This version requires a current llvm 11+ compiled from the GitHub master.
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Use afl-clang-lto/afl-clang-lto++ because it is faster and gives better coverage than anything else that is out there in the AFL world.
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You can use it together with llvm_mode: laf-intel and the instrument file listing features and can be combined with cmplog/Redqueen.
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It only works with llvm 11+.
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AUTODICTIONARY feature (see below)!
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If any problems arise, be sure to set
AR=llvm-ar RANLIB=llvm-ranlib
. Some targets might needLD=afl-clang-lto
and othersLD=afl-ld-lto
.
A big issue with how AFL++ works is that the basic block IDs that are set during compilation are random - and hence naturally the larger the number of instrumented locations, the higher the number of edge collisions are in the map. This can result in not discovering new paths and therefore degrade the efficiency of the fuzzing process.
This issue is underestimated in the fuzzing community! With a 2^16 = 64kb standard map at already 256 instrumented blocks, there is on average one collision. On average, a target has 10.000 to 50.000 instrumented blocks, hence the real collisions are between 750-18.000!
To reach a solution that prevents any collisions took several approaches and many dead ends until we got to this:
- We instrument at link time when we have all files pre-compiled.
- To instrument at link time, we compile in LTO (link time optimization) mode.
- Our compiler (afl-clang-lto/afl-clang-lto++) takes care of setting the correct LTO options and runs our own afl-ld linker instead of the system linker.
- The LLVM linker collects all LTO files to link and instruments them so that we have non-colliding edge overage.
- We use a new (for afl) edge coverage - which is the same as in llvm -fsanitize=coverage edge coverage mode. :)
The result:
- 10-25% speed gain compared to llvm_mode
- guaranteed non-colliding edge coverage :-)
- The compile time, especially for binaries to an instrumented library, can be much longer.
Example build output from a libtiff build:
libtool: link: afl-clang-lto -g -O2 -Wall -W -o thumbnail thumbnail.o ../libtiff/.libs/libtiff.a ../port/.libs/libport.a -llzma -ljbig -ljpeg -lz -lm
afl-clang-lto++2.63d by Marc "vanHauser" Heuse <[email protected]> in mode LTO
afl-llvm-lto++2.63d by Marc "vanHauser" Heuse <[email protected]>
AUTODICTIONARY: 11 strings found
[+] Instrumented 12071 locations with no collisions (on average 1046 collisions would be in afl-gcc/afl-clang-fast) (non-hardened mode).
llvm 11 or even 12 should be available in all current Linux repositories. If you use an outdated Linux distribution, read the next section.
Installing the llvm snapshot builds is easy and mostly painless:
In the following line, change NAME
for your Debian or Ubuntu release name
(e.g., buster, focal, eon, etc.):
echo deb http://apt.llvm.org/NAME/ llvm-toolchain-NAME NAME >> /etc/apt/sources.list
Then add the pgp key of llvm and install the packages:
wget -O - https://apt.llvm.org/llvm-snapshot.gpg.key | apt-key add -
apt-get update && apt-get upgrade -y
apt-get install -y clang-12 clang-tools-12 libc++1-12 libc++-12-dev \
libc++abi1-12 libc++abi-12-dev libclang1-12 libclang-12-dev \
libclang-common-12-dev libclang-cpp12 libclang-cpp12-dev liblld-12 \
liblld-12-dev liblldb-12 liblldb-12-dev libllvm12 libomp-12-dev \
libomp5-12 lld-12 lldb-12 llvm-12 llvm-12-dev llvm-12-runtime llvm-12-tools
Building llvm from GitHub takes quite some time and is not painless:
sudo apt install binutils-dev # this is *essential*!
