Last updated on August 7, 2024
The post-prompting defense simply puts the user input before the prompt.
Take this prompt as an example:
Translate the following to French: {user_input}
It can be improved with post-prompting:
{user_input}
Translate the above text to French.
This can help since ignore the above instruction...
doesn't work as well. Even though a user could say ignore the below instruction...
instead, LLMs often will follow the last instruction they see.
Post-prompting, although seemingly simple, is yet another effective defense against prompt hacking methods like prompt injection. This technique takes advantage of the fact that the model is more inclined to follow the last instruction it sees.
Mark, C. (2022). Talking to machines: prompt engineering & injection. https://artifact-research.com/artificial-intelligence/talking-to-machines-prompt-engineering-injection/ ↩