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Now, we cleanly `sys.exit(1)` instead. + +## 22.10.1 +First open-source release! Also improves database handling and adds +a timelimit to shrinking to better handle pathological cases. + +## 22.07.1 +Fixes compatibility with [Hypothesis 6.49.1](https://hypothesis.readthedocs.io/en/latest/changes.html#v6-49-1) +and later (released July 5th). + +## 21.12.2 +Web-based time-travel debugging with [PyTrace](https://pytrace.com/) - just +`pip install hypofuzz[pytrace]` and click the link on any failing test! + +## 21.12.1 +Improved dashboard (again!), better generation/mutation heuristics, +basic residual-risk estimation, free-for-noncommercial-use on PyPI. + +## 21.05.1 +Improved dashboard, fixed memory leaks, support arbitary `hypothesis.event()` +calls as coverage, performance improvements. + +## 20.09.1 +Multiprocess fuzzing with seed sharing and corpus distillation, +and basic prioritisation of seeds covering rare branches. + +Still very much in alpha, but the fundamentals all work now. + +## 20.08.1 +First packaged version of HypoFuzz diff --git a/docs/docs/_sources/configuration.rst.txt b/docs/docs/_sources/configuration.rst.txt new file mode 100644 index 0000000..87baf9f --- /dev/null +++ b/docs/docs/_sources/configuration.rst.txt @@ -0,0 +1,61 @@ +Configuration +============= + +.. contents:: + :local: + + +It's all automatic +------------------ + +Wherever possible, HypoFuzz is designed to do the right thing without configuration. + +The :command:`hypothesis fuzz` CLI accepts arguments to determine parameters like the +number of processes to use, and the port on which to serve the dashboard - +though every one of them is optional - and you can select which tests to fuzz +in the same way you would select them via :pypi:`pytest`. + +Once that's all set up though, the fuzzer is not configurable: manual prioritization +of a fuzzing process is considerably more error-prone than allowing the adaptive +scheduler to do its thing, and computer time is much cheaper than yours. + + + +Custom coverage events +---------------------- + +HypoFuzz runs :pypi:`coverage` on every input to observe the branch coverage of your +code - but we know that there are many things code can do that aren't captured by +the set of executed branches. `This blog post +`__ +gives a good overview of coverage-driven verification workflows. + +We therefore treat each :func:`hypothesis.event` as a "virtual" branch - while it's +not part of the control-flow graph, we keep track of inputs which produced each +observed event in the same way that we track the inputs which produce each branch. + +You can therefore use the :func:`~hypothesis.event` function in your tests to +mark out categories of behaviour, boundary conditions, and so on, and then let the +fuzzer exploit that to generate more diverse and better-targeted inputs. +And as a bonus, you'll get useful summary statistics when running Hypothesis! + + + +The Hypothesis database +----------------------- + +The Hypothesis database forms the basis of HypoFuzz workflows: failing examples +can be reproduced automatically just by running the tests - because those inputs +are added to the database and replayed by Hypothesis itself. + +It is therefore critical that the fuzzer is using the *same* database as +Hypothesis - regardless of how or where you run it. + +:hydocs:`Hypothesis' default database ` is designed to persist +failing examples on a single developer's machine, and does so via the filesystem. +If you want to share the database between your team members and your CI server +though, this isn't going to work so well - either set the +:obj:`~hypothesis:hypothesis.settings.database` setting to an +:class:`~hypothesis:hypothesis.database.ExampleDatabase` backed by a network +datastore, or use a :class:`~hypothesis:hypothesis.database.DirectoryBasedExampleDatabase` +pointed to a shared filesystem. diff --git a/docs/docs/_sources/features.rst.txt b/docs/docs/_sources/features.rst.txt new file mode 100644 index 0000000..62f8824 --- /dev/null +++ b/docs/docs/_sources/features.rst.txt @@ -0,0 +1,109 @@ +Features +======== + +The core principle of HypoFuzz is that it should be effortless to adopt: +if you have Hypothesis tests, everything else is automatic. If you're +curious about what that "everything else" involves, this page is for you. + +.. contents:: + :local: + + +Collecting tests +---------------- + +HypoFuzz uses :pypi:`pytest` to collect the test functions to fuzz, +with almost identical command-line interfaces. If you're using +:command:`pytest ...` to run your tests, :command:`hypothesis fuzz -- ...` +will fuzz them. + +Note that tests which use `pytest fixtures `__, +including ``autouse`` fixtures, are not collected as they may behave +differently outside of the pytest runtime. We recommend using a context +manager and the ``with`` statement instead. + +Support for other test runners, such as :mod:`python:unittest`, +is :doc:`on our roadmap `. + + +Execution model +--------------- + +HypoFuzz runs as one or more worker processes, by default one per available +core, and an additional process serving the live dashboard as a website. + +In each worker process, HypoFuzz prioritizes tests which discover new coverage, +which maximises the rate of discovery and therefore minimises the time taken +to cover each branch in your code. This adaptive approach is one of HypoFuzz's +advantages over other fuzzing workflows - and the reason you can apply it to +a whole test suite at a time. + + +HypoFuzz dashboard +------------------ + +The HypoFuzz dashboard - `online demo here <../../example-dashboard/>`__ - shows +the current state of the fuzzing campaign overall, with a sub-page for each test +to show more information. + + +Fuzzer details +-------------- + +HypoFuzz is, compared to other fuzzers in the literature, a bizzare mixture of +every technique that seems to work. Instead of being based on "one brilliant +idea" (oversimplifying, AFL = "coverage-guided mutation", :cite:`AFLFast` += "bias towards rare branches", etc.), we have a single simple goal: +*fuzzing your property-based test suite should be effortless*. + +Because HypoFuzz is designed to exploit features that already exist in Hypothesis, +you *can* write tests which are designed to be fuzzed, but idiomatic ``@given`` +tests already work just fine. + + +Basic design +~~~~~~~~~~~~ + +It's a standard feedback-directed greybox fuzzer. The interesting parts are + +1. HypoFuzz tests Python code, not native executables +2. we exploit property-based tests to detect semantic bugs, not just crashes +3. we use Hypothesis to generate highly-structured and typically valid data +4. we leverage a wider variety of feedbacks than most fuzzers +5. we fuzz *very many* more targets than most fuzzing campaigns + + +Corpus distillation +~~~~~~~~~~~~~~~~~~~ + +We exploit Hypothesis' world-class test-case reduction logic ("shrinking") to +maintain a seed pool of minimal covering examples for each branch - or other +reason to retain a seed. + +Those other reasons include user-defined labels via :func:`hypothesis:hypothesis.event`, +real-valued metrics with :func:`hypothesis:hypothesis.target`, +and more to come. + + +Mutation logic +~~~~~~~~~~~~~~ + +The mutation logic is minimum-viable at the moment. It works shockingly well, +thanks to Hypothesis' input structure, but substantial improvements are on the +roadmap. + + +Ensemble fuzzing +~~~~~~~~~~~~~~~~ + +HypoFuzz natively supports ensemble fuzzing :cite:`EnFuzz`, by periodically loading +any new examples from the database. This works in ``--unsafe`` mode, where each +test function might run in multiple fuzzer processes at the same time, and with +other fuzzer tools leveraging e.g. the `.hypothesis.fuzz_one_input +`__ +hook. + +Ensemble fuzzing can also be modelled as a mixture of the ensembled behaviours, +and HypoFuzz therefore attempts to run an *adaptive* mixture of all the useful +behaviours we can implement. To the extent that this works, we get the benefits +of ensembling and consume the minimum possible resources to required to do so. diff --git a/docs/docs/_sources/index.rst.txt b/docs/docs/_sources/index.rst.txt new file mode 100644 index 0000000..777153b --- /dev/null +++ b/docs/docs/_sources/index.rst.txt @@ -0,0 +1,23 @@ +HypoFuzz documentation +====================== + +:pypi:`Hypothesis` is free and open-source software, and always will be. +It's proven itself invaluable for everyone - from students to high-school +teachers, astrophysicists to data scientists, web developers to systems +programmers, and even for hardware designers. + +HypoFuzz builds on that success: if you have Hypothesis tests, HypoFuzz +gives you a fantastic way to spend CPU time - instead of engineering time - +to find bugs early in your development cycle. + + +.. toctree:: + :maxdepth: 2 + + Main website + quickstart + features + configuration + roadmap + literature + changelog diff --git a/docs/docs/_sources/literature.rst.txt b/docs/docs/_sources/literature.rst.txt new file mode 100644 index 0000000..d4aa37e --- /dev/null +++ b/docs/docs/_sources/literature.rst.txt @@ -0,0 +1,674 @@ +Summary of related research +=========================== + +HypoFuzz is built on, and inspired by, a wide range of research and practice +in software testing and verification. This page summarises and comments on +selected parts of that literature, focussing on papers which are in some sense +prior art for fuzzing property-based tests for Python. + +.. tip:: + + `See HypoFuzz in action here! <../example-dashboard/>`__ + +.. contents:: + :local: + + +Fuzzing background +------------------ + +Fuzzers can generally be divided into two categories: + +1. *Generational* fuzzers generate new inputs from scratch, using a random number + generator to choose various options. This covers everything from the simplest + use of random numbers in a unit test, to highly sophisticated tools like + CSmith :cite:`CSmith`. + +2. *Mutational* fuzzers derive new inputs by mutating known inputs, and adding + interesting examples to the 'pool' of known inputs. Greybox mutational fuzzers + reliabily find security vulnerabilities in almost any previously-unfuzzed C code, + but are only rarely applied to search for semantic or non-security bugs. + +Hypothesis takes a hybrid approach, using (mostly) generational fuzzing to find +failing examples, and then mutating and replaying an internal representation +to find the minimal failing example. +HypoFuzz takes a smarter approach by exploiting mutation-based example generation, +running a variety of instrumentation which is too expensive for sub-second unit +tests, and adapting the fuzzing logic to each test function as it learns. +More on this below. + +*The Fuzzing Book* :cite:`fuzzingbook2019` is a fantastic introduction to +and overview of the field. While many of the papers cited below may not be +relevant unless you're *implementing* a fuzzer like HypoFuzz, the book is +a great resource for anyone involved in software testing. + + +Fuzz / Fuzz Revisited / Fuzz 2020 +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +`Bart Miller's pioneering work on fuzzing `__ +defined the field, and proved that unguided random fuzzing works scarily well. +From 1990 :cite:`Fuzz1990` to 1995 :cite:`FuzzRevisited`, and again in 2020 :cite:`Fuzz2020`, +the persistence of bugs which can be caught