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Through analyzing the evaluation criteria of virtual enterprise knowledge sharing risk early-warning which was one of the important supply chain organizations, a hierarchical structure evaluation attribute system was proposed in this paper. And then, by utilizing the basic theory and method of rough sets and fuzzy sets, a supply chain knowledge sharing risk early-warning model was established, in order to reduce redundancy indexes, the heuristic attribute reduction algorithm based on discernable matrix was put forward. On this basis, supply chain knowledge sharing risk was assessed with the use of fuzzy sets, and its detailed calculation steps were designed. Finally, an example was used to verify the effectiveness and the practical value of the model, the grade of knowledge sharing risk early-warning is gained, and the evaluation result is consistent with the actual result.