Fuzzing Interface¶
The fuzzing interface is glue code living in mozilla-central in order to make it easier for developers and security researchers to test C/C++ code with either libFuzzer or afl-fuzz.
These fuzzing tools, are based on compile-time instrumentation to measure things like branch coverage and more advanced heuristics per fuzzing test. Doing so allows these tools to progress through code with little to no custom logic/knowledge implemented in the fuzzer itself. Usually, the only thing these tools need is a code “shim” that provides the entry point for the fuzzer to the code to be tested. We call this additional code a fuzzing target and the rest of this manual describes how to implement and work with these targets.
As for the tools used with these targets, we currently recommend the use of libFuzzer over afl-fuzz, as the latter is no longer maintained while libFuzzer is being actively developed. Furthermore, libFuzzer has some advanced instrumentation features (e.g. value profiling to deal with complicated comparisons in code), making it overall more effective.
What can be tested?¶
The interface can be used to test all C/C++ code that either ends up in
libxul
(more precisely, the gtest version of libxul
) or is
part of the JS engine.
Note that this is not the right testing approach for testing the full browser as a whole. It is rather meant for component-based testing (especially as some components cannot be easily separated out of the full build).
Note
Note: If you are working on the JS engine (trying to reproduce a bug or seeking to develop a new fuzzing target), then please also read the JS Engine Specifics Section at the end of this documentation, as the JS engine offers additional options for implementing and running fuzzing targets.
Reproducing bugs for existing fuzzing targets¶
If you are working on a bug that involves an existing fuzzing interface target, you have two options for reproducing the issue:
Using existing builds¶
We have several fuzzing builds in CI that you can simply download. We recommend
using fuzzfetch
for this purpose, as it makes downloading and unpacking
these builds much easier.
You can install fuzzfetch
from
Github or
via pip.
Afterwards, you can run
$ python -m fuzzfetch -a --fuzzing --gtest -n firefox-fuzzing
to fetch the latest optimized build. Alternatively, we offer non-ASan debug builds which you can download using
$ python -m fuzzfetch -d --fuzzing --gtest -n firefox-fuzzing
In both commands, firefox-fuzzing
indicates the name of the directory that
will be created for the download.
Afterwards, you can reproduce the bug using
$ FUZZER=TargetName firefox-fuzzing/firefox test.bin
assuming that TargetName
is the name of the fuzzing target specified in the
bug you are working on and test.bin
is the attached testcase.
Note
Note: You should not export the FUZZER
variable permanently
in your shell, especially if you plan to do local builds. If the FUZZER
variable is exported, it will affect the build process.
If the CI builds don’t meet your requirements and you need a local build instead, you can follow the steps below to create one:
Local build requirements and flags¶
You will need a Linux environment with a recent Clang. Using the Clang downloaded
by ./mach bootstrap
or a newer version is recommended.
The only build flag required to enable the fuzzing targets is --enable-fuzzing
,
so adding
ac_add_options --enable-fuzzing
to your .mozconfig
is already sufficient for producing a fuzzing build.
However, for improved crash handling capabilities and to detect additional errors,
it is strongly recommended to combine libFuzzer with AddressSanitizer
by adding
ac_add_options --enable-address-sanitizer
at least for optimized builds and bugs requiring ASan to reproduce at all (e.g. you are working on a bug where ASan reports a memory safety violation of some sort).
Once your build is complete, you must additionally run
$ ./mach gtest dontruntests
to force the gtest libxul to be built.
Note
Note: If you modify any code, please ensure that you run both build
commands to ensure that the gtest libxul is also rebuilt. It is a common mistake
to only run ./mach build
and miss the second command.
Once these steps are complete, you can reproduce the bug locally using the same steps as described above for the downloaded builds.
Developing new fuzzing targets¶
Developing a new fuzzing target using the fuzzing interface only requires a few steps.
Determine if the fuzzing interface is the right tool¶
The fuzzing interface is not suitable for every kind of testing. In particular if your testing requires the full browser to be running, then you might want to look into other testing methods.
The interface uses the ScopedXPCOM
implementation to provide an environment
in which XPCOM is available and initialized. You can initialize further subsystems
that you might require, but you are responsible yourself for any kind of
initialization steps.
There is (in theory) no limit as to how far you can take browser initialization. However, the more subsystems are involved, the more problems might occur due to non-determinism and loss of performance.
If you are unsure if the fuzzing interface is the right approach for you or you require help in evaluating what could be done for your particular task, please don’t hestitate to contact us.
Develop the fuzzing code¶
Where to put your fuzzing code¶
The code using the fuzzing interface usually lives in a separate directory
called fuzztest
that is on the same level as gtests. If your component
has no gtests, then a subdirectory either in tests or in your main directory
will work. If such a directory does not exist yet in your component, then you
need to create one with a suitable moz.build
. See the transport target
for an example
In order to include the new subdirectory into the build process, you will
also have to modify the toplevel moz.build
file accordingly. For this
purpose, you should add your directory to TEST_DIRS
only if FUZZING_INTERFACES
is set. See again the transport target for an example.
