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New attack extracts data from multimodal AI systems

Researchers have developed a new method called \"immrag\" to extract data from multimodal retrieval-augmented generation (MRAG) systems. This technique operates in a black-box setting and embeds malicious instructions within an input image, rather than a textual prompt, to probe the system. Experiments demonstrated that immrag can reconstruct a significant number of images from various scenarios, highlighting the need for enhanced safeguards in multimodal AI. AI

IMPACT Highlights potential vulnerabilities in multimodal AI systems, necessitating the development of new security measures.

RANK_REASON Academic paper detailing a new method for data extraction from multimodal AI systems. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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New attack extracts data from multimodal AI systems

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Academic paper detailing a new method for data extraction from multimodal AI systems. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Maria Carmen Jica, Ali Satvaty, Suzan Verberne, Fatih Turkmen ·

    Walking the Embedding Space: Datastore Extraction from Multimodal RAG

    arXiv:2610.01871v1 Announce Type: cross Abstract: Multimodal Retrieval-Augmented Generation (MRAG) has emerged as a reliable and cost-effective technique of grounding the generative capabilities of Multimodal Large Language Models (MLLMs) into relevant, up-to-date, external knowl…