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+Fuzzing
+=======
+
+.. toctree::
+  :maxdepth: 1
+  :hidden:
+  :glob:
+  :reversed:
+
+  *
+
+This section focuses on explaining the software testing technique called
+“Fuzzing” or “Fuzz Testing” and its application to the Mozilla codebase.
+The overall goal is to educate developers about the capabilities and
+usefulness of fuzzing and also allow them to write their own fuzzing
+targets. Note that not all fuzzing tools used at Mozilla are open
+source. Some tools are for internal use only because they can easily
+find critical security vulnerabilities.
+
+What is Fuzzing?
+----------------
+
+Fuzzing (or Fuzz Testing) is a technique to randomly use a program or
+parts of it with the goal to uncover bugs. Random usage can have a wide
+variety of forms, a few common ones are
+
+-  random input data (e.g. file formats, network data, source code, etc.)
+
+-  random API usage
+
+-  random UI interaction
+
+with the first two being the most practical methods used in the field.
+Of course, these methods are not entirely separate, combinations are
+possible. Fuzzing is a great way to find quality issues, some of them
+being also security issues.
+
+Random input data
+~~~~~~~~~~~~~~~~~
+
+This is probably the most obvious fuzzing method: You have code that
+processes data and you provide it with random or mutated data, hoping
+that it will uncover bugs in your implementation. Examples are media
+formats like JPEG or H.264, but basically anything that involves
+processing a “blob” of data can be a valuable target. Countless security
+vulnerabilities in a variety of libraries and programs have been found
+using this method (the AFLFuzz
+`bug-o-rama <http://lcamtuf.coredump.cx/afl/#bugs>`__ gives a good
+impression).
+
+Common tools for this task are e.g.
+`libFuzzer <https://llvm.org/docs/LibFuzzer.html>`__ and
+`AFLFuzz <http://lcamtuf.coredump.cx/afl/>`__, but also specialized
+tools with custom logic like
+`LangFuzz <https://www.usenix.org/system/files/conference/usenixsecurity12/sec12-final73.pdf>`__
+and `Avalanche <https://github.com/MozillaSecurity/avalanche>`__.
+
+Random API Usage
+~~~~~~~~~~~~~~~~
+
+Randomly testing APIs is especially helpful with parts of software that
+expose a well-defined interface (see also :ref:`Well-defined
+behavior and Safety`). If this interface is additionally exposed to
+untrusted parties/content, then this is a strong sign that random API
+testing would be worthwhile here, also for security reasons. APIs can be
+anything from C++ layer code to APIs offered in the browser.
+
+A good example for a fuzzing target here is the DOM (Document Object
+Model) and various other browser APIs. The browser exposes a variety of
+different APIs for working with documents, media, communication,
+storage, etc. with a growing complexity. Each of these APIs has
+potential bugs that can be uncovered with fuzzing. At Mozilla, we
+currently use domino (internal tool) for this purpose.
+
+Random UI Interaction
+~~~~~~~~~~~~~~~~~~~~~
+
+A third way to test programs and in particular user interfaces is by
+directly interacting with the UI in a random way, typically in
+combination with other actions the program has to perform. Imagine for
+example an automated browser that surfs through the web and randomly
+performs actions such as scrolling, zooming and clicking links. The nice
+thing about this approach is that you likely find many issues that the
+end-user also experiences. However, this approach typically suffers from
+bad reproducibility (see also :ref:`Reproducibility`) and is therefore
+often of limited use.
+
+An example for a fuzzing tool using this technique is `Android
+Monkey <https://developer.android.com/studio/test/monkey>`__. At
+Mozilla however, we currently don’t make much use of this approach.
