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Diffstat (limited to 'tools/fuzzing/libfuzzer/FuzzerCorpus.h')
| -rw-r--r-- | tools/fuzzing/libfuzzer/FuzzerCorpus.h | 533 |
1 files changed, 533 insertions, 0 deletions
diff --git a/tools/fuzzing/libfuzzer/FuzzerCorpus.h b/tools/fuzzing/libfuzzer/FuzzerCorpus.h new file mode 100644 index 0000000000..54d1e09ec6 --- /dev/null +++ b/tools/fuzzing/libfuzzer/FuzzerCorpus.h @@ -0,0 +1,533 @@ +//===- FuzzerCorpus.h - Internal header for the Fuzzer ----------*- C++ -* ===// +// +// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. +// See https://llvm.org/LICENSE.txt for license information. +// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception +// +//===----------------------------------------------------------------------===// +// fuzzer::InputCorpus +//===----------------------------------------------------------------------===// + +#ifndef LLVM_FUZZER_CORPUS +#define LLVM_FUZZER_CORPUS + +#include "FuzzerDataFlowTrace.h" +#include "FuzzerDefs.h" +#include "FuzzerIO.h" +#include "FuzzerRandom.h" +#include "FuzzerSHA1.h" +#include "FuzzerTracePC.h" +#include <algorithm> +#include <numeric> +#include <random> +#include <unordered_set> + +namespace fuzzer { + +struct InputInfo { + Unit U; // The actual input data. + uint8_t Sha1[kSHA1NumBytes]; // Checksum. + // Number of features that this input has and no smaller input has. + size_t NumFeatures = 0; + size_t Tmp = 0; // Used by ValidateFeatureSet. + // Stats. + size_t NumExecutedMutations = 0; + size_t NumSuccessfullMutations = 0; + bool MayDeleteFile = false; + bool Reduced = false; + bool HasFocusFunction = false; + Vector<uint32_t> UniqFeatureSet; + Vector<uint8_t> DataFlowTraceForFocusFunction; + // Power schedule. + bool NeedsEnergyUpdate = false; + double Energy = 0.0; + size_t SumIncidence = 0; + Vector<std::pair<uint32_t, uint16_t>> FeatureFreqs; + + // Delete feature Idx and its frequency from FeatureFreqs. + bool DeleteFeatureFreq(uint32_t Idx) { + if (FeatureFreqs.empty()) + return false; + + // Binary search over local feature frequencies sorted by index. + auto Lower = std::lower_bound(FeatureFreqs.begin(), FeatureFreqs.end(), + std::pair<uint32_t, uint16_t>(Idx, 0)); + + if (Lower != FeatureFreqs.end() && Lower->first == Idx) { + FeatureFreqs.erase(Lower); + return true; + } + return false; + } + + // Assign more energy to a high-entropy seed, i.e., that reveals more + // information about the globally rare features in the neighborhood + // of the seed. Since we do not know the entropy of a seed that has + // never been executed we assign fresh seeds maximum entropy and + // let II->Energy approach the true entropy from above. + void UpdateEnergy(size_t GlobalNumberOfFeatures) { + Energy = 0.0; + SumIncidence = 0; + + // Apply add-one smoothing to locally discovered features. + for (auto F : FeatureFreqs) { + size_t LocalIncidence = F.second + 1; + Energy -= LocalIncidence * logl(LocalIncidence); + SumIncidence += LocalIncidence; + } + + // Apply add-one smoothing to locally undiscovered features. + // PreciseEnergy -= 0; // since logl(1.0) == 0) + SumIncidence += (GlobalNumberOfFeatures - FeatureFreqs.size()); + + // Add a single locally abundant feature apply add-one smoothing. + size_t AbdIncidence = NumExecutedMutations + 1; + Energy -= AbdIncidence * logl(AbdIncidence); + SumIncidence += AbdIncidence; + + // Normalize. + if (SumIncidence != 0) + Energy = (Energy / SumIncidence) + logl(SumIncidence); + } + + // Increment the frequency of the feature Idx. + void UpdateFeatureFrequency(uint32_t Idx) { + NeedsEnergyUpdate = true; + + // The local feature frequencies is an ordered vector of pairs. + // If there are no local feature frequencies, push_back preserves order. + // Set the feature frequency for feature Idx32 to 1. + if (FeatureFreqs.empty()) { + FeatureFreqs.push_back(std::pair<uint32_t, uint16_t>(Idx, 1)); + return; + } + + // Binary search over local feature frequencies sorted by index. + auto Lower = std::lower_bound(FeatureFreqs.begin(), FeatureFreqs.end(), + std::pair<uint32_t, uint16_t>(Idx, 0)); + + // If feature Idx32 already exists, increment its frequency. + // Otherwise, insert a new pair right after the next lower index. + if (Lower != FeatureFreqs.end() && Lower->first == Idx) { + Lower->second++; + } else { + FeatureFreqs.insert(Lower, std::pair<uint32_t, uint16_t>(Idx, 1)); + } + } +}; + +struct EntropicOptions { + bool Enabled; + size_t NumberOfRarestFeatures; + size_t FeatureFrequencyThreshold; +}; + +class InputCorpus { + static const uint32_t kFeatureSetSize = 1 << 21; + static const uint8_t kMaxMutationFactor = 20; + static const size_t kSparseEnergyUpdates = 100; + + size_t NumExecutedMutations = 0; + + EntropicOptions Entropic; + +public: + InputCorpus(const std::string &OutputCorpus, EntropicOptions Entropic) + : Entropic(Entropic), OutputCorpus(OutputCorpus) { + memset(InputSizesPerFeature, 0, sizeof(InputSizesPerFeature)); + memset(SmallestElementPerFeature, 0, sizeof(SmallestElementPerFeature)); + } + ~InputCorpus() { + for (auto II : Inputs) + delete II; + } + size_t size() const { return Inputs.size(); } + size_t SizeInBytes() const { + size_t Res = 0; + for (auto II : Inputs) + Res += II->U.size(); + return Res; + } + size_t NumActiveUnits() const { + size_t Res = 0; + for (auto II : Inputs) + Res += !II->U.empty(); + return Res; + } + size_t MaxInputSize() const { + size_t Res = 0; + for (auto II : Inputs) + Res = std::max(Res, II->U.size()); + return Res; + } + void IncrementNumExecutedMutations() { NumExecutedMutations++; } + + size_t NumInputsThatTouchFocusFunction() { + return std::count_if(Inputs.begin(), Inputs.end(), [](const InputInfo *II) { + return II->HasFocusFunction; + }); + } + + size_t NumInputsWithDataFlowTrace() { + return std::count_if(Inputs.begin(), Inputs.end(), [](const InputInfo *II) { + return !II->DataFlowTraceForFocusFunction.empty(); + }); + } + + bool empty() const { return Inputs.empty(); } + const Unit &operator[] (size_t Idx) const { return Inputs[Idx]->U; } + InputInfo *AddToCorpus(const Unit &U, size_t NumFeatures, bool MayDeleteFile, + bool HasFocusFunction, + const Vector<uint32_t> &FeatureSet, + const DataFlowTrace &DFT, const InputInfo *BaseII) { + assert(!U.empty()); + if (FeatureDebug) + Printf("ADD_TO_CORPUS %zd NF %zd\n", Inputs.size(), NumFeatures); + Inputs.push_back(new InputInfo()); + InputInfo &II = *Inputs.back(); + II.U = U; + II.NumFeatures = NumFeatures; + II.MayDeleteFile = MayDeleteFile; + II.UniqFeatureSet = FeatureSet; + II.HasFocusFunction = HasFocusFunction; + // Assign maximal energy to the new seed. + II.Energy = RareFeatures.empty() ? 