American Fuzzy Lop VS boofuzz

There's some efforts to guide test generation for property based testing to make the instruction pointer explore as large a space as possible.

This effort is more mature in the fuzzing community. See eg American Fuzzy Lop https://github.com/google/AFL

What you're describing, just generating random input to test a program, is sometimes called "blind fuzzing" but the state-of-the-art is far beyond that. Maybe try reading through the documentation of e.g. https://github.com/google/AFL to see what a fuzzer does and why just producing random input isn't even scratching the surface.

for general riscv I used to use this https://github.com/google/AFL I dont know if it supports x64 tho.

Ex ( AFL, WinAFL, HonggFuzz, LibFuzzer, Jazzer )

I wrote this little fuzz test target in order to fuzz it with afl (under ASan and UBSan):

afl, which is trivial to apply to this program:

I made my own version of a TCL interpreter (well, a very TCL like langauge) derived from "picol" available at https://github.com/howerj/pickle. There are many different re-implementations and derivatives of this interpreter but they all seem very "crashy", this one has been significantly hardened by using a fuzzer on it which ran for months called American Fuzzy Lop https://lcamtuf.coredump.cx/afl/ . It is also more suitable for embedded use whilst still not having arbitrary restrictions like many other implementations.

On Linux afl is a very powerful bug-finding tool, and it's a great companion when doing code review. Composes well with ASan and UBSan.

b-, https://lcamtuf.coredump.cx/afl/

The one thing that's not really fully encapsulated in a lot of these comment chains below is the role of custom written fuzzers for competitions like this. Frameworks like AFL, BooFuzz, etc. A properly written test file will allow for most of the hunting to happen automagically by tampering with function calls or inputs until something crashes. By configuring an environment appropriately, you can run millions of test cases, and get the crashes logged to parse through later. This allows the researchers/exploit writers to only focus on the exceptions/traces that seem the most fruitful. This is one methodology, it's not the case for everyone, but most codebases are too big to go through the ASM by hand these days.