Currently, to satisfy the high number of system requirements, complex software is created which turns its development costintensive and more susceptible to security vulnerabilities. In software security testing, empirical studies typically use artificial faulty programs because of the challenges involved in the extraction or reproduction of real security vulnerabilities. Thus, researchers tend to use hand-seeded faults or mutations to overcome these issues which might not be suitable for software testing techniques since the two approaches can create samples that inadvertently differ from the real vulnerabilities and thus might lead to misleading assessments of the capabilities of the tools. Although there are databases targeting security vulnerabilities test cases, one database contains only real vulnerabilities, the other ones are a mix of real and artificial or even only artificial samples. Secbench is a database of real security vulnerabilities mined from Github which hosts millions of open-source projects carrying a considerable number of security vulnerabilities. We mined 248 projects accounting to almost 2M commits for 16 different vulnerability patterns, yielding a Database with 682 real security vulnerabilities.
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