+
+Why Fuzzing Helps You
+---------------------
+
+Understanding the value of fuzzing for you as a developer and software
+quality in general is important to justify the support this testing
+method might need from you. When your component is fuzzed for the first
+time there are two common things you will be confronted with:
+
+**Bug reports that don’t seem real bugs or not important:** Fuzzers
+find all sorts of bugs in various corners of your component, even
+obscure ones. This automatically leads to a larger number of bugs that
+either don’t seem to be bugs (see also the :ref:`Well-defined behavior and
+safety` section below) or that don’t seem to be important bugs.
+
+Fixing these bugs is still important for the fuzzers because ignoring them
+in fuzzing costs resources (performance, human resources) and might even
+prevent the fuzzer from hitting other bugs. For example certain fuzzing tools
+like libFuzzer run in-process and have to restart on every crash, involving a
+costly re-read of the fuzzing samples.
+
+Also, as some of our code evolves quickly, a corner case might become a
+hot code path in a few months.
+
+**New steps to reproduce:** Fuzzing tools are very likely to exercise
+your component using different methods than an average end-user. A
+common technique is modify existing parts of a program or write entirely
+new code to yield a fuzzing "target". This target is specifically
+designed to work with the fuzzing tools in use. Reproducing the reported
+bugs might require you to learn these new steps to reproduce, including
+building/acquiring that target and having the right environment.
+
+Both of these issues might seem like a waste of time in some cases,
+however, realizing that both steps are a one-time investment for a
+constant stream of valuable bug reports is paramount here. Helping your
+security engineers to overcome these issues will ensure that future
+regressions in your code can be detected at an earlier stage and in a
+form that is more easily actionable. Especially if you are dealing with
+regressions in your code already, fuzzing has the potential to make your
+job as a developer easier.
+
+One of the best examples at Mozilla is the JavaScript engine. The JS
+team has put great quite some effort into getting fuzzing started and
+supporting our work. Here’s what Jan de Mooij, a senior platform
+engineer for the JavaScript engine, has to say about it:
+
+*“Bugs in the engine can cause mysterious browser crashes and bugs that
+are incredibly hard to track down. Fortunately, we don't have to deal
+with these time consuming browser issues very often: usually the fuzzers
+find a reliable shell test long before the bug makes it into a release.
+Fuzzing is invaluable to us and I cannot imagine working on this project
+without it.”*
+
+Levels of Fuzzing in Firefox/Gecko
+----------------------------------
+
+Applying fuzzing to e.g. Firefox happens at different "levels", similar
+to the different types of automated tests we have:
+
+Full Browser Fuzzing
+~~~~~~~~~~~~~~~~~~~~
+
+The most obvious method of testing would be to test the full browser and
+doing so is required for certain features like the DOM and other APIs.
+The advantage here is that we have all the features of the browser
+available and testing happens closely to what we actually ship. The
+downside here though is that browser testing is by far the slowest of
+all testing methods. In addition, it has the most amount of
+non-determinism involved (resulting e.g. in intermittent testcases).
+Browser fuzzing at Mozilla is largely done with the `Grizzly
+framework <https://blog.mozilla.org/security/2019/07/10/grizzly/>`__
+(`meta bug <https://bugzilla.mozilla.org/show_bug.cgi?id=grizzly>`__)
+and one of the most successful fuzzers is the Domino tool (`meta
+bug <https://bugzilla.mozilla.org/show_bug.cgi?id=domino>`__).
+
+Summarizing, full browser fuzzing is the right technique to investigate
+if your feature really requires it. Consider using other methods (see
+below) if your code can be exercised in this way.
+
+The Fuzzing Interface
+~~~~~~~~~~~~~~~~~~~~~
+
+**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.
+
+This interface offers a gtest (C++ unit test) level component based
+fuzzing approach and is suitable for anything that could also be
+tested/exercised using a gtest. This method is by far the fastest, but
+usually limited to testing isolated components that can be instantiated
+on this level. Utilizing this method requires you to write a fuzzing
+target similar to writing a gtest. This target will automatically be
+usable with libFuzzer and AFLFuzz. We offer a :ref:`comprehensive manual <Fuzzing Interface>`
+that describes how to write and utilize your own target.
