https://github.com/aflgo/aflgo

Directed Greybox Fuzzing with AFL
https://github.com/aflgo/aflgo

Last synced: 3 months ago
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Directed Greybox Fuzzing with AFL

• Host: GitHub
• URL: https://github.com/aflgo/aflgo
• Owner: aflgo
• License: apache-2.0
• Fork: true (mirrorer/afl)
• Created: 2017-08-14T06:33:10.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2024-03-13T14:14:57.000Z (8 months ago)
• Last Synced: 2024-07-25T13:51:51.260Z (4 months ago)
• Language: C
• Homepage: http://mboehme.github.io/paper/CCS17.pdf
• Size: 1.98 MB
• Stars: 486
• Watchers: 21
• Forks: 133
• Open Issues: 18
• Metadata Files:
  • Readme: Readme.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-binary-analysis - AFLgo
• awesome-embedded-fuzzing - AFLGo

README

        
# AFLGo: Directed Greybox Fuzzing



AFLGo is an extension of American Fuzzy Lop (AFL).

Given a set of target locations (e.g., `folder/file.c:582`), AFLGo generates inputs specifically with the objective to exercise these target locations.

Unlike AFL, AFLGo spends most of its time budget on reaching specific target locations without wasting resources stressing unrelated program components. This is particularly interesting in the context of

* **patch testing** by setting changed statements as targets. When a critical component is changed, we would like to check whether this introduced any vulnerabilities. AFLGo, a fuzzer that can focus on those changes, has a higher chance of exposing the regression.

* **static analysis report verification** by setting statements as targets that a static analysis reports as potentially dangerous or vulnerability-inducing. When assessing the security of a program, static analysis tools might identify dangerous locations, such as critical system calls. AFLGo can generate inputs that actually show that this is indeed no false positive.

* **information flow detection** by setting sensitive sources and sinks as targets. To expose data leakage vulnerabilities, a security researcher would like to generate executions that exercise sensitive sources containing private information and sensitive sinks where data becomes visible to the outside world. A directed fuzzer can be used to generate such executions efficiently.

* **crash reproduction**  by setting method calls in the stack-trace as targets. When in-field crashes are reported, only the stack-trace and some environmental parameters are sent to the in-house development team. To preserve the user's privacy, the specific crashing input is often not available. AFLGo could help the in-house team to swiftly reproduce these crashes.

AFLGo is based on AFL from Michał Zaleski \. Checkout the project [awesome-directed-fuzzing](https://github.com/strongcourage/awesome-directed-fuzzing) for related work on directed greybox/whitebox fuzzing.

# Getting Started

Let's get started with building AFLGo (on Ubuntu 20.04) and fuzz the target libxml2:

```bash

git clone https://github.com/aflgo/aflgo.git

cd aflgo

export AFLGO=$PWD

# Build AFLGo

sudo ./build.sh

# When you fuzz for the very first time...

sudo sh -c 'echo core > /proc/sys/kernel/core_pattern'

# Fuzz the target libxml2

cd examples

./libxml2-ef709ce2.sh

```

See the detailed steps discussed below.

# Integration into OSS-Fuzz

The easiest way to use AFLGo is as patch testing tool in OSS-Fuzz. Here is our integration:

* https://github.com/aflgo/oss-fuzz

# Environment Variables

* **AFLGO_INST_RATIO** -- The proportion of basic blocks instrumented with distance values (default: 100).

* **AFLGO_SELECTIVE** -- Add AFL-trampoline only to basic blocks with distance values? (default: off).

* **AFLGO_PROFILER_FILE** -- When CFG-tracing is enabled, the data will be stored here. (See `instrument/README.md`)

# How to instrument a Binary with AFLGo

You can run [AFLGo building script](./build.sh) to do everything for you instead of manually go through **step 1** to **step 3**. Be careful in these steps we would download, build and install LLVM 11.0.0 from source, which may have unexpected impacts on compiler toolchain in current system.

For **step 4** to **step 8**, we are going to take libxml2 as an example. You can also equivalently run [libxml2 fuzzing script](./examples/libxml2-ef709ce2.sh) instead.

