
handle: 10316/101176
Security vulnerabilities are present in most software systems, especially in projects with a large codebase, with several versions over the years, developed by many developers. Issues with memory management, in particular buffer overflow, are among the most frequently exploited vulnerabilities in software systems developed in C/C++. Nevertheless, most buffer overflow vulnerabilities are not detectable by vulnerability detection tools and static analysis tools (SATs). To improve vulnerability detection, we need to better understand the characteristics of such vulnerabilities and their root causes. In this study, we analyze 159 vulnerable code units from three representative projects (i.e., Linux Kernel, Mozilla, and Xen). First, the vulnerable code is characterized using the Orthogonal Defect Classification (ODC), showing that most buffer overflow vulnerabilities are related to missing or incorrect checking (e.g., missing if construct around statement or incorrect logical expression used as branch condition). Then, we run two widely used C/C++ Static Analysis Tools (SATs) (i.e., CppCheck and Flawfinder) on the vulnerable and neutral (after the vulnerability fix) versions of each code unit, showing the low effectiveness of this type of tool in detecting buffer overflow vulnerabilities. Finally, we characterize the vulnerable and neutral versions of each code unit using software metrics, demonstrating that, although such metrics are frequently used as indicators of software quality, there is no clear correlation between them and the existence of buffer overflow in the code. As a result, we highlight a set of observations that should be considered to improve the detection of buffer overflow vulnerabilities.
orthogonal defect classification (ODC), Software security, vulnerability detection, buffer over flow, software metrics, static code analysis
orthogonal defect classification (ODC), Software security, vulnerability detection, buffer over flow, software metrics, static code analysis
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 8 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
