MIT AI Risk Repository · Risk Sub-Category · 64.04.02

Adversarial input

Category: Misuse tactics to compromise GenAI systems (Model integrity)

Description

"Adversarial Inputs involve modifying individual input data to cause a model to malfunction. These modifications, which are often imperceptible to humans, exploit how the model makes decisions to produce errors (Wallace et al., 2019) and can be applied to text, but also to images, audio, or video (e.g. changing pixels in an image of a panda in a way that causes a model to label it as a gibbon).6"

From Generative AI Misuse: A Taxonomy of Tactics and Insights from Real-World Data (Marchal2024), as extracted by the MIT AI Risk Repository (CC BY 4.0).

Classification

Causal entity
Human

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 Marchal2024