MIRAGE: Stealthy Visual Prompt Injection for Vulnerability Detection in Web Agents

• URL: http://arxiv.org/abs/2606.20717v1
• Date: Tue, 16 Jun 2026 15:31:33 GMT
• Title: MIRAGE: Stealthy Visual Prompt Injection for Vulnerability Detection in Web Agents
• Abstract summary: Multimodal Large Language Model (MLLM)-based web agents provide practical, high-precision solutions for visual browser automation.<n>They inherently expand the attack surface, introducing novel vision-based vulnerabilities.<n>We propose MIRAGE, a novel visual indirect prompt injection framework for targeted next-action hijacking.
• Score: 21.863110073132773
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Multimodal Large Language Model (MLLM)-based web agents provide practical, high-precision solutions for visual browser automation; however, they inherently expand the attack surface, introducing novel vision-based vulnerabilities. Existing adversarial evaluations targeting these agents frequently rely on permissive threat models and visually conspicuous artifacts. In this paper, we investigate a constrained vulnerability detection setting: a trusted web platform where the evaluator acts solely as an unprivileged third party, such as a merchant or advertiser, controlling only a semantically legitimate, spatially constrained region, such as an ad slot, a sponsored card, or a localized widget. Operating under these realistic constraints, we propose MIRAGE, a novel visual indirect prompt injection framework for targeted next-action hijacking. Our approach leverages diffusion models to generate perceptually benign adversarial images strictly confined to the attacker-controlled boundaries permitted by the trusted service provider. To maximize attack efficacy within such a restrictive setting, we introduce a robust optimization technique combining curvature-aware adversarial diffusion guidance with sparse, dark-pixel residual perturbations. Comprehensive evaluations against prominent MLLM web agent frameworks, specifically SeeAct and OpenClaw, empirically demonstrate the potency, realism, and stealth of our proposed MIRAGE.

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