MIT AI Risk Repository · Risk Sub-Category · 30.07.01

Prompt Attacks

Category: Robustness

Description

carefully controlled adversarial perturbation can flip a GPT model’s answer when used to classify text inputs. Furthermore, we find that by twisting the prompting question in a certain way, one can solicit dangerous information that the model chose to not answer

From Trustworthy LLMs: A Survey and Guideline for Evaluating Large Language Models’ Alignment (Liu2024), as extracted by the MIT AI Risk Repository (CC BY 4.0).

Classification

Causal entity
Human
Timing
Other

Subdomain definition: Vulnerabilities in AI systems, software development toolchains, and hardware that can be exploited, resulting in unauthorized access, data and privacy breaches, or system manipulation causing unsafe outputs or behavior.

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Other entries from Liu2024