Proposal: Custom Fuzz Input Types

Author: Richard Hansen rhansen@rhansen.org

Last updated: 2023-06-08

Discussion at https://go.dev/issue/48815.

Abstract

Extend testing.F.Fuzz to support custom types, with their own custom mutation logic, as input parameters. This enables developers to perform structure-aware fuzzing.

Background

As of Go 1.20, testing.F.Fuzz only accepts fuzz functions that have basic parameter types: []byte, string, int, etc. Custom input types with custom mutation logic would make it easier to fuzz functions that take complex data structures as input.

It is technically possible to fuzz such functions using the basic types, but the benefit is limited:

  • A basic input type can be used as a pseudo-random number generator seed to generate a valid structure at test time. Downsides:
    • The seed, not the generated structure, is saved in testdata/fuzz/FuzzTestName/*. This makes it difficult for developers to examine the structure to figure out why it is interesting. It also means that a minor change to the structure generation algorithm can invalidate the entire seed corpus.
    • A problematic or interesting structure discovered or created outside of fuzzing cannot be added to the seed corpus.
    • F.Fuzz cannot distinguish the structure generation code from the code under test, so the structure generation code is instrumented and included in F.Fuzz's analysis. This causes unnecessary slowdowns and false positives (uninteresting inputs treated as interesting due to changed coverage).
    • F.Fuzz has limited ability to explore or avoid “similar” inputs in its pursuit of new execution paths. (Similar seeds produce pseudo-randomly independent structures.)
  • Multiple input values can be used to populate the fields of the complex structure. This has many of the same downsides as using a single seed input.
  • Raw input values can be cast as (an encoding of) the complex structure. For example, a []byte input could be interpreted as a protobuf. Depending on the specifics, the yield of this approach (the number of bugs it finds) is likely to be low due to the low probability of generating a syntactically and semantically valid structure. (Sometimes it is important to attempt invalid structures to exercise error handling and discover security vulnerabilities, but this does not apply to function call traces that are replayed to test a stateful system.)

See Structure-Aware Fuzzing with libFuzzer for additional background.

Proposal

Extend testing.F.Fuzz to accept fuzz functions with parameter types that implement the following interface (not exported, just documented in testing.F.Fuzz):

// A customMutator is a fuzz input value that is self-mutating. This interface
// extends the encoding.BinaryMarshaler and encoding.BinaryUnmarshaler
// interfaces.
type customMutator interface {
	// MarshalBinary encodes the customMutator's value in a platform-independent
	// way (e.g., JSON or Protocol Buffers).
	MarshalBinary() ([]byte, error)
	// UnmarshalBinary restores the customMutator's value from encoded data
	// previously returned from a call to MarshalBinary.
	UnmarshalBinary([]byte) error
	// Mutate pseudo-randomly transforms the customMutator's value. The mutation
	// must be repeatable: every call to Mutate with the same starting value and
	// seed must result in the same transformed value.
	Mutate(ctx context.Context, seed int64) error
}

Also extend the seed corpus file format to support custom values. A line for a custom value has the following form:

custom("type identifier here", []byte("marshal output here"))

The type identifier is a globally unique and stable identifier derived from the value's fully qualified type name, such as "*example.com/mod/pkg.myType".

Example Usage

package pkg_test

import (
	"encoding/json"
	"testing"

	"github.com/go-loremipsum/loremipsum"
)

type fuzzInput struct{ Word string }

func (v *fuzzInput) MarshalBinary() ([]byte, error) { return json.Marshal(v) }
func (v *fuzzInput) UnmarshalBinary(d []byte) error { return json.Unmarshal(d, v) }
func (v *fuzzInput) Mutate(ctx context.Context, seed int64) error {
	v.Word = loremipsum.NewWithSeed(seed).Word()
	return nil
}

func FuzzInput(f *testing.F) {
	f.Fuzz(func(t *testing.T, v *fuzzInput) {
		if v.Word == "lorem" {
			t.Fatal("boom!")
		}
	})
}

The fuzzer eventually encounters an input value that causes the test function to fail, and produces a seed corpus file in testdata/fuzz like the following:

go test fuzz v1
custom("*example.com/mod/pkg_test.fuzzInput", []byte("{\"Word\":\"lorem\"}"))

Rationale

Private interface

The customMutator interface is not exported for a few reasons:

  • Exporting is not strictly required because it does not appear anywhere outside of internal logic.

  • It can be easily exported in the future if needed. The opposite is not true: un-exporting requires a major version change.

