Monero’s approach to privacy relies heavily on ensuring that all transactions are indistinguishable, since any patterns visible to an outside observer can be leveraged for blockchain analysis and transaction linking. Mapping the blockchain history to human-interpretable visualizations is a powerful tool for privacy coin research, since potential heuristics that would be challenging to identify from log files are intuitive to spot as visual patterns or clusters corresponding to information leaks. Consensus-level prevention of identifying features (e.g. custom ring sizes - fixed in v8) is paramount, due to the inherent threat of retroactive deanonymization, statistically-noisy change output traces, and combinable heuristics. I’ll introduce the basics of transaction tree analysis and key tools from the exploratory data analysis toolkit (histograms, heatmaps, and more). Together, we’ll leverage these visualizations to intuit ongoing information leaks and mitigation strategies for the next upgrade. Mitchell Krawiec-Thayer (a.k.a. “Isthmus”) is the Decentralized Consensus Lead at Insight Data Science, a Monero Research Lab contributor, the editor of Mastering Monero, the founder of Noncesense Research Lab, and a hobbyist chess player & bread baker.