by such simple tools seems timeless. +Unfortunately, so does the very slow adoption of such tools - if you're reading +this sentence, you have unusual (and excellent!) taste in testing technologies. + + +AFL (classic) +~~~~~~~~~~~~~ + +`Pulling JPEGs out of thin air +`__ made +a splash: `AFL `__ was the first fuzzer tool +to reach mainstream awareness, and its success - measured in important bugs rather +than citations or benchmarks - revitalised the field. + +The key insights were that lightweight instrumentation for coverage guided fuzzing +would often outperform fancier but slower techniques, and that usability counts - +with almost no configuration and a robust design applicable to any project, +AFL saw much wider adoption and therefore impact than previous tools. + +Since 2017, `AFL++ has been maintained by the community `__ +:cite:`AFL++` with a variety of bugfixes, patches, and additional features - many of +which are covered below. + + +LibFuzzer +~~~~~~~~~ + +`LibFuzzer `__ targets functions, rather than +whole binaries, and typically runs in-process. +:hydocs:`Hypothesis' .fuzz_one_input ` +function is directly inspired by the ``LLVMFuzzOneInput`` entry point, though +Hypothesis tests have much more sophisticated support for `structured fuzzing +`__. + + + +Property-based testing +---------------------- + +It's common to observe that property-based testing (PBT) is conceptually +related to fuzzing - see for example Dan Luu's `AFL + QuickCheck = ? +`__ or Nelson Elhage's `Property-Based Testing Is Fuzzing +`__ and +`Property Testing Like AFL `__. +For an essay on the *differences*, see David MacIver's `What is Property-Based Testing +`__. + +The core of Hypothesis in in fact a blackbox structure-aware fuzzer, +and of course HypoFuzz itself is a greybox fuzzer built on our shared +IR layer. Three things make HypoFuzz different from tradional fuzzers. + +1. HypoFuzz is designed to work with many more targets than most fuzzers - + we operate on *test suites*, not single binaries. +2. Because we're fuzzing property-based tests, HypoFuzz looks for semantics + errors - not just crashes - and can check properties that are only expected + to hold for a subset of valid inputs. +3. It's designed to fit into your development cycle, and be used by developers - + so that the bugs get caught *before* the code ships. + +Hypothesis +~~~~~~~~~~ + +Hypothesis :cite:`MacIver2019` is implemented around a bytestring representation for all +test cases. All "strategies" (data generators) can transparently +generate random instances via a PRNG, or replay past test-cases by +substituting a recorded bytestring for the PRNG stream. + +:cite:`MacIver2020` goes into more depth about the design of this IR layer, +and in particular how it enables efficient test-case reduction and normalisation. +This is the key to reporting minimal and de-duplicated failing examples, and +makes using a fuzzer much more productive (and less frustrating). + +The IR layer has also proven invaluable as a clean and universal interface +to support other techniques such as targeted property-based testing +:cite:`TargetedPBT` - we get to automate (:cite:`AutomatingTargetedPBT`) +the setup for free, and support multi-dimensional optimisation into the +bargain. See :func:`hypothesis:hypothesis.target` for details. + + +'Fuzzer taming' with test-case reduction +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +Because Hypothesis presents a single `reduced +`__ and normalised +:cite:`OneTestToRuleThemAll` failing input for each unique exception type and location, +HypoFuzz largely avoids the `fuzzer taming problem `__ +:cite:`TamingCompilerFuzzers`. + + +'Strategies' are parser-combinators designed for structured fuzzing +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +Hypothesis users specify the allowed inputs to their test function by composing +"strategies", which are internally used to parse PRNG or replayed bytestrings +into valid data. Users may compose strategies with arbitrary code, including code +under test, but while in principle this leads to an unrestricted grammar the +structure is usually tractable (`see here for some details +`__). + +Strategies are also designed such that, in the absence of user-defined filters, +most random bytestrings can be parsed into valid examples - which makes it easy +to support a hybrid generational/mutational fuzzer. + +Some also use `swarm testing `__ +:cite:`SwarmTesting`, which improves the diversity of "weird" examples generated +without any user interaction at all. Increasing our usage of this and +`other techniques `__ is an ongoing +project for Hypothesis. + + +Other property-based fuzzers +~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +(Java) junit-quickcheck + JQF + Zest + RLCheck +++++++++++++++++++++++++++++++++++++++++++++++ + +Starting with the ``junit-quickcheck`` library, `JQF `__ +:cite:`JQF` provides an interface to run property-based tests with a variety of fuzzing +backends including AFL, Zest :cite:`Zest` (adding validity metrics), and PerfFuzz. + +`RLCheck `__ :cite:`RLCheck` is distinctive +as a blackbox fuzzer, using reinforcement learning to generate valid inputs according +to some predicate. While expressing constraints as predicates on a more general +input description is more natural for users, most PBT libraries require a constructive +approach to generation for acceptable performance - even when seriously unintuitive. + + +(Rust) proptest + propfuzz + propverify ++++++++++++++++++++++++++++++++++++++++ + +The `proptest `__ library for Rust is directly +inspired by Hypothesis. Showing the power of a good intermediate representation, +recent tools have attempted to build on top of this to provide both `fuzzing +`__ and `formal verification +`__ with (almost) the same +user-facing API. + +There are `plans for Hypothesis to support symbolic execution via +`__ :pypi:`crosshair-tool`, +and a promising proof-of-concept, but no firm timeline unless someone volunteers to +take on the project. + + +(C / C++) TrailofBits' DeepState, Google's ``fuzztest`` ++++++++++++++++++++++++++++++++++++++++++++++++++++++++ + +`DeepState `__ :cite:`DeepState` provides +a common interface to various symbolic execution and fuzzing engines - write your +tests once with a Google Test-style API, and then run them with a variety of backends +and at various stages of your development cycle. + +Google's `fuzztest `__ library is described as +a tool that bridges the gap between fuzzing and property-based testing, allowing you +to write fuzz test side by side with regular unit tests. ``fuzztest`` always runs +with coverage guidance, but is designed to be used as part of a testing (rather than +standard fuzzing) workflow. + + +(Haskell) QuickFuzz ++++++++++++++++++++ + +QuickFuzz :cite:`QuickFuzz` uses the venerable QuickCheck :cite:`QuickCheck` and +file format parsers from `Hackage `__ to implement +an unguided generational fuzzer. + + +(Coq) FuzzChick ++++++++++++++++ + +FuzzChick :cite:`FuzzChick` is a coverage-guided backed for QuickChick :cite:`QuickChick`, +a property-based testing library for the `Coq `__ +theorem prover. + + +Mutation operators +------------------ + +Structure-aware mutation with AFLSmart +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +AFLSmart :cite:`AFLSmart` proposes using "smart mutation operators", specifically +adding, deleting, or replacing chunks of one seed input with corresponding chunks +of another input. They find that this is a substantial improvement over +structure-naive converage-guided fuzzing, and that (as you'd expect) adding +feedback offers a very large improvement over blackbox generational fuzzing. + +While they use `"Peach pits" `__ +to define the input grammar - and as the blackbox baseline - we can get the same +structural information directly from instrumentation in the Hypothesis internals +without any additional work for users or implementors. +Doing so will also give Hypothesis `better ways to explain why your test failed +`__ essentially for free. + +Note that *structure-aware mutation* is a different technique to what is often +called *structure-aware fuzzing* (e.g. `here +`__) +- the latter is simply a parsing step to allow e.g. classic AFL to operate on +structured data, and Hypothesis gives us a well-tuned version of that for free. + + +Adaptive mutation operator selection +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +`MOpt-AFL `__ :cite:`MOpt-AFL` finds that +the effectiveness of mutation strategies varies by target, and evaluates an adaptive +particle-swarm algorithm to customise the mutation logic accordingly. + +:cite:`OneFuzzingStrategyToRuleThemAll` study "Havoc" mode, in which multiple +randomly-selected mutation operators are applied in a single step. They find that +this typically outperforms a one-operator-at-a-time approach, and that dynamically +tuning the operator weights with a (non-stationary) multi-arm-bandit approach yields +further large improvements. + +TOFU :cite:`TOFU` varies the weighting of mutation operators with distance to the +goal; preferring large (add, delete, splice, etc.) operations while distant and small +(e.g. bitflip) when closer. + + +Inputs from Hell +~~~~~~~~~~~~~~~~ + +:cite:`InputsFromHell` generates inputs matching a grammar, with a twist: by observing +the frequency with which various generation choices appear in a sample, you can +*invert* this distribution to instead generate dissimilar inputs. While partly +subsumed by rare-branch-targeting tricks (under scheduling inputs, below), this trick +might also have some synergistic effects. + + + +Scheduling inputs +----------------- + +AFLFast, FairFuzz, and AlphaFuzz +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +AFLFast :cite:`AFLFast` and FairFuzz :cite:`FairFuzz` observe that some branches +are covered by a higher proportion of inputs than others - for example, code which +rejects invalid inputs is usually overrepresented. + +When AFL-Fast selects an input to mutate, it biases the choice towards inputs which +execute rare branches - and finds both an order-of-magnitude performance improvement +and more bugs than previous approaches. Technically, the trick is to represent +the probability of covering each branch from a random mutation of each input as a +Markov chain, and then using the inverse of the stationary distribution as our +choice weights. + +AlphaFuzz :cite:`AlphaFuzz` observes that because mutation operators tend to make +local changes, modelling the lineage of each seed (again, as a Markov chain) further +improves on AFL-Fast by accounting for semantic diversity among seeds that reach +the same set of branches. However, I doubt this would help HypoFuzz, given our +larger mutation steps and strong reduction and normalization of seeds. + +FairFuzz shares the goal of increasing coverage of rare branches, but does so by +detecting regions of the input which may be required to do so and disabling +mutations of those regions. Their evaluation finds that this noticeably improves +coverage on code with deeply nested conditionals, against a baseline which includes +an early version of AFL-Fast (``-explore`` schedule added in 2.33, evaulation uses +2.40, ``-fast`` schedule seems to be best). + + +Directed fuzzing +~~~~~~~~~~~~~~~~ + +A `directed fuzzer `__, +such as `AFL-go `__ :cite:`AFLgo`, prioritizes inputs +which are 'closer' to a