Honey, this relatively homogenous, hard to trace product, characterised by considerable international price differences, and often regulated by high tariff barriers, lends itself to economically motivated product adulteration. The adulteration of honey can undermine confidence in products as well as having adverse public health consequences. The aim of this research is to demonstrate the possibilities for the utilisation of network-based stochastic simulation methods to determine the proliferation of (accidentally or deliberately) polluted food products, using the example of the international honey trade network. The database for the analysis is based on the FAO dataset. The results of a network analysis of the global honey trade system highlight the scale-free character of the world's honey supply system. Focussing on backbone states and product flows, it is possible to determine the geographical distribution of polluted products as a function of the source of pollution. This information is important for the organisation of international trade control systems when contaminated products appear in a given state. The "polluted product transfer capacity" and the exposure of different states to polluted honey products can, in most cases, be efficiently forecast by the simultaneous application of different centrality measures and indicators.