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I've just written a performant in-memory fuzzing module with @fridadotre for AFL++ https://github.com/andreafioraldi/frida-js-afl-instr …. Watch AFL++ on GH and stay tuned for a frida_mode in the next days!pic.twitter.com/4FHZbsi0Fy
If you want to start now to fuzz Android native libraries I've just merged a @quarkslab QBDI based mode for Android fuzzing from hac425xxx. For fuzzing both native and generated code, Frida mode will be here ASAP ;)https://github.com/vanhauser-thc/AFLplusplus/tree/master/qbdi_mode …
Sounds like you'd need to be quite careful about picking what you want to harness this way, pretty limited to stateless parsing code? Could you fix state, free allocations the target makes, close fds, etc at the end of one persistent loop in frida? Pretty cool if so :)
yep my simple script is pure persistent fuzzing now. probably i'll implement also a forkserver. For allocations/fds can be done simply hooking *alloc/open but of course has a cost that can be huge if the application heavily uses such functions.
Awesome! How does this improve over the existing persistent-mode implementation?
It doesn't. QEMU persistent mode is faster (but only for x86), the benefit of using Frida is the binary instrumentation of mobile apps. The frida_mode AFL++ will problably targets only mobile devices, for the other options there is already QEMU.
What is performant in memory fuzzing?
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