DigFuzz

Unofficial Implementation of DigFuzz from paper "Send Hardest Problems My Way: Probabilistic Path Prioritization for Hybrid Fuzzing"

Setup Executor

Executor is the part of DigFuzz that collects coverage and bb hit count data. Currently, we support QEMU or LLVM.

QEMU:

QEMU is instrumented to dump bb hit count to a shared memory region where DigFuzz can read.

./build_all_qemu.sh

LLVM:

trace-pc-guard feature of LLVM is used to provide bb hit count information. Although this is faster than using QEMU, translating the address of LLVM instrumented binary to that of uninstrumented binary (concolic execution tools have difficulty with instrumented binaries) may not be accurate.

TODO

Setup Concolic Execution Tools

Concolic execution tool is the part of DigFuzz that conducts directed solving. Fundamentally, it is a function that takes in a binary and a list of code location (representing a path), then provides an input that makes binary go through this path. Currently, we support QSYM or SymCC.

QSYM:

Given QSYM is built on old version of LLVM, you can use a remote instance with Ubuntu 14.04 and setup QSYM there.

Run following command at remote host:

git clone https://github.com/sslab-gatech/qsym.git && cd qsym
vim qsym.diff # copy content from qsym.diff in this repo to remote
git apply qsym.diff
./setup.sh
pip install .

Then, edit the config.py to set the credential for accessing that instance and installation location of QSYM.

SymCC:

TODO

Start Fuzzing (QEMU + QSYM)

Compile your target with LLVMFuzzerTestOneInput exported and -no-pie enabled, which should yield a .o file

CFLAGS="-no-pie" CXXFLAGS="-no-pie" make fuzzer

Edit config.py for path of the .o file

vim config.py

If not configured system for AFL, do

sudo ./AFLplusplus/afl-system-config

In one terminal (AFL stuffs)

python3 run_afl.py

In another terminal (QSYM stuffs)

python3 digfuzz.py

QEMU-based Instrumentation Workflow

QEMU side:

Dump BB hitcount to shared memory

Our side:

Re-execute corpus inputs to build execution tree. (Not concolic execution, just concrete execution with instrumentation)
Read shared memory and add BB visit count to execution tree
Do a DFS on execution to assign probabilities for each edge
Identify missed branch in all corpus traces and build a priority queue for these traces with priority as 1-probability
QSYM do concolic execution on the missed branch to identify input
Add input to AFL corpus

LLVM-based Instrumentation Workflow

AFL side:

Compile binary with two harness, one for AFL, another for angr.
Instrument AFL binary via Clang to provide block information.

Our side:

Re-execute corpus inputs to build execution tree. (Not concolic execution, just concrete execution with instrumentation)
For every trace AFL binary gives, add visit count to the execution tree.
Do a DFS on execution to assign probabilities for each edge
Identify missed branch in all corpus traces and build a priority queue for these traces with priority as 1-probability
QSYM do concolic execution on the missed branch to identify input
Add input to AFL corpus

shouc/digfuzz

ErrorLooks like something went wrong!

About

Resources

Uh oh!

Stars

Watchers

Forks

Releases

Packages 0

Uh oh!

Languages

Error
Looks like something went wrong!

Packages