BugAnaBench: benchmark for software vulnerability analysis and its construction method

Software vulnerabilities are an important resource for cyberspace security. The rapid development of automated bug finding methods represented by fuzzing enables vulnerabilities to be found quickly, but the precise analysis of vulnerabilities mainly relies on manual labor. To improve the efficiency of vulnerability analysis, many automated vulnerability analysis tools have emerged in recent years, and how to evaluate these analysis engines has become a new challenge. This paper designs and implements a set of anomaly sample datasets for vulnerability analysis and introduces the construction method of the datasets. The data set has the characteristics of complete variety, strong applicability, and high degree of expansion, and is expected to support the ability verification of vulnerability analysis tools.