Detecting Integer Overflow Vulnerabilities in Binary Executables Based on Target Filtering and Dynamic Taint Tracing

The number of identified integer overflow vulnerabilities has been increasing rapidly in recent years. In this paper, a smart software vulnerability detection technology is presented, which is used for the identification of integer overflow vulnerabilities in binary executables. The proposed algorithm is combined with Target filtering and dynamic taint tracing (TFDTT). Dynamic taint tracing is used to reduce the mutation space and target filtering function is used to filter test cases during the process of test case generation. Theory analysis indicates that the efficiency of TFDTT is higher than NonTF-DTT and random Fuzzing technology. And the experiment results indicate that the detection technology based upon TFDTT can identify the possible integer vulnerabilities in binary program, meanwhile, it is more efficiency than other two technologies.