How your code should look like¶
In order to define your fuzzing target MyTarget
, you only need to implement 2 functions:
A one-time initialization function.
At startup, the fuzzing interface calls this function once, so this can be used to perform one-time operations like initializing subsystems or parsing extra fuzzing options.
This function is the equivalent of the LLVMFuzzerInitialize function and has the same signature. However, with our fuzzing interface, it won’t be resolved by its name, so it can be defined
static
and called whatever you prefer. Note that the function should alwaysreturn 0
and can (except for the return), remain empty.For the sake of this documentation, we assume that you have
static int FuzzingInitMyTarget(int* argc, char*** argv);
The fuzzing iteration function.
This is where the actual fuzzing happens, and this function is the equivalent of LLVMFuzzerTestOneInput. Again, the difference to the fuzzing interface is that the function won’t be resolved by its name. In addition, we offer two different possible signatures for this function, either
static int FuzzingRunMyTarget(const uint8_t* data, size_t size);
or
static int FuzzingRunMyTarget(nsCOMPtr<nsIInputStream> inputStream);
The latter is just a wrapper around the first one for implementations that usually work with streams. No matter which of the two signatures you choose to work with, the only thing you need to implement inside the function is the use of the provided data with your target implementation. This can mean to simply feed the data to your target, using the data to drive operations on the target API, or a mix of both.
While doing so, you should avoid altering global state in a permanent way, using additional sources of data/randomness or having code run beyond the lifetime of the iteration function (e.g. on another thread), for one simple reason: Coverage-guided fuzzing tools depend on the deterministic nature of the iteration function. If the same input to this function does not lead to the same execution when run twice (e.g. because the resulting state depends on multiple successive calls or because of additional external influences), then the tool will not be able to reproduce its fuzzing progress and perform badly. Dealing with this restriction can be challenging e.g. when dealing with asynchronous targets that run multi-threaded, but can usually be managed by synchronizing execution on all threads at the end of the iteration function. For implementations accumulating global state, it might be necessary to (re)initialize this global state in each iteration, rather than doing it once in the initialization function, even if this costs additional performance.
Note that unlike the vanilla libFuzzer approach, you are allowed to
return 1
in this function to indicate that an input is “bad”. Doing so will cause libFuzzer to discard the input, no matter if it generated new coverage or not. This is particularly useful if you have means to internally detect and catch bad testcase behavior such as timeouts/excessive resource usage etc. to avoid these tests to end up in your corpus.
Once you have implemented the two functions, the only thing remaining is to register them with the fuzzing interface. For this purpose, we offer two macros, depending on which iteration function signature you used. If you sticked to the classic signature using buffer and size, you can simply use
#include "FuzzingInterface.h"
// Your includes and code
MOZ_FUZZING_INTERFACE_RAW(FuzzingInitMyTarget, FuzzingRunMyTarget, MyTarget);
where MyTarget
is the name of the target and will be used later to decide
at runtime which target should be used.
If instead you went for the streaming interface, you need a different include, but the macro invocation is quite similar:
#include "FuzzingInterfaceStream.h"
// Your includes and code
MOZ_FUZZING_INTERFACE_STREAM(FuzzingInitMyTarget, FuzzingRunMyTarget, MyTarget);
For a live example, see also the implementation of the STUN fuzzing target.
Add instrumentation to the code being tested¶
libFuzzer requires that the code you are trying to test is instrumented
with special compiler flags. Fortunately, adding these on a per-directory basis
can be done just by including the following directive in each moz.build
file that builds code under test:
# Add libFuzzer configuration directives
include('/tools/fuzzing/libfuzzer-config.mozbuild')
The include already does the appropriate configuration checks to be only active in fuzzing builds, so you don’t have to guard this in any way.
Note
Note: This include modifies CFLAGS and CXXFLAGS accordingly
but this only works for source files defined in this particular
directory. The flags are not propagated to subdirectories automatically
and you have to ensure that each directory that builds source files
for your target has the include added to its moz.build
file.
By keeping the instrumentation limited to the parts that are actually being tested using this tool, you not only increase the performance but also potentially reduce the amount of noise that libFuzzer sees.
Build your code¶
See the Build instructions above for instructions
how to modify your .mozconfig
to create the appropriate build.
Running your code and building a corpus¶
You need to set the following environment variable to enable running the fuzzing code inside Firefox instead of the regular browser.
FUZZER=name
Where name
is the name of your fuzzing module that you specified
when calling the MOZ_FUZZING_INTERFACE_RAW
macro. For the example
above, this would be MyTarget
or StunParser
for the live example.
Now when you invoke the firefox binary in your build directory with the
-help=1
parameter, you should see the regular libFuzzer help. On
Linux for example:
$ FUZZER=StunParser obj-asan/dist/bin/firefox -help=1
You should see an output similar to this:
Running Fuzzer tests...
