LATIDIA · Ciberseguridad

Exploits de Data-Void en LLM de búsqueda web

arXiv: 2610.30365v1Tipo de anuncio: nuevo Resumen: Los modelos de lenguaje grandes (LLM) de búsqueda en la web han cambiado la forma en que los usuarios buscan información en línea: en lugar de examinar las listas clasificadas de enlaces, los usuarios leen respuestas sintetizadas.

La noticia

arXiv:2610.30365v1 Announce Type: new Abstract: Web-searching Large Language Models (LLMs) have changed how users seek online information: instead of sifting through ranked lists of links, users read synthesized answers. This shift creates a new LLM vulnerability: a data-void exploit. Disinformers publish their narratives in search spaces where relevant and reliable content is scarce, i.e. data voids, then rely on the LLM's web-search to retrieve and then use, cite, or list those pages in its responses to data-void seeking prompts. Unlike classical search, where users see ranking cues and competing results, LLMs can obscure when an answer relies on sparse, unverified, or adversarial sources. We study this threat by varying the