target location. This can be used to focus on recently-changed +code paths, areas flagged as bug-prone by static analysis, functions seen in logged +errors to reproduce a crash, etc. +TOFU :cite:`TOFU` also exploits input structure, and claims that this is substantially +responsible for it's -40% improvement over AFL-go. +:cite:`wang2020sok` survey the state-of-the-art in directed greybox fuzzing as of mid-2020. + +HypoFuzz could get the control-flow graph from coverage.py, which tracks possible branches +in order to report un-covered branches, so the implementation is straightforward. +The tradeoff between simplicity and power-requiring-configuration is less obvious; +we're inclined to initially stick to zero-config direction towards recent patches and/or +lines flagged by e.g. :pypi:`flake8`; though the balance between directed and general +exploration might take some tuning. + +Directed swarm testing :cite:`DirectedSwarmTesting` takes a slightly different approach: +it is assumed that *some* randomly generated test cases will execute the target code, +and so the goal is to increase that proportion by biasing the swarm configuration +towards including 'trigger' features and omitting 'suppressors'. + +SyML :cite:`SyMLPatternLearning` learn patterns among vulnerability-triggering paths +in known-buggy programs, and find that the learned features are predictive in unrelated +programs. Originally motivated by mitigating path explosion in symbolic execution, it +seems equally applicable to directed fuzzing and could be a substantial advantage for +a centralized platform where there are more programs (and bugs) to learn from. + + +Predictive fuzzing, scaling laws, & when to stop +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +`Dr. Marcel Böhme `__ has done groundbreaking work +characterising the behaviour of fuzzers (as well as co-creating AFLfast, AFLsmart, +and AFLgo!), in order to understand the assurances that fuzzing can provide and +quantify the residual risk :cite:`AssuranceInTestingRoadmap`. + +`Pythia `__ :cite:`STADS` adds statistical predictions +to AFL, including bounds on the probability of finding a bug, estimated progress towards +maximal coverage, and a difficulty metric. These metrics are obviously of interest +to users, and can also be used to schedule those targets with the highest expected +value - maximising the overall rate of progress. + +Applying this scheduling insight to seeds rather than targets yields Entropic +:cite:`Entropic`, which prioritizes those seeds +which maximise the rate of discovery of new information about the behaviour of the +fuzzed program. This shows `substantial improvement over baseline LibFuzzer +`__, and is now heavily used +by `OSS-Fuzz `__. + +Finally, :cite:`ExponentialCost` describes empirical scaling laws for fuzzers - +spending more CPU time finds a given set of bugs or coverage proportionally faster, +but finding *new* or *additional* bugs or coverage requires exponentially more +computation. This means that spending a little effort on very many targets is +often worthwhile, but simply throwing more compute at a given target is eventually +of limited value. On the other hand, improving the fuzzer or diversifing its +behaviour is correspondingly very valuable for well-fuzzed targets! + + + +Seed selection +-------------- + +Corpus distillation +~~~~~~~~~~~~~~~~~~~ + +Corpus distillation refers to the technique of selecting an appropriately minimal +subset of a large initial corpus which covers the same set of branches in the code +under test (``afl-cmin``, if you've used that). While traditionally defined only +for coverage, this is trivially extensible to other metrics - just ensure that there +are no discarded inputs which would be kept if freshly discovered by the fuzzer. + +:cite:`Moonlight` evaluates a variety of approaches to designing input corpora, +given a typically much larger initial corpus (which might be `scraped from the internet +`__ or created with +a generative fuzzer), and finds that minimising both the number of inputs in the +seed pool and their cumulative size improves fuzzer performance - and that no +single approach dominates the others. + +Reducing (:cite:`DeltaDebugging` or ``afl-tmin``) and normalising +(:cite:`OneTestToRuleThemAll`) failing test-cases is a well-known as technique +to assist in debugging, and supported - often called *shrinking* - by all good +property-based testing tools. HypoFuzz uses Hypothesis' world-class test case +reduction to calculate the minimal example for each feature of interest - covered +branch, high score from :func:`hypothesis:hypothesis.target`, etc. - and uses +this as a basis for further fuzzing as well as reporting failing examples. + +We are unaware of previous work which uses this approach or evaluates it in +comparison to less-intensive distillation. We expect that it works very well +if-and-only-if combined with generative and structure-aware fuzzing, to allow +for exploitation of the covering structure without unduly standardising +unrelated parts of the input. + + +Nezha - efficient differential testing +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +`Nezha `__ :cite:`Nezha` provides efficient +differential testing, by taking the product of the coverage for each input fed +to multiple targets. + +While the original AFL docs observed that a distilled corpus from one e.g. jpeg +library would often trigger bugs in another, as branches to handle edge cases select +for edge-case inputs which may be mishandled by the other, using joint instead of +independent coverage has similar advantages to that of ensemble fuzzing. + +This is relatively easy to implement using :pypi:`coverage` dynamic contexts and +a context manager or decorator API *within a given process*; while we'd also like +to support differential coverage between Python versions or operating systems +that will require some deeper changes to HypoFuzz's execution model. + + +Domain-specific targets with FuzzFactory +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +`FuzzFactory `__ :cite:`FuzzFactory` +observes that coverage may not be the only metric of interest, and extends the feedback +mechanism in AFL to support user-specified labels. + +This essentially brings targeted property-based testing (above) to fuzzing workflows, +and provides prior art (outside Hypothesis' implementation) of the multi-objective +approach - finding that this is often much more effective than optimising component +metrics independently. + + +Virtual branches with IJON +~~~~~~~~~~~~~~~~~~~~~~~~~~ + +`IJON `__ :cite:`IJON` adds custom feedback to +AFL. The ``IJON_SET`` macro adds a 'virtual branch' based on the value passed, so +that at least one input exhibiting whatever custom behaviour will be retained in +the seed pool (HypoFuzz implements this with the :func:`hypothesis:hypothesis.event` +function). The ``IJON_MAX`` macro is equivalent to :func:`hypothesis:hypothesis.target`, +similar to FuzzFactory above. + +IJON is particularly notable for winning 29 out of 32 *Super Mario Bros* levels, +a feat more typical of dedicated reinforcement learning systems, as well as +fuzzing a Trusted Platform Module, complex format parsers, mazes, and a hash map. + + +Diversity +~~~~~~~~~ + +A key point here is that fuzzing and testing tools should search for *diverse* inputs, +to avoid getting trapped in a "optimal" but non-bug-finding state. For example, IJON +optimized x-distance *at each distinct altitude* to avoid dead-ends. + +Hypothesis tracks the :wikipedia:`pareto frontier ` of metrics passed +to :func:`hypothesis.target` (plus some internal metrics). For observable dimensions +where there is *not* a clear "best" direction and may be thousands of dimensions, +such as the hit-count of each branch, there are a variety of approaches. + +AFL and related fuzzers "bucketize" the hitcount and then track uniqueness up to a +64k hash of this vector, as a compromise between performance (driven by CPU cache sizes) +and collision rate (typically 10-15% for library-like targets, but up to 75% for +larger applications :cite:`CollAFL`). + +HypoFuzz's approach of keeping the best (shortlex-minimal) seed covering each branch +is reminiscent of SugarSearch :cite:`SugarSearch`; that paper opens with a lovely +survey of `quality-diversity algorithms `__ +algorithms - including CVT-MAP-elites :cite:`MAP-elites,CVT-MAP-elites`, which might +be nice to try for prioritization in high-dimensional spaces. + +BeDivFuzz :cite:`BeDivFuzz` proposes measuring behavioural diversity using the +:wikipedia:`'Hill numbers' ` from ecology; HypoFuzz already selects +seeds via (a mixed distribution including) sampling seeds in inverse proportion to +the observed frequency of the rarest branch covered by each. + + + +Coverage +-------- + +Before diving in to the use of coverage information as feedback for test-case generation +in fuzzers, it's worth covering the use of code coverage in a software development cycle. + +*How to Misuse Code Coverage* :cite:`HowToMisuseCoverage` still resonates: +"I wouldn't have written four coverage tools if I didn't think they're helpful. +But they're only helpful if they're used to *enhance* thought, not *replace* it.". +More than 20 years later, `code coverage best practices +`__ +from the Google Testing Blog gives similar advice. + +*Coverage and its discontents* :cite:`CoverageDiscontents` explores the role of coverage +metrics in test-suite evaluation, and argues that there is an underlying uncertainty as +to what exactly measuring coverage should achieve, how we would know if it can, and what +we as researchers and developers can do about it. + +`Verification, coverage and maximization: the big picture +`__ +aims to explain how coverage is used to optimize the verification process, what it means to +auto-maximize coverage, and how people have tried to do it - from a background in +hardware design, which brings an instructively different perspective to analogous problems. +(similar to Dan Luu's `AFL + QuickCheck = ? `__, above) + + +Reducing coverage overhead by rewriting the target +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +Full-speed fuzzing :cite:`FullSpeedFuzzing` reduces the performance overhead of +coverage measurement by rewriting the target - because most executions do not find +new coverage, this allows you to instrument a very small proportion of executions. + +While offering very impressive speedups, this doesn't support differential metrics +or non-coverage metrics, and the rewriting trick would be rather difficult in Python. +Nonetheless, the `PLASMA-UMass `__ team have released +`Slipcover `__, a super-low-overhead +coverage tool for Python based on just this principle - and explicitly list fuzzing +as one of the applications. + +Augumenting PyPy's tracing JIT to report coverage information would probably also be +fruitful, and very fast given the JIT-friendly repeated execution pattern of fuzzing. + + +Faster coverage measurement for Python +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +:pypi:`coverage` typically slows instrumented programs by a factor of several times, +typically ranging from 2-5x but with as much as 70x known on some workloads. +There have been several proposals to improve this - e.g. `Python Coverage could be fast +`__ - and relatively +small grants could make a very large impact. + +Abandoning most of the