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New MIRAGE framework enables stealthy visual prompt injection attacks on web agents

By PulseAugur Editorial · [1 sources] ·

Researchers have developed MIRAGE, a novel framework for visual indirect prompt injection attacks against multimodal large language model (MLLM) web agents. This method uses diffusion models to create adversarial images that are perceptually benign and confined to attacker-controlled regions, such as ad slots or widgets. MIRAGE combines curvature-aware adversarial diffusion guidance with sparse perturbations to effectively hijack the agent's next action, demonstrating significant potency and realism against frameworks like SeeAct and OpenClaw. AI

IMPACT This research highlights new vulnerabilities in multimodal LLM web agents, potentially impacting the security of automated browsing and interaction systems.

RANK_REASON The cluster contains a research paper detailing a new method for attacking AI agents. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New MIRAGE framework enables stealthy visual prompt injection attacks on web agents

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The cluster contains a research paper detailing a new method for attacking AI agents. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Xuelong Dai, Jianyu Ma, Boyang Ma, Biwei Yan, Yijun Yang, Yue Zhang ·

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

    arXiv:2606.20717v2 Announce Type: replace-cross 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 vulnerab…

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