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This research paper investigates privacy leakage in tabular diffusion models, quantifying how training setups, synthesis choices, and attacker knowledge impact privacy risks. It reveals that adversaries can succeed without perfect knowledge or massive resources and highlights pitfalls in heuristic privacy metrics.