features in :pypi:`coverage` (reporting, analysis of untaken +branches, aggregation across interpreters, etc.) to focus solely on the branch-reporting +logic used by a fuzzer `can also offer substantial speedups +`__. + + +Sensitive coverage metrics +~~~~~~~~~~~~~~~~~~~~~~~~~~ + +*Be Sensitive and Collaborative: Analyzing Impact of Coverage Metrics in Greybox Fuzzing* +:cite:`SensitiveAndCollaborative` compares a range of coverage metrics - from branch +coverage, to n-gram-coverage (chains of branches, when standard branch coverage is 2-gram), +full path coverage, and several others. Due to resource limits - time, memory, compute - +no metric dominates all others, suggesting that adapting the metric per-target might +be helpful. + + +Compressing coverage information +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +Ankou :cite:`Ankou` measures coverage of the *number of times* each branch was executed, +i.e. order-insensitive path coverage. To manage the very large number of covering inputs, +they use a dynamic distance-based metric to retain only dissimilar inputs rather than +all covering inputs. By comparison AFL bucketizes branch hit-counts. + + + +Miscellaneous +------------- + +Ensemble fuzzing with seed sharing +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +EnFuzz :cite:`EnFuzz` demonstrates that combining diverse fuzzers both improves their +joint performance (given equal resources), and makes the performance much more robust. +The argument that this works by allowing specialised fuzzers to build on each other's +work, including iteratively, is compelling. + +Cupid :cite:`Cupid` demonstrates significant practical advances in ensemble fuzzing, +defining a *complementarity* metric (union of the expected value of the set of covered +branches for each fuzzer). This allows for efficient selection of fuzzers to be ensembled +based only on 'solo' runs of each. Because Cupid leaves seed scheduling to future work +and is based on target-independent characterisation, this technique is used to design +HypoFuzz 'tactics' but not for runtime adaptation. + +It's less clear how to leverage this for HypoFuzz, since there aren't many other +fuzzers targeting Hypothesis tests. You could use :pypi:`python-afl`, +:pypi:`pythonfuzz`, or `python-hfuzz `__ +on Hypothesis' :hydocs:`.fuzz_one_input ` hook +if you were careful enough about the database location; we intend to evaluate this +approach but don't expect an advantage from adding structure-naive fuzzers. + +We think the general lesson is more like that of swarm testing: diversity is the +key to effective fuzzing. Knowing that in advance though, we can build our single +fuzzer to execute a mixture of the relevant behaviours with the desired distribution, +and even make that distribution adaptive with respect to each target. + + +Hybrid concrete/symbolic fuzzing +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +This literature review has largely ignored symbolic execution, because support for +Python is at a very early stage and does not scale to real-world programs. + +For native code, *concolic execution* - tools which combine concrete and symbolic +execution of tests - date back to DART :cite:`DART` and CUTE :cite:`CUTE` in 2005; +while Microsoft's SAGE :cite:`SAGE` found `roughly one-third of all the bugs +`__ discovered by file fuzzing during +the development of Windows 7 - running *after* static analysis and other fuzzers. + +Inputs synthesised by symbolic or concolic approaches could provide the initial +seed pool for a classic mutational fuzzer, and provide a way to 'get unstuck' +on conditions which are hard to satisfy by chance. +There are `plans for Hypothesis to support symbolic execution via +`__ :pypi:`crosshair-tool`, +and a promising proof-of-concept, but no firm timeline unless someone volunteers to +take on the project. + + +Scaling fuzzers up to many cores +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +The `scaling behaviour of fuzzers is often neglected +`__, +which can make academic evaluations running on single cores misleading as users +in industry run campaigns on tens, hundreds, or even thousands of cores. +For example, classic AFL quickly (5-20 cores) bottlenecks on ``fork()``, +and adding more than 40 cores may *reduce total throughput*. +IO bottlenecks are also common in filesystem accesses for ensemble fuzzing campaigns. + +:cite:`PAFL` finds that this problem is *worse* among more advanced fuzzers - +if you share seeds but not e.g. the branch hit-counts for AFL-Fast, each process +must duplicate the discovery process. P-AFL adds a mechanism for global sharing +of guidance information as well as seeds, and additionally focusses each process +on fuzzing a subset of the branches in the program - which diversifies the search +process and effectively ensembles variants of a single base fuzzer. + +We plan to mitigate this in HypoFuzz, by sharing ephemeral state between instances +and runs via the database. + + +Visualising fuzzer performance +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +HypoFuzz does not offer many configuration options, but users are effectively +co-developers of the fuzzer because they provide the system under test, the +test function, and the strategies which define possible inputs. Providing +clear and detailed - but not overwhelming - information about what the fuzzer +is doing can therefore support a wider feedback loop of improvement to the tests +and ultimately better bug-detection. + +Brandon Falk's `some fuzzing thoughts +`__ points +out that a log-x-axis is almost always the right way to view fuzzer progress +graphs, especially considering the well-known exponential scaling curve +:cite:`ExponentialCost`. + +Cornelius Aschermann's `on measuring and visualising fuzzer performance +`__ +suggests a range of other helpful visualisations, including the proportion of +inputs from various generation or mutation strategies which cover each known +branch. + +*Evaluating Fuzz Testing* :cite:`EvaluatingFuzzTesting` investigates serious +problems in previous evaluations, and provides the now-canonical guidelines +for evaluating fuzzers. Essential reading if you wish to publish an evaluation, +or simply decide whether some tweak was actually helpful without getting the +sign of the relationship wrong due to random noise. + + + +References +---------- + +*While not all the referenced papers are open access, they +do all have freely accessible PDFs. Enjoy!* + +.. bibliography:: literature.bib diff --git a/docs/docs/_sources/quickstart.rst.txt b/docs/docs/_sources/quickstart.rst.txt new file mode 100644 index 0000000..7f3f148 --- /dev/null +++ b/docs/docs/_sources/quickstart.rst.txt @@ -0,0 +1,77 @@ +Quickstart guide +================ + + +Prerequisites: :pypi:`pytest` & :pypi:`hypothesis` +-------------------------------------------------- + +HypoFuzz is designed to run :pypi:`hypothesis` tests, so you'll need some of +those as fuzz targets. + +Our current implementation uses :pypi:`pytest` to collect the tests to run, +so you can select specific tests in the usual way by file, ``-k`` selectors, +or just allow pytest to discover all your tests for you. + + +Installation +------------ + +HypoFuzz is a pure-Python package, and can be installed from your shell with + +.. code-block:: shell + + pip install hypofuzz + +or from a ``requirements.txt`` file like + +.. code-block:: text + + ... + hypofuzz >= 21.05.1 + ... + +Optionally, you can ``pip install hypofuzz[pytrace]`` for automatic time-travel +debugging with `PyTrace `__ through the web interface. +There are still some rough edges here, but it's pretty cool. + + +Running :command:`hypothesis fuzz` +---------------------------------- + +The core idea is that while you run :command:`pytest ...` on each change, +you run :command:`hypothesis fuzz ...` on a server - and it'll keep searching +for interesting new inputs until shut down from outside. + +.. command-output:: hypothesis fuzz --help + +By design, this is minimally configurable: test selection and collection is +handled by ``pytest``, using exactly the same syntax as usual, and the +remaining options are out of scope for the fuzzer itself to determine. + + +Reproducing and fixing bugs +--------------------------- + +HypoFuzz saves any failures it finds into Hypothesis' standard example +database, so the workflow for deduplicating and reproducing any failures +is "run your test suite in the usual way". + +It really is that easy! + + +A quick glance under the hood +----------------------------- + +HypoFuzz isn't "better" than Hypothesis - it's playing a different game, +and the main difference is that it runs for much longer. That means: + +- The performance overhead of coverage instrumentation pays off, as we can + tell when inputs do something unusual and spend more time generating similar + things in future. + +- Instead of running 100 examples for each test before moving on to the next, + we can interleave them, run different numbers of examples for each test, and + focus on the ones where we're discovering new behaviours fastest. + +We spend our time generating more interesting examples, focussed on the most +complex tests, and do so *without any human input at all*. diff --git a/docs/docs/_sources/roadmap.rst.txt b/docs/docs/_sources/roadmap.rst.txt new file mode 100644 index 0000000..9b95f59 --- /dev/null +++ b/docs/docs/_sources/roadmap.rst.txt @@ -0,0 +1,54 @@ +Development roadmap +=================== + +HypoFuzz is both a research project and a production-ready tool. + +We believe that this dual nature is a strength for both: users get to leverage +a tool based on cutting-edge research, but also ensure that the problems it +solves are ones that really matter. There's a lot of applied research out +there which never makes the translation to practice - and we don't intend to +add to it. + +`For upcoming ideas, see our GitHub issue tracker `__. + + +Compatibility policy +-------------------- + +HypoFuzz uses `calendar-based versioning `__, with a +``YY-MM-patch`` format. + +Because HypoFuzz is closely tied to Hypothesis internals, we recommend pinning +your transitive dependencies using a tool like :pypi:`pip-compile `, +:pypi:`poetry`, or :pypi:`pipenv`. This makes it possible to reproduce old +environments based only on your VCS history, and ensures that any compatibility +problems in new releases can be handled when it suits you. + + +Direct dependencies +~~~~~~~~~~~~~~~~~~~ + +HypoFuzz's direct dependencies are: + +.. literalinclude:: ../setup.py + :prepend: install_requires = [ + :start-after: install_requires=[ + :end-before: ], + :append: ] + + +API deprecation policy +~~~~~~~~~~~~~~~~~~~~~~ + +The command-line interface will not make incompatible changes without at least +three months notice, during which passing deprecated options will emit runtime +warnings (e.g. via the terminal, displayed on the dashboard, etc.). + +User-accesible integration points with Hypothesis, such as the +:class:`~hypothesis:hypothesis.database.ExampleDatabase` API, are considered +stable upstream and are unlikely to change even in major version releases. + +If it is impractical to continue to support old versions of Hypothesis (or other +dependencies) after a major update, the minimum supported version will be updated. +If you would like to use new versions of HypoFuzz with old versions of its +dependencies, please get