blob: 05d6412ff42092f28f881bc54b32c24861a3256a [file]
// Copyright 2023 The Centipede Authors.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// https://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "./centipede/distill.h"
#include <algorithm>
#include <cstddef>
#include <cstdlib>
#include <functional>
#include <memory>
#include <numeric>
#include <optional>
#include <sstream>
#include <string>
#include <string_view>
#include <thread> // NOLINT(build/c++11)
#include <utility>
#include <vector>
#include "absl/base/thread_annotations.h"
#include "absl/log/check.h"
#include "absl/log/log.h"
#include "absl/strings/str_cat.h"
#include "absl/synchronization/mutex.h"
#include "absl/time/time.h"
#include "./centipede/blob_file.h"
#include "./centipede/defs.h"
#include "./centipede/environment.h"
#include "./centipede/feature.h"
#include "./centipede/feature_set.h"
#include "./centipede/logging.h"
#include "./centipede/rusage_profiler.h"
#include "./centipede/shard_reader.h"
#include "./centipede/thread_pool.h"
#include "./centipede/util.h"
#include "./centipede/workdir.h"
namespace centipede {
namespace {
struct CorpusElt {
ByteArray input;
FeatureVec features;
CorpusElt(const ByteArray &input, FeatureVec features)
: input(input), features(std::move(features)) {}
// Movable, but not copyable for efficiency.
CorpusElt(const CorpusElt &) = delete;
CorpusElt &operator=(const CorpusElt &) = delete;
CorpusElt(CorpusElt &&) = default;
CorpusElt &operator=(CorpusElt &&) = default;
ByteArray PackedFeatures() const {
return PackFeaturesAndHash(input, features);
}
};
using CorpusEltVec = std::vector<CorpusElt>;
// The maximum number of threads reading input shards concurrently. This is
// mainly to prevent I/O congestion.
// TODO(ussuri): Bump up significantly when RSS-gated mutexing is in.
inline constexpr size_t kMaxReadingThreads = 1;
std::string LogPrefix(const Environment &env) {
return absl::StrCat("DISTILL[S.", env.my_shard_index, "]: ");
}
// TODO(ussuri): Move the reader/writer classes to shard_reader.cc, rename it
// to corpus_io.cc, and reuse the new APIs where useful in the code base.
// A helper class for reading input corpus shards. Thread-safe.
class InputCorpusShardReader {
public:
InputCorpusShardReader(const Environment &env)
: workdir_{env}, log_prefix_{LogPrefix(env)} {}
// Reads and returns a single shard's elements. Thread-safe.
CorpusEltVec ReadShard(size_t shard_idx) {
const auto corpus_path = workdir_.CorpusFiles().ShardPath(shard_idx);
const auto features_path = workdir_.FeaturesFiles().ShardPath(shard_idx);
VLOG(1) << log_prefix_ << "reading input shard " << shard_idx << ":\n"
<< VV(corpus_path) << "\n"
<< VV(features_path);
CorpusEltVec elts;
// Read elements from the current shard.
centipede::ReadShard( //
corpus_path, features_path,
[&elts](const ByteArray &input, FeatureVec &features) {
elts.emplace_back(input, std::move(features));
});
return elts;
}
private:
const WorkDir workdir_;
const std::string log_prefix_;
};
// A helper class for writing corpus shards. Thread-safe.
class CorpusShardWriter {
public:
// The writing stats so far.
struct Stats {
size_t num_total_elts = 0;
size_t num_written_elts = 0;
size_t num_written_batches = 0;
};
CorpusShardWriter(const Environment &env, bool append)
: workdir_{env},
log_prefix_{LogPrefix(env)},
corpus_path_{workdir_.DistilledCorpusFiles().MyShardPath()},
features_path_{workdir_.DistilledFeaturesFiles().MyShardPath()},
corpus_writer_{DefaultBlobFileWriterFactory()},
feature_writer_{DefaultBlobFileWriterFactory()} {
CHECK_OK(corpus_writer_->Open(corpus_path_, append ? "a" : "w"));
CHECK_OK(feature_writer_->Open(features_path_, append ? "a" : "w"));
}
virtual ~CorpusShardWriter() = default;
void WriteElt(CorpusElt elt) {
absl::MutexLock lock(&mu_);
WriteEltImpl(std::move(elt));
}
void WriteBatch(CorpusEltVec elts) {
absl::MutexLock lock(&mu_);
VLOG(1) << log_prefix_ << "writing " << elts.size()
<< " elements to output shard:\n"
<< VV(corpus_path_) << "\n"
<< VV(features_path_);
for (auto &elt : elts) {
WriteEltImpl(std::move(elt));
}
++stats_.num_written_batches;
}
Stats GetStats() const {
absl::MutexLock lock(&mu_);
return stats_;
}
protected:
// A behavior customization point: a derived class gets an opportunity to
// analyze and/or preprocess `elt` before it is written. For example, a
// derived class can trim the element's feature set before it is written, or
// choose to skip writing it entirely by returning `std::nullopt`.
virtual std::optional<CorpusElt> PreprocessElt(CorpusElt elt) {
return std::move(elt);
}
private:
void WriteEltImpl(CorpusElt elt) ABSL_EXCLUSIVE_LOCKS_REQUIRED(mu_) {
++stats_.num_total_elts;
const auto preprocessed_elt = PreprocessElt(std::move(elt));
if (preprocessed_elt.has_value()) {
// Append to the distilled corpus and features files.
