Summary The growing adoption of large language models (LLMs) in enterprise workflows has introduced a new class of adversarial techniques: indirect prompt injection. Indirect prompt injection can be used against systems that leverage large language models (LLMs) to process untrusted data. Fundamentally, the risk is that an attacker could provide specially crafted data that the LLM misinterprets as instructions.