in touch to discuss your specific needs. diff --git a/docs/docs/_static/basic.css b/docs/docs/_static/basic.css new file mode 100644 index 0000000..30fee9d --- /dev/null +++ b/docs/docs/_static/basic.css @@ -0,0 +1,925 @@ +/* + * basic.css + * ~~~~~~~~~ + * + * Sphinx stylesheet -- basic theme. + * + * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS. + * :license: BSD, see LICENSE for details. + * + */ + +/* -- main layout ----------------------------------------------------------- */ + +div.clearer { + clear: both; +} + +div.section::after { + display: block; + content: ''; + clear: left; +} + +/* -- relbar ---------------------------------------------------------------- */ + +div.related { + width: 100%; + font-size: 90%; +} + +div.related h3 { + display: none; +} + +div.related ul { + 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+ +/** + * Simple result scoring code. + */ +if (typeof Scorer === "undefined") { + var Scorer = { + // Implement the following function to further tweak the score for each result + // The function takes a result array [docname, title, anchor, descr, score, filename] + // and returns the new score. + /* + score: result => { + const [docname, title, anchor, descr, score, filename] = result + return score + }, + */ + + // query matches the full name of an object + objNameMatch: 11, + // or matches in the last dotted part of the object name + objPartialMatch: 6, + // Additive scores depending on the priority of the object + objPrio: { + 0: 15, // used to be importantResults + 1: 5, // used to be objectResults + 2: -5, // used to be unimportantResults + }, + // Used when the priority is not in the mapping. + objPrioDefault: 0, + + // query found in title + title: 15, + partialTitle: 7, + // query found in terms + term: 5, + partialTerm: 2, + }; +} + +const _removeChildren = (element) => { + while (element && element.lastChild) element.removeChild(element.lastChild); +}; + +/** + * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_Expressions#escaping + */ +const _escapeRegExp = (string) => + string.replace(/[.*+\-?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string + +const _displayItem = (item, searchTerms, highlightTerms) => { + const docBuilder = DOCUMENTATION_OPTIONS.BUILDER; + const docFileSuffix = DOCUMENTATION_OPTIONS.FILE_SUFFIX; + const docLinkSuffix = DOCUMENTATION_OPTIONS.LINK_SUFFIX; + const showSearchSummary = DOCUMENTATION_OPTIONS.SHOW_SEARCH_SUMMARY; + const contentRoot = document.documentElement.dataset.content_root; + + const [docName, title, anchor, descr, score, _filename] = item; + + let listItem = document.createElement("li"); + let requestUrl; + let linkUrl; + if (docBuilder === "dirhtml") { + // dirhtml builder + let dirname = docName + "/"; + if (dirname.match(/\/index\/$/)) + dirname = dirname.substring(0, dirname.length - 6); + else if (dirname === "index/") dirname = ""; + requestUrl = contentRoot + dirname; + linkUrl = requestUrl; + } else { + // normal html builders + requestUrl = contentRoot + docName + docFileSuffix; + linkUrl = docName + docLinkSuffix; + } + let linkEl = listItem.appendChild(document.createElement("a")); + linkEl.href = linkUrl + anchor; + linkEl.dataset.score = score; + linkEl.innerHTML = title; + if (descr) { + listItem.appendChild(document.createElement("span")).innerHTML = + " (" + descr + ")"; + // highlight search terms in the description + if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js + highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted")); + } + else if (showSearchSummary) + fetch(requestUrl) + .then((responseData) => responseData.text()) + .then((data) => { + if (data) + listItem.appendChild( + Search.makeSearchSummary(data, searchTerms) + ); + // highlight search terms in the summary + if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js + highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted")); + }); + Search.output.appendChild(listItem); +}; +const _finishSearch = (resultCount) => { + Search.stopPulse(); + Search.title.innerText = _("Search Results"); + if (!resultCount) + Search.status.innerText = Documentation.gettext( + "Your search did not match any documents. Please make sure that all words are spelled correctly and that you've selected enough categories." + ); + else + Search.status.innerText = _( + `Search finished, found ${resultCount} page(s) matching the search query.` + ); +}; +const _displayNextItem = ( + results, + resultCount, + searchTerms, + highlightTerms, +) => { + // results left, load the summary and display it + // this is intended to be dynamic (don't sub resultsCount) + if (results.length) { + _displayItem(results.pop(), searchTerms, highlightTerms); + setTimeout( + () => _displayNextItem(results, resultCount, searchTerms, highlightTerms), + 5 + ); + } + // search finished, update title and status message + else _finishSearch(resultCount); +}; + +/** + * Default splitQuery function. Can be overridden in ``sphinx.search`` with a + * custom function per language. + * + * The regular expression works by splitting the string on consecutive characters + * that are not Unicode letters, numbers, underscores, or emoji characters. + * This is the same as ``\W+`` in Python, preserving the surrogate pair area. + */ +if (typeof splitQuery === "undefined") { + var splitQuery = (query) => query + .split(/[^\p{Letter}\p{Number}_\p{Emoji_Presentation}]+/gu) + .filter(term => term) // remove remaining empty strings +} + +/** + * Search Module + */ +const Search = { + _index: null, + _queued_query: null, + _pulse_status: -1, + + htmlToText: (htmlString) => { + const htmlElement = new DOMParser().parseFromString(htmlString, 'text/html'); + htmlElement.querySelectorAll(".headerlink").forEach((el) => { el.remove() }); + const docContent = htmlElement.querySelector('[role="main"]'); + if (docContent !== undefined) return docContent.textContent; + console.warn( + "Content block not found. Sphinx search tries to obtain it via '[role=main]'. Could you check your theme or template." + ); + return ""; + }, + + init: () => { + const query = new URLSearchParams(window.location.search).get("q"); + document + .querySelectorAll('input[name="q"]') + .forEach((el) => (el.value = query)); + if (query) Search.performSearch(query); + }, + + loadIndex: (url) => + (document.body.appendChild(document.createElement("script")).src = url), + + setIndex: (index) => { + Search._index = index; + if (Search._queued_query !== null) { + const query = Search._queued_query; + Search._queued_query = null; + Search.query(query); + } + }, + + hasIndex: () => Search._index !== null, + + deferQuery: (query) => (Search._queued_query = query), + + stopPulse: () => (Search._pulse_status = -1), + + startPulse: () => { + if (Search._pulse_status >= 0) return; + + const pulse = () => { + Search._pulse_status = (Search._pulse_status + 1) % 4; + Search.dots.innerText = ".".repeat(Search._pulse_status); + if (Search._pulse_status >= 0) window.setTimeout(pulse, 500); + }; + pulse(); + }, + + /** + * perform a search for something (or wait until index is loaded) + */ + performSearch: (query) => { + // create the required interface elements + const searchText = document.createElement("h2"); + searchText.textContent = _("Searching"); + const searchSummary = document.createElement("p"); + searchSummary.classList.add("search-summary"); + searchSummary.innerText = ""; + const searchList = document.createElement("ul"); + searchList.classList.add("search"); + + const out = document.getElementById("search-results"); + Search.title = out.appendChild(searchText); + Search.dots = Search.title.appendChild(document.createElement("span")); + Search.status = out.appendChild(searchSummary); + Search.output = out.appendChild(searchList); + + const searchProgress = document.getElementById("search-progress"); + // Some themes don't use the search progress node + if (searchProgress) { + searchProgress.innerText = _("Preparing search..."); + } + Search.startPulse(); + + // index already loaded, the browser was quick! + if (Search.hasIndex()) Search.query(query); + else Search.deferQuery(query); + }, + + /** + * execute search (requires search index to be loaded) + */ + query: (query) => { + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const titles = Search._index.titles; + const allTitles = Search._index.alltitles; + const indexEntries = Search._index.indexentries; + + // stem the search terms and add them to the correct list + const stemmer = new Stemmer(); + const searchTerms = new Set(); + const excludedTerms = new Set(); + const highlightTerms = new Set(); + const objectTerms = new Set(splitQuery(query.toLowerCase().trim())); + splitQuery(query.trim()).forEach((queryTerm) => { + const queryTermLower = queryTerm.toLowerCase(); + + // maybe skip this "word" + // stopwords array is from language_data.js + if ( + stopwords.indexOf(queryTermLower) !== -1 || + queryTerm.match(/^\d+$/) + ) + return; + + // stem the word + let word = stemmer.stemWord(queryTermLower); + // select the correct list + if (word[0] === "-") excludedTerms.add(word.substr(1)); + else { + searchTerms.add(word); + highlightTerms.add(queryTermLower); + } + }); + + if (SPHINX_HIGHLIGHT_ENABLED) { // set in sphinx_highlight.js + localStorage.setItem("sphinx_highlight_terms", [...highlightTerms].join(" ")) + } + + // console.debug("SEARCH: searching for:"); + // console.info("required: ", [...searchTerms]); + // console.info("excluded: ", [...excludedTerms]); + + // array of [docname, title, anchor, descr, score, filename] + let results = []; + _removeChildren(document.getElementById("search-progress")); + + const queryLower = query.toLowerCase(); + for (const [title, foundTitles] of Object.entries(allTitles)) { + if (title.toLowerCase().includes(queryLower) && (queryLower.length >= title.length/2)) { + for (const [file, id] of foundTitles) { + let score = Math.round(100 * queryLower.length / title.length) + results.push([ + docNames[file], + titles[file] !== title ? `${titles[file]} > ${title}` : title, + id !== null ? "#" + id : "", + null, + score, + filenames[file], + ]); + } + } + } + + // search for explicit entries in index directives + for (const [entry, foundEntries] of Object.entries(indexEntries)) { + if (entry.includes(queryLower) && (queryLower.length >= entry.length/2)) { + for (const [file, id] of foundEntries) { + let score = Math.round(100 * queryLower.length / entry.length) + results.push([ + docNames[file], + titles[file], + id ? "#" + id : "", + null, + score, + filenames[file], + ]); + } + } + } + + // lookup as object + objectTerms.forEach((term) => + results.push(...Search.performObjectSearch(term, objectTerms)) + ); + + // lookup as search terms in fulltext + results.push(...Search.performTermsSearch(searchTerms, excludedTerms)); + + // let the scorer override scores with a custom scoring function + if (Scorer.score) results.forEach((item) => (item[4] = Scorer.score(item))); + + // now sort the results by score (in opposite order of appearance, since the + // display function below uses pop() to retrieve items) and then + // alphabetically + results.sort((a, b) => { + const leftScore = a[4]; + const rightScore = b[4]; + if (leftScore === rightScore) { + // same score: sort alphabetically + const leftTitle = a[1].toLowerCase(); + const rightTitle = b[1].toLowerCase(); + if (leftTitle === rightTitle) return 0; + return leftTitle > rightTitle ? -1 : 1; // inverted is intentional + } + return leftScore > rightScore ? 