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Vulnerable open-source component reuse can lead to security problems. At present, open-source component detection for binary programs can only reveal whether open-source components with vulnerabilities are reused, which cannot determine the specific location of vulnerabilities. To address this problem, we propose BMVul, an open-source vulnerability function detection based on the software modularization method, which is oriented to binary programs. BMVul performs binary modularization by the overlapping clustering method DBM based on directed graph, then uses feature comparison technology to carry out modular software component analysis. After creating open-source component vulnerability function set through function signature, BMVul detects vulnerability function in the binary modules reusing open-source components. The experimental results show that compared with the component detection based on Louvain modularization and B2SFinder, BMVul improves the precision by 3.16% and 59.57%, respectively. Moreover, the precision of unique binary module matching is improved by 39.43% compared with the Louvain method. The F1 score is improved by 8.45% compared to B2SFinder. Module-level detection narrows the search space of vulnerability functions, thereby reducing the workload of open-source vulnerability detection, which is of great significance for software security analysis. [ABSTRACT FROM AUTHOR]