CHECK_OK(corpus_writer_->Write(preprocessed_elt->input));
CHECK_OK(feature_writer_->Write(preprocessed_elt->PackedFeatures()));
++stats_.num_written_elts;
}
}
// Const state.
const WorkDir workdir_;
const std::string log_prefix_;
const std::string corpus_path_;
const std::string features_path_;
// Mutable state.
mutable absl::Mutex mu_;
std::unique_ptr<BlobFileWriter> corpus_writer_ ABSL_GUARDED_BY(mu_);
std::unique_ptr<BlobFileWriter> feature_writer_ ABSL_GUARDED_BY(mu_);
Stats stats_ ABSL_GUARDED_BY(mu_);
};
// A helper class for writing distilled corpus shards. NOT thread-safe because
// all writes go to a single file.
class DistilledCorpusShardWriter : public CorpusShardWriter {
public:
// An extension to the parent class's `Stats`.
struct DistilledStats {
// The accumulated features of the distilled corpus so far, represents in
// the same compact textual form that Centipede uses in its fuzzing progress
// log messages, e.g.: "ft: 96331 cov: 81793 usr1: 5045 ...".
std::string coverage_str;
};
DistilledCorpusShardWriter(const Environment &env, bool append)
: CorpusShardWriter{env, append},
feature_set_{/*frequency_threshold=*/1, env.MakeDomainDiscardMask()} {}
~DistilledCorpusShardWriter() override = default;
DistilledStats GetDistilledStats() const {
absl::MutexLock lock(&mu_);
DistilledStats stats;
std::stringstream coverage_ss;
coverage_ss << feature_set_;
stats.coverage_str = coverage_ss.str();
return stats;
}
protected:
std::optional<CorpusElt> PreprocessElt(CorpusElt elt) override {
absl::MutexLock lock(&mu_);
feature_set_.PruneDiscardedDomains(elt.features);
if (!feature_set_.HasUnseenFeatures(elt.features)) return std::nullopt;
feature_set_.IncrementFrequencies(elt.features);
return std::move(elt);
}
private:
mutable absl::Mutex mu_;
FeatureSet feature_set_ ABSL_GUARDED_BY(mu_);
};
} // namespace
void DistillTask(const Environment &env,
const std::vector<size_t> &shard_indices) {
// Read and write the shards in parallel, but gate reading of each on the
// availability of free RAM to keep the peak RAM usage under control.
const size_t num_shards = shard_indices.size();
InputCorpusShardReader reader{env};
// NOTE: Always overwrite corpus and features files, never append.
DistilledCorpusShardWriter writer{env, /*append=*/false};
{
ThreadPool threads{kMaxReadingThreads};
for (size_t shard_idx : shard_indices) {
threads.Schedule([shard_idx, &reader, &writer, &env, num_shards] {
CorpusEltVec shard_elts = reader.ReadShard(shard_idx);
// Reverse the order of elements. The intuition is as follows:
// * If the shard is the result of fuzzing with Centipede, the inputs
// that are closer to the end are more interesting, so we start there.
// * If the shard resulted from somethening else, the reverse order is
// not any better or worse than any other order.
std::reverse(shard_elts.begin(), shard_elts.end());
writer.WriteBatch(std::move(shard_elts));
const auto stats = writer.GetStats();
const auto distilled_stats = writer.GetDistilledStats();
LOG(INFO) << LogPrefix(env) << distilled_stats.coverage_str
<< " batches: " << stats.num_written_batches << "/"
<< num_shards << " inputs: " << stats.num_total_elts
<< " distilled: " << stats.num_written_elts;
});
}
} // The reading threads join here.
}
int Distill(const Environment &env) {
RPROF_THIS_FUNCTION_WITH_TIMELAPSE( //
/*enable=*/VLOG_IS_ON(1), //
/*timelapse_interval=*/absl::Seconds(VLOG_IS_ON(2) ? 10 : 60), //
/*also_log_timelapses=*/VLOG_IS_ON(10));
// Run `env.num_threads` independent distillation threads.
std::vector<std::thread> threads(env.num_threads);
std::vector<Environment> envs(env.num_threads, env);
std::vector<std::vector<size_t>> shard_indices_per_thread(env.num_threads);
// Start the threads.
for (size_t thread_idx = 0; thread_idx < env.num_threads; ++thread_idx) {
envs[thread_idx].my_shard_index += thread_idx;
// Shuffle the shards, so that every thread produces different result.
Rng rng(GetRandomSeed(env.seed + thread_idx));
auto &shard_indices = shard_indices_per_thread[thread_idx];
shard_indices.resize(env.total_shards);
std::iota(shard_indices.begin(), shard_indices.end(), 0);
std::shuffle(shard_indices.begin(), shard_indices.end(), rng);
// Run the thread.
threads[thread_idx] =
std::thread(DistillTask, std::ref(envs[thread_idx]), shard_indices);
}
// Join threads.
for (size_t thread_idx = 0; thread_idx < env.num_threads; thread_idx++) {
threads[thread_idx].join();
}
return EXIT_SUCCESS;
}
} // namespace centipede