NEZHA is an efficient and domain-independent differential fuzzer developed at Columbia University. NEZHA exploits the behavioral asymmetries between multiple test programs to focus on inputs that are more likely to trigger logic bugs.
NEZHA features several runtime diversity-promoting metrics used to generate inputs for multi-app differential testing. These metrics are described in detail in the 2017 IEEE Symposium on Security and Privacy (Oakland) paper - NEZHA: Efficient Domain-Independent Differential Testing.
The current code is a WIP to port NEZHA to the latest libFuzzer and is non-tested. Users who wish to access the code used in the NEZHA paper and the respective examples should access v-0.1.
We welcome issues and pull requests with new fuzzing targets.