Submission for VAST MC2 2026 - TUM

Authors

Advitya Chopra (Technical University of Munich), Jacob Miller (Technical University of Munich), Oscar Edgardo Navarro Banderas (Technical University of Munich)

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.