+
+A simple example here is the `SDP parser
+target <https://searchfox.org/mozilla-central/rev/efdf9bb55789ea782ae3a431bda6be74a87b041e/media/webrtc/signaling/fuzztest/sdp_parser_libfuzz.cpp#30>`__,
+which tests the SipccSdpParser in our codebase.
+
+Shell-based Fuzzing
+~~~~~~~~~~~~~~~~~~~
+
+Some of our fuzzing, e.g. JS Engine testing, happens in a separate shell
+program. For JS, this is the JS shell also used for most of the JS tests
+and development. In theory, xpcshell could also be used for testing but
+so far, there has not been a use case for this (most things that can be
+reached through xpcshell can also be tested on the gtest level).
+
+Identifying the right level of fuzzing is the first step towards
+continuous fuzz testing of your code.
+
+Code/Process Requirements for Fuzzing
+-------------------------------------
+
+In this section, we are going to discuss how code should be written in
+order to yield optimal results with fuzzing.
+
+Defect Oracles
+~~~~~~~~~~~~~~
+
+Fuzzing is only effective if you are able to know when a problem has
+been found. Crashes are typically problems if the unit being tested is
+safe for fuzzing (see Well-defined behavior and Safety). But there are
+many more problems that you would want to find, correctness issues,
+corruptions that don’t necessarily crash etc. For this, you need an
+*oracle* that tells you something is wrong.
+
+The simplest defect oracle is the assertion (ex: ``MOZ_ASSERT``).
+Assertions are a very powerful instrument because they can be used to
+determine if your program is performing correctly, even if the bug would
+not lead to any sort of crash. They can encode arbitrarily complex
+information about what is considered correct, information that might
+otherwise only exist in the developers’ minds.
+
+External tools like the sanitizers (AddressSanitizer aka ASan,
+ThreadSanitizer aka TSan, MemorySanitizer aka MSan and
+UndefinedBehaviorSanitizer - UBSan) can also serve as oracles for
+sometimes severe issues that would not necessarily crash. Making sure
+that these tools can be used on your code is highly useful.
+
+Examples for bugs found with sanitizers are `bug
+1419608 <https://bugzilla.mozilla.org/show_bug.cgi?id=1419608>`__,
+`bug 1580288 <https://bugzilla.mozilla.org/show_bug.cgi?id=1580288>`__
+and `bug 922603 <https://bugzilla.mozilla.org/show_bug.cgi?id=922603>`__,
+but since we started using sanitizers, we have found over 1000 bugs with
+these tools.
+
+Another defect oracle can be a reference implementation. Comparing
+program behavior (typically output) between two programs or two modes of
+the same program that should produce the same outputs can find complex
+correctness issues. This method is often called differential testing.
+
+One example where this is regularly used to find issues is the Mozilla
+JavaScript engine: Running random programs with and without JIT
+compilation enabled finds lots of problems with the JIT implementation.
+One example for such a bug is `Bug
+1404636 <https://bugzilla.mozilla.org/show_bug.cgi?id=1404636>`__.
+
+Component Decoupling
+~~~~~~~~~~~~~~~~~~~~
+
+Being able to test components in isolation can be an advantage for
+fuzzing (both for performance and reproducibility). Clear boundaries
+between different components and documentation that explains the
+contracts usually help with this goal. Sometimes it might be useful to
+mock a certain component that the target component is interacting with
+and that is much harder if the components are tightly coupled and their
+contracts unclear. Of course, this does not mean that one should only
+test components in isolation. Sometimes, testing the interaction between
+them is even desirable and does not hurt performance at all.
+
+Avoiding external I/O
+~~~~~~~~~~~~~~~~~~~~~
+
+External I/O like network or file interactions are bad for performance
+and can introduce additional non-determinism. Providing interfaces to
+process data directly from memory instead is usually much more helpful.