1.0 : log(RareFeatures.size()); + II.SumIncidence = RareFeatures.size(); + II.NeedsEnergyUpdate = false; + std::sort(II.UniqFeatureSet.begin(), II.UniqFeatureSet.end()); + ComputeSHA1(U.data(), U.size(), II.Sha1); + auto Sha1Str = Sha1ToString(II.Sha1); + Hashes.insert(Sha1Str); + if (HasFocusFunction) + if (auto V = DFT.Get(Sha1Str)) + II.DataFlowTraceForFocusFunction = *V; + // This is a gross heuristic. + // Ideally, when we add an element to a corpus we need to know its DFT. + // But if we don't, we'll use the DFT of its base input. + if (II.DataFlowTraceForFocusFunction.empty() && BaseII) + II.DataFlowTraceForFocusFunction = BaseII->DataFlowTraceForFocusFunction; + DistributionNeedsUpdate = true; + PrintCorpus(); + // ValidateFeatureSet(); + return &II; + } + + // Debug-only + void PrintUnit(const Unit &U) { + if (!FeatureDebug) return; + for (uint8_t C : U) { + if (C != 'F' && C != 'U' && C != 'Z') + C = '.'; + Printf("%c", C); + } + } + + // Debug-only + void PrintFeatureSet(const Vector<uint32_t> &FeatureSet) { + if (!FeatureDebug) return; + Printf("{"); + for (uint32_t Feature: FeatureSet) + Printf("%u,", Feature); + Printf("}"); + } + + // Debug-only + void PrintCorpus() { + if (!FeatureDebug) return; + Printf("======= CORPUS:\n"); + int i = 0; + for (auto II : Inputs) { + if (std::find(II->U.begin(), II->U.end(), 'F') != II->U.end()) { + Printf("[%2d] ", i); + Printf("%s sz=%zd ", Sha1ToString(II->Sha1).c_str(), II->U.size()); + PrintUnit(II->U); + Printf(" "); + PrintFeatureSet(II->UniqFeatureSet); + Printf("\n"); + } + i++; + } + } + + void Replace(InputInfo *II, const Unit &U) { + assert(II->U.size() > U.size()); + Hashes.erase(Sha1ToString(II->Sha1)); + DeleteFile(*II); + ComputeSHA1(U.data(), U.size(), II->Sha1); + Hashes.insert(Sha1ToString(II->Sha1)); + II->U = U; + II->Reduced = true; + DistributionNeedsUpdate = true; + } + + bool HasUnit(const Unit &U) { return Hashes.count(Hash(U)); } + bool HasUnit(const std::string &H) { return Hashes.count(H); } + InputInfo &ChooseUnitToMutate(Random &Rand) { + InputInfo &II = *Inputs[ChooseUnitIdxToMutate(Rand)]; + assert(!II.U.empty()); + return II; + } + + // Returns an index of random unit from the corpus to mutate. + size_t ChooseUnitIdxToMutate(Random &Rand) { + UpdateCorpusDistribution(Rand); + size_t Idx = static_cast<size_t>(CorpusDistribution(Rand)); + assert(Idx < Inputs.size()); + return Idx; + } + + void PrintStats() { + for (size_t i = 0; i < Inputs.size(); i++) { + const auto &II = *Inputs[i]; + Printf(" [% 3zd %s] sz: % 5zd runs: % 5zd succ: % 5zd focus: %d\n", i, + Sha1ToString(II.Sha1).c_str(), II.U.size(), + II.NumExecutedMutations, II.NumSuccessfullMutations, II.HasFocusFunction); + } + } + + void PrintFeatureSet() { + for (size_t i = 0; i < kFeatureSetSize; i++) { + if(size_t Sz = GetFeature(i)) + Printf("[%zd: id %zd sz%zd] ", i, SmallestElementPerFeature[i], Sz); + } + Printf("\n\t"); + for (size_t i = 0; i < Inputs.size(); i++) + if (size_t N = Inputs[i]->NumFeatures) + Printf(" %zd=>%zd ", i, N); + Printf("\n"); + } + + void DeleteFile(const InputInfo &II) { + if (!OutputCorpus.empty() && II.MayDeleteFile) + RemoveFile(DirPlusFile(OutputCorpus, Sha1ToString(II.Sha1))); + } + + void DeleteInput(size_t