git clone --depth=1 https://github.com/llvm/llvm-project
cd llvm-project
mkdir build
cd build
# Add -G Ninja if ninja-build installed
# "Building with ninja significantly improves your build time, especially with
# incremental builds, and improves your memory usage."
cmake \
-DCLANG_INCLUDE_DOCS="OFF" \
-DCMAKE_BUILD_TYPE=Release \
-DLLVM_BINUTILS_INCDIR=/usr/include/ \
-DLLVM_BUILD_LLVM_DYLIB="ON" \
-DLLVM_ENABLE_BINDINGS="OFF" \
-DLLVM_ENABLE_PROJECTS='clang;compiler-rt;libcxx;libcxxabi;libunwind;lld' \
-DLLVM_ENABLE_WARNINGS="OFF" \
-DLLVM_INCLUDE_BENCHMARKS="OFF" \
-DLLVM_INCLUDE_DOCS="OFF" \
-DLLVM_INCLUDE_EXAMPLES="OFF" \
-DLLVM_INCLUDE_TESTS="OFF" \
-DLLVM_LINK_LLVM_DYLIB="ON" \
-DLLVM_TARGETS_TO_BUILD="host" \
../llvm/
cmake --build . -j4
export PATH="$(pwd)/bin:$PATH"
export LLVM_CONFIG="$(pwd)/bin/llvm-config"
export LD_LIBRARY_PATH="$(llvm-config --libdir)${LD_LIBRARY_PATH:+:$LD_LIBRARY_PATH}"
cd /path/to/AFLplusplus/
make
sudo make install
Just use afl-clang-lto like you did with afl-clang-fast or afl-gcc.
Also, the instrument file listing (AFL_LLVM_ALLOWLIST/AFL_LLVM_DENYLIST -> README.instrument_list.md) and laf-intel/compcov (AFL_LLVM_LAF_* -> README.laf-intel.md) work.
Example:
CC=afl-clang-lto CXX=afl-clang-lto++ RANLIB=llvm-ranlib AR=llvm-ar ./configure
make
NOTE: some targets also need to set the linker, try both afl-clang-lto
and
afl-ld-lto
for LD=
before configure
.
Note: this is highly discouraged! Try to compile to static libraries with afl-clang-lto instead of shared libraries!
To make instrumented shared libraries work with afl-clang-lto, you have to do quite some extra steps.
Every shared library you want to instrument has to be individually compiled. The
environment variable AFL_LLVM_LTO_DONTWRITEID=1
has to be set during
compilation. Additionally, the environment variable AFL_LLVM_LTO_STARTID
has
to be set to the added edge count values of all previous compiled instrumented
shared libraries for that target. E.g., for the first shared library this would
be AFL_LLVM_LTO_STARTID=0
and afl-clang-lto will then report how many edges
have been instrumented (let's say it reported 1000 instrumented edges). The
second shared library then has to be set to that value
(AFL_LLVM_LTO_STARTID=1000
in our example), for the third to all previous
counts added, etc.
The final program compilation step then may not have
AFL_LLVM_LTO_DONTWRITEID
set, and AFL_LLVM_LTO_STARTID
must be set to all
edge counts added of all shared libraries it will be linked to.
This is quite some hands-on work, so better stay away from instrumenting shared libraries. :-)
While compiling, a dictionary based on string comparisons is automatically generated and put into the target binary. This dictionary is transferred to afl-fuzz on start. This improves coverage statistically by 5-10%. :)
Note that if for any reason you do not want to use the autodictionary feature,
then just set the environment variable AFL_NO_AUTODICT
when starting afl-fuzz.
To speed up fuzzing a little bit more, it is possible to set a fixed shared memory map. Recommended is the value 0x10000.
In most cases, this will work without any problems. However, if a target uses early constructors, ifuncs, or a deferred forkserver, this can crash the target.
Also, on unusual operating systems/processors/kernels or weird libraries the recommended 0x10000 address might not work, so then change the fixed address.
To enable this feature, set AFL_LLVM_MAP_ADDR
with the address.
Setting export AFL_LLVM_DOCUMENT_IDS=file
will document in a file which edge
ID was given to which function. This helps to identify functions with variable
bytes or which functions were touched by an input.
Some targets are difficult because the configure script does unusual stuff that
is unexpected for afl. See the next section Potential issues
for how to solve
these.
An example of a hard to solve target is ffmpeg. Here is how to successfully instrument it:
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Get and extract the current ffmpeg and change to its directory.