+
+Well-defined Behavior and Safety
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+This requirement mostly ties in where defect oracles ended and is one of
+the most important problems seen in the wild nowadays with fuzzing. If a
+part of your program’s behavior is unspecified, then this potentially
+leads to bad times if the behavior is considered a defect by fuzzing.
+For example, if your code has crashes that are not considered bugs, then
+your code might be unsuitable for fuzzing. Your component should be
+fuzzing safe, meaning that any defect oracle (e.g. assertion or crash)
+triggered by the fuzzer is considered a bug. This important aspect is
+often neglected. Be aware that any false positives cause both
+performance degradation and additional manual work for your fuzzing
+team. The Mozilla JS developers for example have implemented this
+concept in a “--fuzzing-safe” switch which disables harmful functions.
+Sometimes, crashes cannot be avoided for handling certain error
+conditions. In such situations, it is important to mark these crashes in
+a way the fuzzer can recognize and distinguish them from undesired
+crashes. However, keep in mind that crashes in general can be disruptive
+to the fuzzing process. Performance is an important aspect of fuzzing
+and frequent crashes can severely degrade performance.
+
+Reproducibility
+~~~~~~~~~~~~~~~
+
+Being able to reproduce issues found with fuzzing is necessary for
+several reasons: First, you as the developer probably want a test that
+reproduces the issue so you can debug it better. Our feedback from most
+developers is that traces without a reproducible test can help to find a
+problem, but it makes the whole process very complicated. Some of these
+non-reproducible bugs never get fixed. Second, having a reproducible
+test also helps the triage process by allowing an automated bisection to
+find the responsible developer. Last but not least, the test can be
+added to a test suite, used for automated verification of fixes and even
+serve as a basis for more fuzzing.
+
+Adding functionality to the program that improve reproducibility is
+therefore a good idea in case non-reproducible issues are found. Some
+examples are shown in the next section.
+
+While many problems with reproducibility are specific for the project
+you are working on, there is one source of these problems that many
+programs have in common: Threading. While some bugs only occur in the
+first place due to concurrency, some other bugs would be perfectly
+reproducible without threads, but are intermittent and hard to with
+threading enabled. If the bug is indeed caused by a data race, then
+tools like ThreadSanitizer will help and we are currently working on
+making ThreadSanitizer usable on Firefox. For bugs that are not caused
+by threading, it sometimes makes sense to be able to disable threading
+or limit the amount of worker threads involved.
+
+Supporting Code
+~~~~~~~~~~~~~~~
+
+Some possibilities of what support implementations for fuzzing can do
+have already been named in the previous sections: Additional defect
+oracles and functionality to improve reproducibility and safety. In
+fact, many features added specifically for fuzzing fit into one of these
+categories. However, there’s room for more: Often, there are ways to
+make it easier for fuzzers to exercise complex and hard to reach parts
+of your code. For example, if a certain optimization feature is only
+turned on under very specific conditions (that are not a requirement for
+the optimization), then it makes sense to add a functionality to force
+it on. Then, a fuzzer can hit the optimization code much more
+frequently, increasing the chance to find issues. Some examples from
+Firefox and SpiderMonkey:
+
+- The `FuzzingFunctions <https://searchfox.org/mozilla-central/rev/efdf9bb55789ea782ae3a431bda6be74a87b041e/dom/webidl/FuzzingFunctions.webidl#15>`__
+  interface in the browser allows fuzzing tools to perform GC/CC, tune various
+  settings related to garbage collection or enable features like accessibility
+  mode. Being able to force a garbage collection at a specific time helped
+  identifying lots of problems in the past.
+
+- The --ion-eager and --baseline-eager flags for the JS shell force JIT
+  compilation at various stages, rather than using the builtin
+  heuristic to enable it only for hot functions.
+
+- The --no-threads flag disables all threading (if possible) in the JS shell.
+  This makes some bugs reproduce deterministically that would otherwise be
+  intermittent and harder to find. However, some bugs that only occur with
+  threading can’t be found with this option enabled.
