Prompt Stealing Attacks Against Large Language Models
Date: 2024-02
Affected: GPT-3.5, GPT-4, prompt-based LLM products
Attack vector: prompt-injection
Category: research
Severity: Medium

Sha and Zhang propose a two-module prompt-stealing attack (parameter extractor + prompt reconstructor) that recovers direct, role-based, and in-context prompts from black-box LLM outputs.


Mitigations:

Architectural layers (MAESTRO):