VAST Challenge

EmbargoLens: Tracing Disclosure Pathways in Multi-Agent Communications through Temporal, Behavioral, and Message-Level Visual Analysis

Ruqi Sun (Southern University of Science and Technology), Jiaping Li (Southern University of Science and Technology), Qianxi Xu (Southern University of Science and Technology), Yuxin Ma (Southern University of Science and Technology)

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Top of the first page of the paper “EmbargoLens: Tracing Disclosure Pathways in Multi-Agent Communications through Temporal, Behavioral, and Message-Level Visual Analysis”.

Abstract

Investigating a failure in a multi-agent communication system requires analysts to follow sensitive information from internal discussion to public release. We present EmbargoLens, a visual analytics system built for VAST Challenge 2026 Mini-Challenge 1. Six coordinated views support this investigation. A timeline and agent swimlanes connect activity peaks to individual messages. Network and channel comparisons show how communication changed before the release. A leak-progression view tracks the spread of sensitive information, while an evidence workspace lets analysts arrange original messages into a supported release path. Using these views, we connect an early exposure in Round 8 and a warning in Round 19 to an authorization decision and two pre-deadline releases in Round 21.