Before we start, make sure that source code tree of AFLGo is ready and we are in its root. Then set the environment variable `AFLGO` to it, which will be used in later steps. For example,

```bash

git clone https://github.com/aflgo/aflgo.git

cd aflgo

export AFLGO=$PWD

```

1) Install LLVM **11.0.0** with Gold-plugin. Then make sure that the following commands successfully executed:

   ```bash

   # Install LLVMgold into bfd-plugins

   mkdir /usr/lib/bfd-plugins

   cp /usr/local/lib/libLTO.so /usr/lib/bfd-plugins

   cp /usr/local/lib/LLVMgold.so /usr/lib/bfd-plugins

   ```

2) Install other prerequisite

   ```bash

   sudo apt-get update

   sudo apt-get install python3

   sudo apt-get install python3-dev

   sudo apt-get install python3-pip

   sudo apt-get install pkg-config

   sudo apt-get install autoconf

   sudo apt-get install automake

   sudo apt-get install libtool-bin

   sudo apt-get install gawk

   sudo apt-get install libboost-all-dev  # boost is not required if you use gen_distance_orig.sh in step 7

   python3 -m pip install networkx  # May vary by different python versions, see the case statement in build.sh

   python3 -m pip install pydot

   python3 -m pip install pydotplus

   ```

3) Compile AFLGo fuzzer, LLVM-instrumentation pass and the distance calculator

   ```bash

   export CXX=`which clang++`

   export CC=`which clang`

   export LLVM_CONFIG=`which llvm-config`

   pushd afl-2.57b; make clean all; popd;

   pushd instrument; make clean all; popd;

   pushd distance/distance_calculator; cmake ./; cmake --build ./; popd;

   ```

4) Download subject libxml2.

   ```bash

   # Clone subject repository

   git clone https://gitlab.gnome.org/GNOME/libxml2

   export SUBJECT=$PWD/libxml2

   ```

5) Set targets (e.g., changed statements in commit ef709ce2). Writes `BBtargets.txt`.

   ```bash

   # Setup directory containing all temporary files

   mkdir temp

   export TMP_DIR=$PWD/temp

   # Download commit-analysis tool

   wget https://raw.githubusercontent.com/jay/showlinenum/develop/showlinenum.awk

   chmod +x showlinenum.awk

   mv showlinenum.awk $TMP_DIR

   # Generate BBtargets from commit ef709ce2

   pushd $SUBJECT

     git checkout ef709ce2

     git diff -U0 HEAD^ HEAD > $TMP_DIR/commit.diff

   popd

   cat $TMP_DIR/commit.diff |  $TMP_DIR/showlinenum.awk show_header=0 path=1 | grep -e "\.[ch]:[0-9]*:+" -e "\.cpp:[0-9]*:+" -e "\.cc:[0-9]*:+" | cut -d+ -f1 | rev | cut -c2- | rev > $TMP_DIR/BBtargets.txt

   # Print extracted targets. 

   echo "Targets:"

   cat $TMP_DIR/BBtargets.txt

   ```

   **Note**: If there are no targets, there is nothing to instrument!

6) Generate CG and intra-procedural CFGs from the subject.

   ```bash

   # Set aflgo-instrumenter

   export CC=$AFLGO/instrument/aflgo-clang

   export CXX=$AFLGO/instrument/aflgo-clang++

   

   # Set aflgo-instrumentation flags

   export COPY_CFLAGS=$CFLAGS

   export COPY_CXXFLAGS=$CXXFLAGS

   export ADDITIONAL="-targets=$TMP_DIR/BBtargets.txt -outdir=$TMP_DIR -flto -fuse-ld=gold -Wl,-plugin-opt=save-temps"

   export CFLAGS="$CFLAGS $ADDITIONAL"

   export CXXFLAGS="$CXXFLAGS $ADDITIONAL"

   

   # Build libxml2 (in order to generate CG and CFGs).

   # Meanwhile go have a coffee ☕️

   export LDFLAGS=-lpthread

   pushd $SUBJECT

     ./autogen.sh

     ./configure --disable-shared

     make clean

     make xmllint

   popd

   ```

   You can test whether CG/CFG extraction was successful with

   ```bash

   $SUBJECT/xmllint --valid --recover $SUBJECT/test/dtd3

   ls $TMP_DIR/dot-files

   echo "Function targets"

   cat $TMP_DIR/Ftargets.txt

   ```

   **Note**:

    - If the linker (CCLD) complains that you should run `ranlib`, make sure that `libLTO.so` and `LLVMgold.so` (from Install LLVM 11.0.0 with Gold-plugin in step 1) can be found in `/usr/lib/bfd-plugins`.

