Researchers have identified a critical blind spot in current information-seeking agents, which rely heavily on search-engine-indexed knowledge, leaving unindexed information unexplored. This limitation, known as Unindexed Information Seeking (UIS), poses a significant challenge as vital information often remains uncaptured by search engine crawlers. To address this issue, a novel research agent system, UIS-Digger, has been proposed to facilitate comprehensive research in real-world UIS scenarios. The system aims to bridge the gap between indexed and unindexed information, enabling more effective information seeking. By exploring UIS, researchers can develop more robust and inclusive information-seeking agents, capable of uncovering hidden or hard-to-reach information1. This development has significant implications for fields where unindexed information is prevalent, such as cybersecurity and intelligence gathering, where the ability to access and analyze unindexed data can be a decisive factor in staying ahead of emerging threats.