Generative AI Misuse: A Taxonomy of Tactics and Insights from Real-World Data
This work addresses the risk of GenAI misuse for society by providing concrete insights from real-world data, though it is incremental as it builds on prior research.
The paper tackles the problem of understanding how generative AI models are exploited in practice by presenting a taxonomy of misuse tactics based on analysis of about 200 real-world incidents from 2023-2024, revealing patterns in motivations and strategies across modalities.
Generative, multimodal artificial intelligence (GenAI) offers transformative potential across industries, but its misuse poses significant risks. Prior research has shed light on the potential of advanced AI systems to be exploited for malicious purposes. However, we still lack a concrete understanding of how GenAI models are specifically exploited or abused in practice, including the tactics employed to inflict harm. In this paper, we present a taxonomy of GenAI misuse tactics, informed by existing academic literature and a qualitative analysis of approximately 200 observed incidents of misuse reported between January 2023 and March 2024. Through this analysis, we illuminate key and novel patterns in misuse during this time period, including potential motivations, strategies, and how attackers leverage and abuse system capabilities across modalities (e.g. image, text, audio, video) in the wild.