In the context of massive data, intelligent auditing faces challenges in data mining efficiency and accuracy. To address this issue, this article proposes a design scheme for an intelligent audit data mining toolbox based on massive data. This plan helps auditors quickly and accurately identify abnormal data and potential risks by analyzing and mining audit data. This article first proposes the problem of intelligent audit data mining, then analyzes the shortcomings of existing technologies and methods. Finally, by designing and implementing this toolbox, an effective solution is provided. Through data simulation, we can know that this toolbox has the characteristics of efficiency, accuracy, and ease of use, providing new ideas and tools for data mining in the field of intelligent auditing, helping to improve audit efficiency and accuracy, and reduce audit risks.