Usage:
To run fuzzing pass 0 or more directories.
obj-asan/dist/bin/firefox [-flag1=val1 [-flag2=val2 ...] ] [dir1 [dir2 ...] ]
To run individual tests without fuzzing pass 1 or more files:
obj-asan/dist/bin/firefox [-flag1=val1 [-flag2=val2 ...] ] file1 [file2 ...]
Flags: (strictly in form -flag=value)
verbosity 1 Verbosity level.
seed 0 Random seed. If 0, seed is generated.
runs -1 Number of individual test runs (-1 for infinite runs).
max_len 0 Maximum length of the test input. If 0, libFuzzer tries to guess a good value based on the corpus and reports it.
...
Reproducing a Crash¶
In order to reproduce a crash from a given test file, simply put the file as the only argument on the command line, e.g.
$ FUZZER=StunParser obj-asan/dist/bin/firefox test.bin
This should reproduce the given problem.
FuzzManager and libFuzzer¶
Our FuzzManager project comes with a harness for running libFuzzer with an optional connection to a FuzzManager server instance. Note that this connection is not mandatory, even without a server you can make use of the local harness.
You can find the harness here.
An example invocation for the harness to use with StunParser could look like this:
FUZZER=StunParser python /path/to/afl-libfuzzer-daemon.py --fuzzmanager \
--stats libfuzzer-stunparser.stats --libfuzzer-auto-reduce-min 500 --libfuzzer-auto-reduce 30 \
--tool libfuzzer-stunparser --libfuzzer --libfuzzer-instances 6 obj-asan/dist/bin/firefox \
-max_len=256 -use_value_profile=1 -rss_limit_mb=3000 corpus-stunparser
What this does is
run libFuzzer on the
StunParser
target with 6 parallel instances using the corpus in thecorpus-stunparser
directory (with the specified libFuzzer options such as-max_len
and-use_value_profile
)automatically reduce the corpus and restart if it grew by 30% (and has at least 500 files)
use FuzzManager (need a local
.fuzzmanagerconf
and afirefox.fuzzmanagerconf
binary configuration as described in the FuzzManager manual) and submit crashes aslibfuzzer-stunparser
toolwrite statistics to the
libfuzzer-stunparser.stats
file
JS Engine Specifics¶
The fuzzing interface can also be used for testing the JS engine, in fact there are two separate options to implement and run fuzzing targets:
Implementing in C++¶
Similar to the fuzzing interface in Firefox, you can implement your target in entirely C++ with very similar interfaces compared to what was described before.
There are a few minor differences though:
All of the fuzzing targets live in js/src/fuzz-tests.
All of the code is linked into a separate binary called fuzz-tests, similar to how all JSAPI tests end up in jsapi-tests. In order for this binary to be built, you must build a JS shell with
--enable-fuzzing
and--enable-tests
. Again, this can and should be combined with AddressSanitizer for maximum effectiveness. This also means that there is no need to (re)build gtests when dealing with a JS fuzzing target and using a shell as part of a full browser build.The harness around the JS implementation already provides you with an initialized
JSContext
and global object. You can access these in your target by declaringextern JS::PersistentRootedObject gGlobal;
and
extern JSContext* gCx;
but there is no obligation for you to use these.
For a live example, see also the implementation of the StructuredCloneReader target.
Implementing in JS¶
In addition to the C++ targets, you can also implement targets in JavaScript
using the JavaScript Runtime (JSRT) fuzzing approach. Using this approach is
not only much simpler (since you don’t need to know anything about the
JSAPI or engine internals), but it also gives you full access to everything
defined in the JS shell, including handy functions such as timeout()
.
Of course, this approach also comes with disadvantages: Calling into JS and performing the fuzzing operations there costs performance. Also, there is more chance for causing global side-effects or non-determinism compared to a fairly isolated C++ target.
As a rule of thumb, you should implement the target in JS if
you don’t know C++ and/or how to use the JSAPI (after all, a JS fuzzing target is better than none),
your target is expected to have lots of hangs/timeouts (you can catch these internally),
or your target is not isolated enough for a C++ target and/or you need specific JS shell functions.
There is an example target in-tree that shows roughly how to implement such a fuzzing target.
To run such a target, you must run the js
(shell) binary instead of the
fuzz-tests
binary and point the FUZZER
variable to the file containing
your fuzzing target, e.g.
$ FUZZER=/path/to/jsrtfuzzing-example.js obj-asan/dist/bin/js --fuzzing-safe --no-threads -- <libFuzzer options here>
More elaborate targets can be found in js/src/fuzz-tests/.
Troubleshooting¶
Fuzzing Interface: Error: No testing callback found¶
This error means that the fuzzing callback with the name you specified
using the FUZZER
environment variable could not be found. Reasons
for are typically either a misspelled name or that your code wasn’t
built (check your moz.build
file and build log).
mach build
doesn’t seem to update my fuzzing code¶
Keep in mind you always need to run both the mach build
and
mach gtest dontruntests
commands in order to update your fuzzing
code. The latter rebuilds the gtest version of libxul
, containing
your code.