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Realistic Environmental Injection Attacks on GUI Agents

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Abstract

GUI agents built on LVLMs are increasingly used to interact with websites. However, their exposure to open-world content makes them vulnerable to Environmental Injection Attacks (EIAs) that hijack agent behavior via webpage elements. Many recent studies assume the attacker to be a regular user who can only upload a single trigger image, which is more realistic than earlier assumptions of website-level administrative control. However, these works still fall short of realism: (1) the trigger's position and surrounding context remain largely fixed between training and testing, failing to capture the dynamic nature of real webpages and (2) the trigger often occupies an unrealistically large area, whereas real-world images are typically small. To better reflect real-world scenarios, we introduce a more realistic threat model where the attacker is a regular user and the trigger image is small and embedded within a dynamically changing environment. As a result, existing attacks prove largely ineffective under this threat model.

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