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diff --git a/tools/fuzzing/docs/index.rst b/tools/fuzzing/docs/index.rst new file mode 100644 index 0000000000..4be57b3be5 --- /dev/null +++ b/tools/fuzzing/docs/index.rst @@ -0,0 +1,434 @@ +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. |