    - If the compiler crashes, there is some problem with LLVM not supporting our instrumentation (*afl-llvm-pass.so.cc:540-577*). LLVM has changed the instrumentation-API very often :( You can check LLVM-version, fix problem, and prepare pull request.

    - You can speed up the compilation with a parallel build. However, this may impact which BBs are identified as targets. See https://github.com/aflgo/aflgo/issues/41.

7) Generate distance file.

   Firstly we need to clean up `BBnames.txt` and `BBcalls.txt`, otherwise `distance_calculator` may fail. This is necessary for any subjects, not only for *libxml2*.

   ```bash

   # Clean up

   cat $TMP_DIR/BBnames.txt | grep -v "^$"| rev | cut -d: -f2- | rev | sort | uniq > $TMP_DIR/BBnames2.txt && mv $TMP_DIR/BBnames2.txt $TMP_DIR/BBnames.txt

   

   cat $TMP_DIR/BBcalls.txt | grep -Ev "^[^,]*$|^([^,]*,){2,}[^,]*$"| sort | uniq > $TMP_DIR/BBcalls2.txt && mv $TMP_DIR/BBcalls2.txt $TMP_DIR/BBcalls.txt

   ```

   Then start to generate (this may take a while):

   ```bash

   # Generate distance ☕️

   # $AFLGO/distance/gen_distance_orig.sh is the original, but significantly slower, version

   

   $AFLGO/distance/gen_distance_fast.py $SUBJECT $TMP_DIR xmllint

   ```

   After that you can check the generated distance file with

   ```bash

   echo "Distance values:"

   head -n5 $TMP_DIR/distance.cfg.txt

   echo "..."

   tail -n5 $TMP_DIR/distance.cfg.txt

   ```

   **Note**: If `distance.cfg.txt` is empty, there was some problem computing the CG-level and BB-level target distance. See `$TMP_DIR/step*.log`.

8) Instrument the subject

   ```bash

   export CFLAGS="$COPY_CFLAGS -distance=$TMP_DIR/distance.cfg.txt"

   export CXXFLAGS="$COPY_CXXFLAGS -distance=$TMP_DIR/distance.cfg.txt"

   # Clean and build subject with distance instrumentation ☕️

   pushd $SUBJECT

     make clean

     ./configure --disable-shared

     make xmllint

   popd

   ```

   If your compilation crashes in this step, have a look at Issue [#4](https://github.com/aflgo/aflgo/issues/4#issuecomment-333947041).

# How to fuzz the instrumented binary

* We set the exponential annealing-based power schedule (`-z exp`).

* We set the time-to-exploitation to 45min (`-c 45m`), assuming the fuzzer is run for about an hour.

(Still take the previous libxml2 as an example)

```bash

# Construct seed corpus

mkdir in

cp -r $SUBJECT/test/dtd* in

cp $SUBJECT/test/dtds/* in

$AFLGO/afl-2.57b/afl-fuzz -S ef709ce2 -z exp -c 45m -i in -o out $SUBJECT/xmllint --valid --recover @@

```

* **Tipp**: Concurrently fuzz the most recent version as master with classical AFL :)

```bash

$AFL/afl-fuzz -M master -i in -o out $MASTER/xmllint --valid --recover @@

```

* Run more [fuzzing scripts](./examples) of various real programs like *Binutils*, *jasper*, *lrzip*, *libming* and *DARPA CGC*. Those scripts haven't contained any dependencies installing steps yet. So it's recommended that see READMEs of those projects first to check their requirements.

## Contributors