Idx) { + InputInfo &II = *Inputs[Idx]; + DeleteFile(II); + Unit().swap(II.U); + II.Energy = 0.0; + II.NeedsEnergyUpdate = false; + DistributionNeedsUpdate = true; + if (FeatureDebug) + Printf("EVICTED %zd\n", Idx); + } + + void AddRareFeature(uint32_t Idx) { + // Maintain *at least* TopXRarestFeatures many rare features + // and all features with a frequency below ConsideredRare. + // Remove all other features. + while (RareFeatures.size() > Entropic.NumberOfRarestFeatures && + FreqOfMostAbundantRareFeature > Entropic.FeatureFrequencyThreshold) { + + // Find most and second most abbundant feature. + uint32_t MostAbundantRareFeatureIndices[2] = {RareFeatures[0], + RareFeatures[0]}; + size_t Delete = 0; + for (size_t i = 0; i < RareFeatures.size(); i++) { + uint32_t Idx2 = RareFeatures[i]; + if (GlobalFeatureFreqs[Idx2] >= + GlobalFeatureFreqs[MostAbundantRareFeatureIndices[0]]) { + MostAbundantRareFeatureIndices[1] = MostAbundantRareFeatureIndices[0]; + MostAbundantRareFeatureIndices[0] = Idx2; + Delete = i; + } + } + + // Remove most abundant rare feature. + RareFeatures[Delete] = RareFeatures.back(); + RareFeatures.pop_back(); + + for (auto II : Inputs) { + if (II->DeleteFeatureFreq(MostAbundantRareFeatureIndices[0])) + II->NeedsEnergyUpdate = true; + } + + // Set 2nd most abundant as the new most abundant feature count. + FreqOfMostAbundantRareFeature = + GlobalFeatureFreqs[MostAbundantRareFeatureIndices[1]]; + } + + // Add rare feature, handle collisions, and update energy. + RareFeatures.push_back(Idx); + GlobalFeatureFreqs[Idx] = 0; + for (auto II : Inputs) { + II->DeleteFeatureFreq(Idx); + + // Apply add-one smoothing to this locally undiscovered feature. + // Zero energy seeds will never be fuzzed and remain zero energy. + if (II->Energy > 0.0) { + II->SumIncidence += 1; + II->Energy += logl(II->SumIncidence) / II->SumIncidence; + } + } + + DistributionNeedsUpdate = true; + } + + bool AddFeature(size_t Idx, uint32_t NewSize, bool Shrink) { + assert(NewSize); + Idx = Idx % kFeatureSetSize; + uint32_t OldSize = GetFeature(Idx); + if (OldSize == 0 || (Shrink && OldSize > NewSize)) { + if (OldSize > 0) { + size_t OldIdx = SmallestElementPerFeature[Idx]; + InputInfo &II = *Inputs[OldIdx]; + assert(II.NumFeatures > 0); + II.NumFeatures--; + if (II.NumFeatures == 0) + DeleteInput(OldIdx); + } else { + NumAddedFeatures++; + if (Entropic.Enabled) + AddRareFeature((uint32_t)Idx); + } + NumUpdatedFeatures++; + if (FeatureDebug) + Printf("ADD FEATURE %zd sz %d\n", Idx, NewSize); + SmallestElementPerFeature[Idx] = Inputs.size(); + InputSizesPerFeature[Idx] = NewSize; + return true; + } + return false; + } + + // Increment frequency of feature Idx globally and locally. + void UpdateFeatureFrequency(InputInfo *II, size_t Idx) { + uint32_t Idx32 = Idx % kFeatureSetSize; + + // Saturated increment. + if (GlobalFeatureFreqs[Idx32] == 0xFFFF) + return; + uint16_t Freq = GlobalFeatureFreqs[Idx32]++; + + // Skip if abundant. + if (Freq > FreqOfMostAbundantRareFeature || + std::find(RareFeatures.begin(), RareFeatures.end(), Idx32) == + RareFeatures.end()) + return; + + // Update global frequencies. + if (Freq == FreqOfMostAbundantRareFeature) + FreqOfMostAbundantRareFeature++; + + // Update local frequencies. + if (II) + II->UpdateFeatureFrequency(Idx32); + } + + size_t