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Generative AI Misuse: A Taxonomy of Tactics and Insights from Real-World Data

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arxiv 2406.13843 v2 pith:3NJL3D5X submitted 2024-06-19 cs.AI

classification cs.AI
keywords misusegenaipotentialtacticsacrossanalysisexploitedgenerative
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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Cited by 5 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 14 citations worldwide. Full citation record

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  4. Understanding U.S. Users' Security and Privacy Transparency Needs for Consumer-Facing Generative AI

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