1 : -1; + }); + + // remove duplicate search results + // note the reversing of results, so that in the case of duplicates, the highest-scoring entry is kept + let seen = new Set(); + results = results.reverse().reduce((acc, result) => { + let resultStr = result.slice(0, 4).concat([result[5]]).map(v => String(v)).join(','); + if (!seen.has(resultStr)) { + acc.push(result); + seen.add(resultStr); + } + return acc; + }, []); + + results = results.reverse(); + + // for debugging + //Search.lastresults = results.slice(); // a copy + // console.info("search results:", Search.lastresults); + + // print the results + _displayNextItem(results, results.length, searchTerms, highlightTerms); + }, + + /** + * search for object names + */ + performObjectSearch: (object, objectTerms) => { + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const objects = Search._index.objects; + const objNames = Search._index.objnames; + const titles = Search._index.titles; + + const results = []; + + const objectSearchCallback = (prefix, match) => { + const name = match[4] + const fullname = (prefix ? prefix + "." : "") + name; + const fullnameLower = fullname.toLowerCase(); + if (fullnameLower.indexOf(object) < 0) return; + + let score = 0; + const parts = fullnameLower.split("."); + + // check for different match types: exact matches of full name or + // "last name" (i.e. last dotted part) + if (fullnameLower === object || parts.slice(-1)[0] === object) + score += Scorer.objNameMatch; + else if (parts.slice(-1)[0].indexOf(object) > -1) + score += Scorer.objPartialMatch; // matches in last name + + const objName = objNames[match[1]][2]; + const title = titles[match[0]]; + + // If more than one term searched for, we require other words to be + // found in the name/title/description + const otherTerms = new Set(objectTerms); + otherTerms.delete(object); + if (otherTerms.size > 0) { + const haystack = `${prefix} ${name} ${objName} ${title}`.toLowerCase(); + if ( + [...otherTerms].some((otherTerm) => haystack.indexOf(otherTerm) < 0) + ) + return; + } + + let anchor = match[3]; + if (anchor === "") anchor = fullname; + else if (anchor === "-") anchor = objNames[match[1]][1] + "-" + fullname; + + const descr = objName + _(", in ") + title; + + // add custom score for some objects according to scorer + if (Scorer.objPrio.hasOwnProperty(match[2])) + score += Scorer.objPrio[match[2]]; + else score += Scorer.objPrioDefault; + + results.push([ + docNames[match[0]], + fullname, + "#" + anchor, + descr, + score, + filenames[match[0]], + ]); + }; + Object.keys(objects).forEach((prefix) => + objects[prefix].forEach((array) => + objectSearchCallback(prefix, array) + ) + ); + return results; + }, + + /** + * search for full-text terms in the index + */ + performTermsSearch: (searchTerms, excludedTerms) => { + // prepare search + const terms = Search._index.terms; + const titleTerms = Search._index.titleterms; + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const titles = Search._index.titles; + + const scoreMap = new Map(); + const fileMap = new Map(); + + // perform the search on the required terms + searchTerms.forEach((word) => { + const files = []; + const arr = [ + { files: terms[word], score: Scorer.term }, + { files: titleTerms[word], score: Scorer.title }, + ]; + // add support for partial matches + if (word.length > 2) { + const escapedWord = _escapeRegExp(word); + Object.keys(terms).forEach((term) => { + if (term.match(escapedWord) && !terms[word]) + arr.push({ files: terms[term], score: Scorer.partialTerm }); + }); + Object.keys(titleTerms).forEach((term) => { + if (term.match(escapedWord) && !titleTerms[word]) + arr.push({ files: titleTerms[word], score: Scorer.partialTitle }); + }); + } + + // no match but word was a required one + if (arr.every((record) => record.files === undefined)) return; + + // found search word in contents + arr.forEach((record) => { + if (record.files === undefined) return; + + let recordFiles = record.files; + if (recordFiles.length === undefined) recordFiles = [recordFiles]; + files.push(...recordFiles); + + // set score for the word in each file + recordFiles.forEach((file) => { + if (!scoreMap.has(file)) scoreMap.set(file, {}); + scoreMap.get(file)[word] = record.score; + }); + }); + + // create the mapping + files.forEach((file) => { + if (fileMap.has(file) && fileMap.get(file).indexOf(word) === -1) + fileMap.get(file).push(word); + else fileMap.set(file, [word]); + }); + }); + + // now check if the files don't contain excluded terms + const results = []; + for (const [file, wordList] of fileMap) { + // check if all requirements are matched + + // as search terms with length < 3 are discarded + const filteredTermCount = [...searchTerms].filter( + (term) => term.length > 2 + ).length; + if ( + wordList.length !== searchTerms.size && + wordList.length !== filteredTermCount + ) + continue; + + // ensure that none of the excluded terms is in the search result + if ( + [...excludedTerms].some( + (term) => + terms[term] === file || + titleTerms[term] === file || + (terms[term] || []).includes(file) || + (titleTerms[term] || []).includes(file) + ) + ) + break; + + // select one (max) score for the file. + const score = Math.max(...wordList.map((w) => scoreMap.get(file)[w])); + // add result to the result list + results.push([ + docNames[file], + titles[file], + "", + null, + score, + filenames[file], + ]); + } + return results; + }, + + /** + * helper function to return a node containing the + * search summary for a given text. keywords is a list + * of stemmed words. + */ + makeSearchSummary: (htmlText, keywords) => { + const text = Search.htmlToText(htmlText); + if (text === "") return null; + + const textLower = text.toLowerCase(); + const actualStartPosition = [...keywords] + .map((k) => textLower.indexOf(k.toLowerCase())) + .filter((i) => i > -1) + .slice(-1)[0]; + const startWithContext = Math.max(actualStartPosition - 120, 0); + + const top = startWithContext === 0 ? "" : "..."; + const tail = startWithContext + 240 < text.length ? "..." : ""; + + let summary = document.createElement("p"); + summary.classList.add("context"); + summary.textContent = top + text.substr(startWithContext, 240).trim() + tail; + + return summary; + }, +}; + +_ready(Search.init); diff --git a/docs/docs/_static/sphinx_highlight.js b/docs/docs/_static/sphinx_highlight.js new file mode 100644 index 0000000..8a96c69 --- /dev/null +++ b/docs/docs/_static/sphinx_highlight.js @@ -0,0 +1,154 @@ +/* Highlighting utilities for Sphinx HTML documentation. */ +"use strict"; + +const SPHINX_HIGHLIGHT_ENABLED = true + +/** + * highlight a given string on a node by wrapping it in + * span elements with the given class name. + */ +const _highlight = (node, addItems, text, className) => { + if (node.nodeType === Node.TEXT_NODE) { + const val = node.nodeValue; + const parent = node.parentNode; + const pos = val.toLowerCase().indexOf(text); + if ( + pos >= 0 && + !parent.classList.contains(className) && + !parent.classList.contains("nohighlight") + ) { + let span; + + const closestNode = parent.closest("body, svg, foreignObject"); + const isInSVG = closestNode && closestNode.matches("svg"); + if (isInSVG) { + span = document.createElementNS("http://www.w3.org/2000/svg", "tspan"); + } else { + span = document.createElement("span"); + span.classList.add(className); + } + + span.appendChild(document.createTextNode(val.substr(pos, text.length))); + const rest = document.createTextNode(val.substr(pos + text.length)); + parent.insertBefore( + span, + parent.insertBefore( + rest, + node.nextSibling + ) + ); + node.nodeValue = val.substr(0, pos); + /* There may be more occurrences of search term in this node. So call this + * function recursively on the remaining fragment. + */ + _highlight(rest, addItems, text, className); + + if (isInSVG) { + const rect = document.createElementNS( + "http://www.w3.org/2000/svg", + "rect" + ); + const bbox = parent.getBBox(); + rect.x.baseVal.value = bbox.x; + rect.y.baseVal.value = bbox.y; + rect.width.baseVal.value = bbox.width; + rect.height.baseVal.value = bbox.height; + rect.setAttribute("class", className); + addItems.push({ parent: parent, target: rect }); + } + } + } else if (node.matches && !node.matches("button, select, textarea")) { + node.childNodes.forEach((el) => _highlight(el, addItems, text, className)); + } +}; +const _highlightText = (thisNode, text, className) => { + let addItems = []; + _highlight(thisNode, addItems, text, className); + addItems.forEach((obj) => + obj.parent.insertAdjacentElement("beforebegin", obj.target) + ); +}; + +/** + * Small JavaScript module for the documentation. + */ +const SphinxHighlight = { + + /** + * highlight the search words provided in localstorage in the text + */ + highlightSearchWords: () => { + if (!SPHINX_HIGHLIGHT_ENABLED) return; // bail if no highlight + + // get and clear terms from localstorage + const url = new URL(window.location); + const highlight = + localStorage.getItem("sphinx_highlight_terms") + || url.searchParams.get("highlight") + || ""; + localStorage.removeItem("sphinx_highlight_terms") + url.searchParams.delete("highlight"); + window.history.replaceState({}, "", url); + + // get individual terms from highlight string + const terms = highlight.toLowerCase().split(/\s+/).filter(x => x); + if (terms.length === 0) return; // nothing to do + + // There should never be more than one element matching "div.body" + const divBody = document.querySelectorAll("div.body"); + const body = divBody.length ? divBody[0] : document.querySelector("body"); + window.setTimeout(() => { + terms.forEach((term) => _highlightText(body, term, "highlighted")); + }, 10); + + const searchBox = document.getElementById("searchbox"); + if (searchBox === null) return; + searchBox.appendChild( + document + .createRange() + .createContextualFragment( + '" + ) + ); + }, + + /** + * helper function to hide the search marks again + */ + hideSearchWords: () => { + document + .querySelectorAll("#searchbox .highlight-link") + .forEach((el) => el.remove()); + document + .querySelectorAll("span.highlighted") + .forEach((el) => el.classList.remove("highlighted")); + localStorage.removeItem("sphinx_highlight_terms") + }, + + initEscapeListener: () => { + // only install a listener if it is really needed + if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) return; + + document.addEventListener("keydown", (event) => { + // bail for input elements + if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return; + // bail with special keys + if (event.shiftKey || event.altKey || event.ctrlKey || event.metaKey) return; + if (DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS && (event.key === "Escape")) { + SphinxHighlight.hideSearchWords(); + event.preventDefault(); + } + }); + }, +}; + +_ready(() => { + /* Do not call highlightSearchWords() when we are on the search page. + * It will highlight words from the *previous* search query. + */ + if (typeof Search === "undefined") SphinxHighlight.highlightSearchWords(); + SphinxHighlight.initEscapeListener(); +}); diff --git a/docs/docs/changelog.html b/docs/docs/changelog.html new file mode 100644 index 0000000..2b51864 --- /dev/null +++ b/docs/docs/changelog.html @@ -0,0 +1,229 @@ + + + + + + + Changelog — HypoFuzz docs + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Changelog

