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Smart fuzzing method for detecting stack-based buffer overflow in binary codes

机译：用于检测二进制代码中基于堆栈的缓冲区溢出的智能模糊方法

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摘要

During the past decades several methods have been proposed to detect the stack-based buffer overflow vulnerability, though it is still a serious threat to the computer systems. Among the suggested methods, various fuzzers have been proposed to detect this vulnerability. However, many of them are not smart enough to have high code-coverage and detect vulnerabilities in feasible execution paths of the program. The authors present a new smart fuzzing method for detecting stack-based buffer overflows in binary codes. In the proposed method, concolic (concrete + symbolic) execution is used to calculate the path and vulnerability constraints for each execution path in the program. The vulnerability constraints determine which parts of input data and to what length should be extended to cause buffer overflow in an execution path. Based on the calculated constraints, the authors generate test data that detect buffer overflows in feasible execution paths of the program. The authors have implemented the proposed method as a plug-in for Valgrind and tested it on three groups of benchmark programs. The results demonstrate that the calculated vulnerability constraints are accurate and the fuzzer is able to detect the vulnerabilities in these programs. The authors have also compared the implemented fuzzer with three other fuzzers and demonstrated how calculating the path and vulnerability constraints in the method helps to fuzz a program more efficiently.
机译：在过去的几十年中，已经提出了几种方法来检测基于堆栈的缓冲区溢出漏洞，尽管它仍然是对计算机系统的严重威胁。在建议的方法中，已提出了各种模糊器来检测此漏洞。但是，它们中的许多都不足够聪明，无法具有较高的代码覆盖率并无法检测程序可行执行路径中的漏洞。作者提出了一种新的智能模糊方法，用于检测二进制代码中基于堆栈的缓冲区溢出。在所提出的方法中，使用concolic（具体+符号）执行来计算程序中每个执行路径的路径和漏洞约束。漏洞约束条件确定输入数据的哪些部分以及应扩展到什么长度，以导致执行路径中的缓冲区溢出。基于计算出的约束，作者生成测试数据，以检测程序可行执行路径中的缓冲区溢出。作者已将所建议的方法作为Valgrind的插件实施，并在三组基准程序上对其进行了测试。结果表明，计算出的漏洞约束是准确的，并且模糊器能够检测这些程序中的漏洞。作者还比较了已实现的模糊器和其他三个模糊器，并演示了如何计算方法中的路径和漏洞约束如何帮助更有效地模糊程序。

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