NumFeatures() const { return NumAddedFeatures; } + size_t NumFeatureUpdates() const { return NumUpdatedFeatures; } + +private: + + static const bool FeatureDebug = false; + + size_t GetFeature(size_t Idx) const { return InputSizesPerFeature[Idx]; } + + void ValidateFeatureSet() { + if (FeatureDebug) + PrintFeatureSet(); + for (size_t Idx = 0; Idx < kFeatureSetSize; Idx++) + if (GetFeature(Idx)) + Inputs[SmallestElementPerFeature[Idx]]->Tmp++; + for (auto II: Inputs) { + if (II->Tmp != II->NumFeatures) + Printf("ZZZ %zd %zd\n", II->Tmp, II->NumFeatures); + assert(II->Tmp == II->NumFeatures); + II->Tmp = 0; + } + } + + // Updates the probability distribution for the units in the corpus. + // Must be called whenever the corpus or unit weights are changed. + // + // Hypothesis: inputs that maximize information about globally rare features + // are interesting. + void UpdateCorpusDistribution(Random &Rand) { + // Skip update if no seeds or rare features were added/deleted. + // Sparse updates for local change of feature frequencies, + // i.e., randomly do not skip. + if (!DistributionNeedsUpdate && + (!Entropic.Enabled || Rand(kSparseEnergyUpdates))) + return; + + DistributionNeedsUpdate = false; + + size_t N = Inputs.size(); + assert(N); + Intervals.resize(N + 1); + Weights.resize(N); + std::iota(Intervals.begin(), Intervals.end(), 0); + + bool VanillaSchedule = true; + if (Entropic.Enabled) { + for (auto II : Inputs) { + if (II->NeedsEnergyUpdate && II->Energy != 0.0) { + II->NeedsEnergyUpdate = false; + II->UpdateEnergy(RareFeatures.size()); + } + } + + for (size_t i = 0; i < N; i++) { + + if (Inputs[i]->NumFeatures == 0) { + // If the seed doesn't represent any features, assign zero energy. + Weights[i] = 0.; + } else if (Inputs[i]->NumExecutedMutations / kMaxMutationFactor > + NumExecutedMutations / Inputs.size()) { + // If the seed was fuzzed a lot more than average, assign zero energy. + Weights[i] = 0.; + } else { + // Otherwise, simply assign the computed energy. + Weights[i] = Inputs[i]->Energy; + } + + // If energy for all seeds is zero, fall back to vanilla schedule. + if (Weights[i] > 0.0) + VanillaSchedule = false; + } + } + + if (VanillaSchedule) { + for (size_t i = 0; i < N; i++) + Weights[i] = Inputs[i]->NumFeatures + ? (i + 1) * (Inputs[i]->HasFocusFunction ? 1000 : 1) + : 0.; + } + + if (FeatureDebug) { + for (size_t i = 0; i < N; i++) + Printf("%zd ", Inputs[i]->NumFeatures); + Printf("SCORE\n"); + for (size_t i = 0; i < N; i++) + Printf("%f ", Weights[i]); + Printf("Weights\n"); + } + CorpusDistribution = std::piecewise_constant_distribution<double>( + Intervals.begin(), Intervals.end(), Weights.begin()); + } + std::piecewise_constant_distribution<double> CorpusDistribution; + + Vector<double> Intervals; + Vector<double> Weights; + + std::unordered_set<std::string> Hashes; + Vector<InputInfo*> Inputs; + + size_t NumAddedFeatures = 0; + size_t NumUpdatedFeatures = 0; + uint32_t InputSizesPerFeature[kFeatureSetSize]; + uint32_t SmallestElementPerFeature[kFeatureSetSize]; + + bool DistributionNeedsUpdate = true; + uint16_t FreqOfMostAbundantRareFeature = 0; + uint16_t GlobalFeatureFreqs[kFeatureSetSize] = {}; + Vector<uint32_t> RareFeatures; + + std::string OutputCorpus; +}; + +} // namespace fuzzer + +#endif // LLVM_FUZZER_CORPUS |