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Abstract
This paper presents an entry to the VAST Challenge 2026 (MC2). We present a visual analytics system that traces an anomalous on- line post through a multi-agent communication network. We show the system can be used to identify an adversarial prompt injection worm. Our system includes a swimlane-based interface with se- mantic zooming, a collapsible provenance graph, a macro density heatmap, a pattern classification tree, and LDA topic modelling.