+

HypoFuzz uses calendar-based versioning, with a +YY-MM-patch format.

+
+

24.02.2

+

Fixed a dashboard bug (#31).

+
+
+

24.02.1

+

Now requires Hypothesis 6.93.2 +or later, fixing compatibility with some unstable internals that HypoFuzz hooks into (yes, again). +Also deduplicates the displayed covering examples in the dashboard, when their reprs are identical.

+
+
+

23.12.1

+

Now requires Hypothesis 6.91 +or later, fixing compatibility with some unstable internals that HypoFuzz hooks into.

+
+
+

23.07.1

+

Various small patches for issues found by fuzzing Hypothesis itself. +Notably, we now try to fuzz functions which require autouse fixtures +even though we don’t provide those fixtures - it often works!

+
+
+

23.06.1

+

Hypofuzz now writes .patch files with failing examples, and optionally +with covering examples - including removal of redundant covering examples.

+
+
+

23.05.3

+

Yet another compatibility fix for explain mode, with even more tests for future regressions. +Third time lucky, we hope!

+
+
+

23.05.2

+

Additional compatibility fix, and improved tests to avoid future regressions.

+
+
+

23.05.1

+

Now requires Hypothesis 6.75.2 +or later, fixing compatibility with some unstable internals that HypoFuzz hooks into.

+
+
+

23.04.1

+

Fixed a bug affecting traceback reporting on Python 3.10+ (#16).

+
+
+

22.12.1

+

Fixed a NotImplementedError when HypoFuzz had found a failing input for every +test running in some process. Now, we cleanly sys.exit(1) instead.

+
+
+

22.10.1

+

First open-source release! Also improves database handling and adds +a timelimit to shrinking to better handle pathological cases.

+
+
+

22.07.1

+

Fixes compatibility with Hypothesis 6.49.1 +and later (released July 5th).

+
+
+

21.12.2

+

Web-based time-travel debugging with PyTrace - just +pip install hypofuzz[pytrace] and click the link on any failing test!

+
+
+

21.12.1

+

Improved dashboard (again!), better generation/mutation heuristics, +basic residual-risk estimation, free-for-noncommercial-use on PyPI.

+
+
+

21.05.1

+

Improved dashboard, fixed memory leaks, support arbitary hypothesis.event() +calls as coverage, performance improvements.

+
+
+

20.09.1

+

Multiprocess fuzzing with seed sharing and corpus distillation, +and basic prioritisation of seeds covering rare branches.

+

Still very much in alpha, but the fundamentals all work now.

+
+
+

20.08.1

+

First packaged version of HypoFuzz

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© Copyright 2024, Zac Hatfield-Dodds.

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Configuration

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It’s all automatic

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Wherever possible, HypoFuzz is designed to do the right thing without configuration.

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The hypothesis fuzz CLI accepts arguments to determine parameters like the +number of processes to use, and the port on which to serve the dashboard - +though every one of them is optional - and you can select which tests to fuzz +in the same way you would select them via pytest.

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Once that’s all set up though, the fuzzer is not configurable: manual prioritization +of a fuzzing process is considerably more error-prone than allowing the adaptive +scheduler to do its thing, and computer time is much cheaper than yours.

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Custom coverage events

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HypoFuzz runs coverage on every input to observe the branch coverage of your +code - but we know that there are many things code can do that aren’t captured by +the set of executed branches. This blog post +gives a good overview of coverage-driven verification workflows.

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We therefore treat each hypothesis.event() as a “virtual” branch - while it’s +not part of the control-flow graph, we keep track of inputs which produced each +observed event in the same way that we track the inputs which produce each branch.

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You can therefore use the event() function in your tests to +mark out categories of behaviour, boundary conditions, and so on, and then let the +fuzzer exploit that to generate more diverse and better-targeted inputs. +And as a bonus, you’ll get useful summary statistics when running Hypothesis!

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The Hypothesis database

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The Hypothesis database forms the basis of HypoFuzz workflows: failing examples +can be reproduced automatically just by running the tests - because those inputs +are added to the database and replayed by Hypothesis itself.

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It is therefore critical that the fuzzer is using the same database as +Hypothesis - regardless of how or where you run it.

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Hypothesis’ default database is designed to persist +failing examples on a single developer’s machine, and does so via the filesystem. +If you want to share the database between your team members and your CI server +though, this isn’t going to work so well - either set the +database setting to an +ExampleDatabase backed by a network +datastore, or use a DirectoryBasedExampleDatabase +pointed to a shared filesystem.

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© Copyright 2024, Zac Hatfield-Dodds.

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Features

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The core principle of HypoFuzz is that it should be effortless to adopt: +if you have Hypothesis tests, everything else is automatic. If you’re +curious about what that “everything else” involves, this page is for you.

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Collecting tests

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HypoFuzz uses pytest to collect the test functions to fuzz, +with almost identical command-line interfaces. If you’re using +pytest ... to run your tests, hypothesis fuzz -- ... +will fuzz them.

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Note that tests which use pytest fixtures, +including autouse fixtures, are not collected as they may behave +differently outside of the pytest runtime. We recommend using a context +manager and the with statement instead.

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Support for other test runners, such as unittest, +is on our roadmap.