+
+Another important feature that must be turned off for fuzzing is
+checksums. Many file formats use checksums to validate a file before
+processing it. If a checksum feature is still enabled, fuzzers are
+likely never going to produce valid files. The same often holds for
+cryptographic signatures. Being able to turn off the validation of these
+features as part of a fuzzing switch is extremely helpful.
+
+An example for such a checksum can be found in the
+`FlacDemuxer <https://searchfox.org/mozilla-central/rev/efdf9bb55789ea782ae3a431bda6be74a87b041e/dom/media/flac/FlacDemuxer.cpp#494>`__.
+
+Test Samples
+~~~~~~~~~~~~
+
+Some fuzzing strategies make use of existing data that is mutated to
+produce the new random data. In fact, mutation-based strategies are
+typically superior to others if the original samples are of good quality
+because the originals carry a lot of semantics that the fuzzer does not
+have to know about or implement. However, success here really stands and
+falls with the quality of the samples. If the originals don’t cover
+certain parts of the implementation, then the fuzzer will also have to
+do more work to get there.
+
+
+Fuzz Blockers
+~~~~~~~~~~~~~
+
+Fuzz blockers are issues that prevent fuzzers from being as
+effective as possible. Depending on the fuzzer and its scope a fuzz blocker
+in one area (or component) can impede performance in other areas and in
+some cases block the fuzzer all together. Some examples are:
+
+- Frequent crashes - These can block code paths and waste compute
+  resources due to the need to relaunch the fuzzing target and handle
+  the results (regardless of whether it is ignored or reported). This can also
+  include assertions that are mostly benign in many cases are but easily
+  triggered by fuzzers.
+
+- Frequent hangs / timeouts - This includes any issue that slows down
+  or blocks execution of the fuzzer or the target.
+
+- Hard to bucket - This includes crashes such as stack overflows or any issue
+  that crashes in an inconsistent location. This also includes issues that
+  corrupt logs/debugger output or provide a broken/invalid crash report.
+
+- Broken builds - This is fairly straightforward, without up-to-date builds
+  fuzzers are unable to run or verify fixes. 
+
+- Missing instrumentation - In some cases tools such as ASan are used as
+  defect oracles and are required by the fuzzing tools to allow for proper
+  automation. In other cases incomplete instrumentation can give a false sense
+  of stability or make investigating issues much more time consuming. Although
+  this is not necessarily blocking the fuzzers it should be prioritized
+  appropriately.
+
+Since these types of crashes harm the overall fuzzing progress, it is important
+for them to be addressed in a timely manner. Even if the bug itself might seem
+trivial and low priority for the product, it can still have devastating effects
+on fuzzing and hence prevent finding other critical issues. 
+
+Issues in Bugzilla are marked as fuzz blockers by adding “[fuzzblocker]”
+to the “Whiteboard” field. A list of open issues marked as fuzz blockers
+can be found on `Bugzilla <https://bugzilla.mozilla.org/buglist.cgi?cmdtype=dorem&remaction=run&namedcmd=fuzzblockers&sharer_id=486634>`__.
+
+
+Documentation
+~~~~~~~~~~~~~
+
+It is important for the fuzzing team to know how your software, tests
+and designs work. Even obvious tasks, like how a test program is
+supposed to be invoked, which options are safe, etc. might be hard to
+figure out for the person doing the testing, just as you are reading
+this manual right now to find out what is important in fuzzing.
+
+Contact Us
+~~~~~~~~~~
+
+The fuzzing team can be reached at
+`fuzzing@mozilla.com <mailto:fuzzing@mozilla.com>`__ or
+`on Matrix <https://chat.mozilla.org/#/room/#fuzzing:mozilla.org>`__
+and will be happy to help you with any questions about fuzzing
+you might have. We can help you find the right method of fuzzing for
+your feature, collaborate on the implementation and provide the
+infrastructure to run it and process the results accordingly.