  • YAGNI: Users are unlikely to want to declare anything with that type. One possible exception is a compile-time type check such as the following:

    var _ testing.CustomMutator = (*myType)(nil)
    

    Such a check is unlikely to have much value: the code is likely being compiled because tests are about to run, and testing.F.Fuzz's runtime check will immediately catch the bug.

  • Exporting now would add friction to extending testing.F.Fuzz again in the future. Should the new interface be exported even if doing so doesn't add much value beyond consistency?

MarshalBinary, UnmarshalBinary methods

Marshal and Unmarshal would be shorter to type than MarshalBinary and UnmarshalBinary, but the longer names make it easier to extend existing types that already implement the encoding.BinaryMarshaler and encoding.BinaryUnmarshaler interfaces.

MarshalText and UnmarshalText were considered but rejected because the most natural representation of a custom type might be binary, not text.

UnmarshalBinary is used both to load seed corpus files from disk and to transmit input values between the coordinator and its workers. Unmarshaling malformed data from disk is allowed to fail, but unmarshaling after transmission to another process is expected to always succeed.

MarshalBinary is used both to save seed corpus files to disk and to transmit input values between the coordinator and its workers. Marshaling is expected to always succeed. Despite this, it returns an error for several reasons:

  • to implement the encoding.BinaryMarshaler interface
  • for symmetry with UnmarshalBinary
  • to match the APIs provided by packages such as encoding/json and encoding/gob
  • to discourage the use of panic

Panicking is especially problematic because:

  • The coordinator process currently interprets a panic as a bug in the code under test, even if it happens outside of the test function.
  • Worker process stdout and stderr is currently suppressed, presumably to reduce the amount of output noise, so developers might not notice that a failure is caused by a panic in a custom input type's method.

Mutate method

The seed parameter is an int64, not an unsigned integer type as is common for holding random bits, because that is what math/rand.NewSource takes.

The Mutate method must be repeatable to avoid violating an assumption in the coordinator–worker protocol. This may be relaxed in the future by revising the protocol.

Some alternatives for the Mutate method were considered:

  • Mutate(): Simplest, but the lack of a seed parameter makes it difficult to satisfy the repeatability requirement.
  • Mutate(seed int64): Simple. Naturally hints to developers that the method is expected to be fast, repeatable, and error-free, which increases the effectiveness of fuzzing. Adding a context parameter or error return value (or both) might be YAGNI, but their absence makes complex mutation operations more difficult to implement. The lack of an error return value encourages the use of panic, which is problematic for the reasons discussed in the MarshalBinary rationale above.
  • Mutate(seed int64) error: The error return value discourages the use of panic, and enables better dev UX when debugging complex mutation operations.
  • Mutate(ctx context.Context, seed int64) error: The context makes this more future-proof by enabling advanced techniques once the repeatability requirement is removed. For example, Mutate could send an RPC to a service that feeds automatic crash report data to fuzzing tasks to increase the likelihood of encountering an interesting value. The context parameter and error return value might be YAGNI, but the added implementation complexity and developer cognitive load is believed to be minor enough to not worry about it (they can be ignored in most use cases).
  • Accept both Mutate(seed int64) and Mutate(ctx context.Context, seed int64) error: The second of the two can be added later after accumulating additional feedback from developers. Supporting both might result in unnecessary complexity.

Because mutation operations on custom types are expected to be somewhat complex (otherwise a basic type would probably suffice), the Mutate(ctx context.Context, seed int64) error option is believed to be the best choice.

Minimization

To simplify the initial implementation, input types are not minimizable. Minimizability could be added in the future by accepting a type like the following and calling its Minimize method:

// A customMinimizingMutator is a customMutator that supports attempts to reduce
// the size of an interesting value.
type customMinimizingMutator interface {
	customMutator
	// Minimize attempts to produce the smallest value (usually defined as
	// easiest to process by machine and/or humans) that still provides the same
	// coverage as the original value. It repeatedly generates candidates,
	// checking each one for suitability with the given callback. It returns
	// a suitable candidate if it is satisfied that the candidate is
	// sufficiently small or nil if it has given up searching.
	Minimize(seed int64, check func(candidate any) (bool, error)) (any, error)
}

Compatibility

No changes in behavior are expected with existing code and seed corpus files.

Implementation

See https://go.dev/cl/493304 for an initial attempt.

For the initial implementation, a worker can simply panic if one of the custom type's methods returns an error. A future change can improve UX by plumbing the error.

No particular Go release is targeted.