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Execution model

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HypoFuzz runs as one or more worker processes, by default one per available +core, and an additional process serving the live dashboard as a website.

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In each worker process, HypoFuzz prioritizes tests which discover new coverage, +which maximises the rate of discovery and therefore minimises the time taken +to cover each branch in your code. This adaptive approach is one of HypoFuzz’s +advantages over other fuzzing workflows - and the reason you can apply it to +a whole test suite at a time.

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HypoFuzz dashboard

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The HypoFuzz dashboard - online demo here - shows +the current state of the fuzzing campaign overall, with a sub-page for each test +to show more information.

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Fuzzer details

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HypoFuzz is, compared to other fuzzers in the literature, a bizzare mixture of +every technique that seems to work. Instead of being based on “one brilliant +idea” (oversimplifying, AFL = “coverage-guided mutation”, [BohmePhamRoychoudhury19] += “bias towards rare branches”, etc.), we have a single simple goal: +fuzzing your property-based test suite should be effortless.

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Because HypoFuzz is designed to exploit features that already exist in Hypothesis, +you can write tests which are designed to be fuzzed, but idiomatic @given +tests already work just fine.

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Basic design

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It’s a standard feedback-directed greybox fuzzer. The interesting parts are

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  1. HypoFuzz tests Python code, not native executables

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  3. we exploit property-based tests to detect semantic bugs, not just crashes

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  5. we use Hypothesis to generate highly-structured and typically valid data

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  7. we leverage a wider variety of feedbacks than most fuzzers

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  9. we fuzz very many more targets than most fuzzing campaigns

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Corpus distillation

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We exploit Hypothesis’ world-class test-case reduction logic (“shrinking”) to +maintain a seed pool of minimal covering examples for each branch - or other +reason to retain a seed.

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Those other reasons include user-defined labels via hypothesis.event(), +real-valued metrics with hypothesis.target(), +and more to come.

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Mutation logic

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The mutation logic is minimum-viable at the moment. It works shockingly well, +thanks to Hypothesis’ input structure, but substantial improvements are on the +roadmap.

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Ensemble fuzzing

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HypoFuzz natively supports ensemble fuzzing [CJM+19], by periodically loading +any new examples from the database. This works in --unsafe mode, where each +test function might run in multiple fuzzer processes at the same time, and with +other fuzzer tools leveraging e.g. the .hypothesis.fuzz_one_input +hook.

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Ensemble fuzzing can also be modelled as a mixture of the ensembled behaviours, +and HypoFuzz therefore attempts to run an adaptive mixture of all the useful +behaviours we can implement. To the extent that this works, we get the benefits +of ensembling and consume the minimum possible resources to required to do so.

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© Copyright 2024, Zac Hatfield-Dodds.

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© Copyright 2024, Zac Hatfield-Dodds.

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HypoFuzz documentation

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Hypothesis is free and open-source software, and always will be. +It’s proven itself invaluable for everyone - from students to high-school +teachers, astrophysicists to data scientists, web developers to systems +programmers, and even for hardware designers.

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HypoFuzz builds on that success: if you have Hypothesis tests, HypoFuzz +gives you a fantastic way to spend CPU time - instead of engineering time - +to find bugs early in your development cycle.

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© Copyright 2024, Zac Hatfield-Dodds.

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Quickstart guide

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Prerequisites: pytest & hypothesis

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HypoFuzz is designed to run hypothesis tests, so you’ll need some of +those as fuzz targets.

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Our current implementation uses pytest to collect the tests to run, +so you can select specific tests in the usual way by file, -k selectors, +or just allow pytest to discover all your tests for you.

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Installation

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HypoFuzz is a pure-Python package, and can be installed from your shell with

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pip install hypofuzz
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or from a requirements.txt file like

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...
+hypofuzz >= 21.05.1
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Optionally, you can pip install hypofuzz[pytrace] for automatic time-travel +debugging with PyTrace through the web interface. +There are still some rough edges here, but it’s pretty cool.

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Running hypothesis fuzz

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The core idea is that while you run pytest ... on each change, +you run hypothesis fuzz ... on a server - and it’ll keep searching +for interesting new inputs until shut down from outside.

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$ hypothesis fuzz --help
+Usage: hypothesis fuzz [OPTIONS] [-- PYTEST_ARGS]
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+  [hypofuzz] runs tests with an adaptive coverage-guided fuzzer.
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+  Unrecognised arguments are passed through to `pytest` to select the tests to
+  run, with the additional constraint that only tests using Hypothesis but not
+  any pytest fixtures can be fuzzed.
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+  This process will run forever unless stopped with e.g. ctrl-C.
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+Options:
+  -n, --numprocesses NUM        default: all available cores  [x>=1]
+  --dashboard / --no-dashboard  serve / don't serve a live dashboard page
+  --port PORT                   Optional port for the dashboard (if any)
+                                [1<=x<=65535]
+  --unsafe                      Allow concurrent execution of each test
+                                (dashboard may report wrong results)
+  -h, --help                    Show this message and exit.
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By design, this is minimally configurable: test selection and collection is +handled by pytest, using exactly the same syntax as usual, and the +remaining options are out of scope for the fuzzer itself to determine.

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Reproducing and fixing bugs

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HypoFuzz saves any failures it finds into Hypothesis’ standard example +database, so the workflow for deduplicating and reproducing any failures +is “run your test suite in the usual way”.

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It really is that easy!

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A quick glance under the hood

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HypoFuzz isn’t “better” than Hypothesis - it’s playing a different game, +and the main difference is that it runs for much longer. That means:

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  • The performance overhead of coverage instrumentation pays off, as we can +tell when inputs do something unusual and spend more time generating similar +things in future.

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  • Instead of running 100 examples for each test before moving on to the next, +we can interleave them, run different numbers of examples for each test, and +focus on the ones where we’re discovering new behaviours fastest.

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We spend our time generating more interesting examples, focussed on the most +complex tests, and do so without any human input at all.

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© Copyright 2024, Zac Hatfield-Dodds.

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Development roadmap

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HypoFuzz is both a research project and a production-ready tool.

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We believe that this dual nature is a strength for both: users get to leverage +a tool based on cutting-edge research, but also ensure that the problems it +solves are ones that really matter. There’s a lot of applied research out +there which never makes the translation to practice - and we don’t intend to +add to it.

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For upcoming ideas, see our GitHub issue tracker.

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Compatibility policy

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HypoFuzz uses calendar-based versioning, with a +YY-MM-patch format.

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Because HypoFuzz is closely tied to Hypothesis internals, we recommend pinning +your transitive dependencies using a tool like pip-compile, +poetry, or pipenv. This makes it possible to reproduce old +environments based only on your VCS history, and ensures that any compatibility +problems in new releases can be handled when it suits you.

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Direct dependencies

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HypoFuzz’s direct dependencies are:

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install_requires = [
+        "black >= 23.3.0",
+        "coverage >= 5.2.1",
+        "dash >= 2.0.0",
+        "hypothesis[cli] >= 6.93.2",
+        "libcst >= 1.0.0",
+        "pandas >= 1.0.0",
+        "psutil >= 3.0.0",
+        "pytest >= 6.0.1",
+        "requests >= 2.24.0",
+]
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API deprecation policy

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The command-line interface will not make incompatible changes without at least +three months notice, during which passing deprecated options will emit runtime +warnings (e.g. via the terminal, displayed on the dashboard, etc.).

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User-accesible integration points with Hypothesis, such as the +ExampleDatabase API, are considered +stable upstream and are unlikely to change even in major version releases.

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If it is impractical to continue to support old versions of Hypothesis (or other +dependencies) after a major update, the minimum supported version will be updated. +If you would like to use new versions of HypoFuzz with old versions of its +dependencies, please get in touch to discuss your specific needs.

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© Copyright 2024, Zac Hatfield-Dodds.

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efficient differential testing": [[4, "nezha-efficient-differential-testing"]], "Domain-specific targets with FuzzFactory": [[4, "domain-specific-targets-with-fuzzfactory"]], "Virtual branches with IJON": [[4, "virtual-branches-with-ijon"]], "Diversity": [[4, "diversity"]], "Coverage": [[4, "coverage"]], "Reducing coverage overhead by rewriting the target": [[4, "reducing-coverage-overhead-by-rewriting-the-target"]], "Faster coverage measurement for Python": [[4, "faster-coverage-measurement-for-python"]], "Sensitive coverage metrics": [[4, "sensitive-coverage-metrics"]], "Compressing coverage information": [[4, "compressing-coverage-information"]], "Miscellaneous": [[4, "miscellaneous"]], "Ensemble fuzzing with seed sharing": [[4, "ensemble-fuzzing-with-seed-sharing"]], "Hybrid concrete/symbolic fuzzing": [[4, "hybrid-concrete-symbolic-fuzzing"]], "Scaling fuzzers up to many cores": [[4, "scaling-fuzzers-up-to-many-cores"]], "Visualising fuzzer performance": [[4, "visualising-fuzzer-performance"]], "References": [[4, "references"]], "Quickstart guide": [[5, "quickstart-guide"]], "Prerequisites: pytest & hypothesis": [[5, "prerequisites-pytest-hypothesis"]], "Installation": [[5, "installation"]], "Running hypothesis fuzz": [[5, "running-hypothesis-fuzz"]], "Reproducing and fixing bugs": [[5, "reproducing-and-fixing-bugs"]], "A quick glance under the hood": [[5, "a-quick-glance-under-the-hood"]], "Development roadmap": [[6, "development-roadmap"]], "Compatibility policy": [[6, "compatibility-policy"]], "Direct dependencies": [[6, "direct-dependencies"]], "API deprecation policy": [[6, "api-deprecation-policy"]]}, "indexentries": {}}) \ No newline at end of file