forked from OSchip/llvm-project
152 lines
5.7 KiB
Plaintext
152 lines
5.7 KiB
Plaintext
This directory contains three utilities for fuzzing Clang: clang-fuzzer,
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clang-objc-fuzzer, and clang-proto-fuzzer. All use libFuzzer to generate inputs
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to clang via coverage-guided mutation.
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The three utilities differ, however, in how they structure inputs to Clang.
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clang-fuzzer makes no attempt to generate valid C++ programs and is therefore
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primarily useful for stressing the surface layers of Clang (i.e. lexer, parser).
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clang-objc-fuzzer is similar but for Objective-C: it makes no attempt to
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generate a valid Objective-C program.
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clang-proto-fuzzer uses a protobuf class to describe a subset of the C++
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language and then uses libprotobuf-mutator to mutate instantiations of that
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class, producing valid C++ programs in the process. As a result,
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clang-proto-fuzzer is better at stressing deeper layers of Clang and LLVM.
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Some of the fuzzers have example corpuses inside the corpus_examples directory.
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===================================
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Building clang-fuzzer
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===================================
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Within your LLVM build directory, run CMake with the following variable
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definitions:
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- CMAKE_C_COMPILER=clang
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- CMAKE_CXX_COMPILER=clang++
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- LLVM_USE_SANITIZE_COVERAGE=YES
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- LLVM_USE_SANITIZER=Address
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Then build the clang-fuzzer target.
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Example:
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cd $LLVM_SOURCE_DIR
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mkdir build && cd build
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cmake .. -GNinja -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ \
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-DLLVM_USE_SANITIZE_COVERAGE=YES -DLLVM_USE_SANITIZER=Address
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ninja clang-fuzzer
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======================
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Running clang-fuzzer
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======================
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bin/clang-fuzzer CORPUS_DIR
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===================================
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Building clang-objc-fuzzer
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===================================
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Within your LLVM build directory, run CMake with the following variable
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definitions:
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- CMAKE_C_COMPILER=clang
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- CMAKE_CXX_COMPILER=clang++
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- LLVM_USE_SANITIZE_COVERAGE=YES
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- LLVM_USE_SANITIZER=Address
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Then build the clang-objc-fuzzer target.
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Example:
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cd $LLVM_SOURCE_DIR
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mkdir build && cd build
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cmake .. -GNinja -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ \
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-DLLVM_USE_SANITIZE_COVERAGE=YES -DLLVM_USE_SANITIZER=Address
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ninja clang-objc-fuzzer
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======================
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Running clang-objc-fuzzer
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======================
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bin/clang-objc-fuzzer CORPUS_DIR
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e.g. using the example objc corpus,
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bin/clang-objc-fuzzer <path to corpus_examples/objc> <path to new directory to store corpus findings>
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=======================================================
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Building clang-proto-fuzzer (Linux-only instructions)
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=======================================================
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Install the necessary dependencies:
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- binutils // needed for libprotobuf-mutator
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- liblzma-dev // needed for libprotobuf-mutator
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- libz-dev // needed for libprotobuf-mutator
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- docbook2x // needed for libprotobuf-mutator
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- Recent version of protobuf [3.3.0 is known to work]
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Within your LLVM build directory, run CMake with the following variable
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definitions:
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- CMAKE_C_COMPILER=clang
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- CMAKE_CXX_COMPILER=clang++
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- LLVM_USE_SANITIZE_COVERAGE=YES
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- LLVM_USE_SANITIZER=Address
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- CLANG_ENABLE_PROTO_FUZZER=ON
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Then build the clang-proto-fuzzer and clang-proto-to-cxx targets. Optionally,
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you may also build clang-fuzzer with this setup.
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Example:
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cd $LLVM_SOURCE_DIR
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mkdir build && cd build
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cmake .. -GNinja -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ \
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-DLLVM_USE_SANITIZE_COVERAGE=YES -DLLVM_USE_SANITIZER=Address \
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-DCLANG_ENABLE_PROTO_FUZZER=ON
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ninja clang-proto-fuzzer clang-proto-to-cxx
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This directory also contains a Dockerfile which sets up all required
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dependencies and builds the fuzzers.
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============================
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Running clang-proto-fuzzer
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============================
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bin/clang-proto-fuzzer CORPUS_DIR
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Arguments can be specified after -ignore_remaining_args=1 to modify the compiler
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invocation. For example, the following command line will fuzz LLVM with a
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custom optimization level and target triple:
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bin/clang-proto-fuzzer CORPUS_DIR -ignore_remaining_args=1 -O3 -triple \
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arm64apple-ios9
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To translate a clang-proto-fuzzer corpus output to C++:
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bin/clang-proto-to-cxx CORPUS_OUTPUT_FILE
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===================
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llvm-proto-fuzzer
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===================
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Like, clang-proto-fuzzer, llvm-proto-fuzzer is also a protobuf-mutator based
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fuzzer. It receives as input a cxx_loop_proto which it then converts into a
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string of valid LLVM IR: a function with either a single loop or two nested
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loops. It then creates a new string of IR by running optimization passes over
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the original IR. Currently, it only runs a loop-vectorize pass but more passes
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can easily be added to the fuzzer. Once there are two versions of the input
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function (optimized and not), llvm-proto-fuzzer uses LLVM's JIT Engine to
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compile both functions. Lastly, it runs both functions on a suite of inputs and
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checks that both functions behave the same on all inputs. In this way,
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llvm-proto-fuzzer can find not only compiler crashes, but also miscompiles
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originating from LLVM's optimization passes.
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llvm-proto-fuzzer is built very similarly to clang-proto-fuzzer. You can run the
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fuzzer with the following command:
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bin/clang-llvm-proto-fuzzer CORPUS_DIR
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To translate a cxx_loop_proto file into LLVM IR do:
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bin/clang-loop-proto-to-llvm CORPUS_OUTPUT_FILE
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To translate a cxx_loop_proto file into C++ do:
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bin/clang-loop-proto-to-cxx CORPUS_OUTPUT_FILE
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Note: To get a higher number of executions per second with llvm-proto-fuzzer it
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helps to build it without ASan instrumentation and with the -O2 flag. Because
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the fuzzer is not only compiling code, but also running it, as the inputs get
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large, the time necessary to fuzz one input can get very high.
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Example:
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cmake .. -GNinja -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ \
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-DCLANG_ENABLE_PROTO_FUZZER=ON -DLLVM_USE_SANITIZE_COVERAGE=YES \
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-DCMAKE_CXX_FLAGS="-O2"
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ninja clang-llvm-proto-fuzzer clang-loop-proto-to-llvm
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