Abstract:

Network protocol grey box fuzzing AFLNET technology based on overlay guidance has attracted more attention in the field of network security testing, and there are many excellent research results. After the analysis of AFLNET and its derivatives, it is found that AFLNET has shortcomings in three aspects: message sequence attribution, message sequence evaluation and the selection of message sequence variation points, and a network protocol grey box fuzzy method based on message sequence attribution optimization is proposed. This method defines the concept of preference degree to measure the fuzzy benefit that message sequence can bring to each state, and proposes a new message sequence assignment algorithm combined with preference degree to re-assign interesting message sequences. Then, an evaluation function is constructed using the feedback information of multiple dimensions, which is used to more accurately calculate the true potential of each message sequence. In addition, a new mutation point analysis algorithm is proposed to help the fuzzer filter out the already mutated positions and mutate other more interesting mutated positions instead. The experimental results show that compared with the mainstream method, the QFuzzer implemented based on the proposed method increases the number of path coverage by 6.94%~11.04%, and the number of vulnerabilities found increases by 7.24%~30.70%.

Key words: network protocol, security, grey box, fuzz testing, message sequence, attribution, optimization, vulnerability mining