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Running configure with --cc=clang fails and various other items will fail when compiling, so we have to trick configure:
./configure --enable-lto --disable-shared --disable-inline-asm
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Now the configuration is done - and we edit the settings in
./ffbuild/config.mak
(-: the original line, +: what to change it into):-CC=gcc +CC=afl-clang-lto -CXX=g++ +CXX=afl-clang-lto++ -AS=gcc +AS=llvm-as -LD=gcc +LD=afl-clang-lto++ -DEPCC=gcc +DEPCC=afl-clang-lto -DEPAS=gcc +DEPAS=afl-clang-lto++ -AR=ar +AR=llvm-ar -AR_CMD=ar +AR_CMD=llvm-ar -NM_CMD=nm -g +NM_CMD=llvm-nm -g -RANLIB=ranlib -D +RANLIB=llvm-ranlib -D
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Then type make, wait for a long time, and you are done. :)
Building jsc is difficult as the build script has bugs.
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Checkout Webkit:
svn checkout https://svn.webkit.org/repository/webkit/trunk WebKit cd WebKit
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Fix the build environment:
mkdir -p WebKitBuild/Release cd WebKitBuild/Release ln -s ../../../../../usr/bin/llvm-ar-12 llvm-ar-12 ln -s ../../../../../usr/bin/llvm-ranlib-12 llvm-ranlib-12 cd ../..
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Build. :)
Tools/Scripts/build-jsc --jsc-only --cli --cmakeargs="-DCMAKE_AR='llvm-ar-12' -DCMAKE_RANLIB='llvm-ranlib-12' -DCMAKE_VERBOSE_MAKEFILE:BOOL=ON -DCMAKE_CC_FLAGS='-O3 -lrt' -DCMAKE_CXX_FLAGS='-O3 -lrt' -DIMPORTED_LOCATION='/lib/x86_64-linux-gnu/' -DCMAKE_CC=afl-clang-lto -DCMAKE_CXX=afl-clang-lto++ -DENABLE_STATIC_JSC=ON"
If you see this message:
/bin/ld: libfoo.a: error adding symbols: archive has no index; run ranlib to add one
This is because usually gnu gcc ranlib is being called which cannot deal with
clang LTO files. The solution is simple: when you ./configure
, you also have
to set RANLIB=llvm-ranlib
and AR=llvm-ar
.
Solution:
AR=llvm-ar RANLIB=llvm-ranlib CC=afl-clang-lto CXX=afl-clang-lto++ ./configure --disable-shared
And on some targets you have to set AR=/RANLIB=
even for make
as the
configure script does not save it. Other targets ignore environment variables
and need the parameters set via ./configure --cc=... --cxx= --ranlib= ...
etc.
(I am looking at you ffmpeg!)
If you see this message:
assembler command failed ...
Then try setting llvm-as
for configure:
AS=llvm-as ...
afl-clang-lto is still work in progress.
Known issues:
- Anything that llvm 11+ cannot compile, afl-clang-lto cannot compile either - obviously.
- Anything that does not compile with LTO, afl-clang-lto cannot compile either - obviously.
Hence, if building a target with afl-clang-lto fails, try to build it with
llvm12 and LTO enabled (CC=clang-12
, CXX=clang++-12
, CFLAGS=-flto=full
,
and CXXFLAGS=-flto=full
).
If this succeeds, then there is an issue with afl-clang-lto. Please report at AFLplusplus#226.
Even some targets where clang-12 fails can be built if the fail is just in
./configure
, see Solving difficult targets
above.
This was originally envisioned by hexcoder- in Summer 2019. However, we saw no way to create a pass that is run at link time - although there is a option for this in the PassManager: EP_FullLinkTimeOptimizationLast. ("Fun" info - nobody knows what this is doing. And the developer who implemented this didn't respond to emails.)
In December then came the idea to implement this as a pass that is run via the llvm "opt" program, which is performed via an own linker that afterwards calls the real linker. This was first implemented in January and work ... kinda. The LTO time instrumentation worked, however, "how" the basic blocks were instrumented was a problem, as reducing duplicates turned out to be very, very difficult with a program that has so many paths and therefore so many dependencies. A lot of strategies were implemented - and failed. And then sat solvers were tried, but with over 10.000 variables that turned out to be a dead-end too.
The final idea to solve this came from domenukk who proposed to insert a block into an edge and then just use incremental counters ... and this worked! After some trials and errors to implement this vanhauser-thc found out that there is actually an llvm function for this: SplitEdge() :-)
Still more problems came up though as this only works without bugs from llvm 9 onwards, and with high optimization the link optimization ruins the instrumented control flow graph.
This is all now fixed with llvm 11+. The llvm's own linker is now able to load passes and this bypasses all problems we had.
Happy end :)