten LLMs and seven tasks marks a significant advancement in the field. This work culminates in the establishment of a common benchmark, which is essential for future research and development of effective defenses. The public availability of their platform, Open-Prompt-Injection, further facilitates ongoing research, allowing the community to build upon their findings and enhance the security of LLM-integrated applications against prompt injection attacks.