Coverage Analysis
Coverage analysis is essential for understanding which parts of your code are exercised during fuzzing. It helps identify fuzzing blockers like magic value checks and tracks the effectiveness of harness improvements over time.
Overview
Code coverage during fuzzing serves two critical purposes:
Assessing harness effectiveness: Understand which parts of your application are actually executed by your fuzzing harnesses Tracking fuzzing progress: Monitor how coverage changes when updating harnesses, fuzzers, or the system under test (SUT)
Coverage is a proxy for fuzzer capability and performance. While coverage is not ideal for measuring fuzzer performance in absolute terms, it reliably indicates whether your harness works effectively in a given setup.
Key Concepts Concept Description Coverage instrumentation Compiler flags that track which code paths are executed Corpus coverage Coverage achieved by running all test cases in a fuzzing corpus Magic value checks Hard-to-discover conditional checks that block fuzzer progress Coverage-guided fuzzing Fuzzing strategy that prioritizes inputs that discover new code paths Coverage report Visual or textual representation of executed vs. unexecuted code When to Apply
Apply this technique when:
Starting a new fuzzing campaign to establish a baseline Fuzzer appears to plateau without finding new paths After harness modifications to verify improvements When migrating between different fuzzers Identifying areas requiring dictionary entries or seed inputs Debugging why certain code paths aren't reached
Skip this technique when:
Fuzzing campaign is actively finding crashes
Coverage infrastructure isn't set up yet
Working with extremely large codebases where full coverage reports are impractical
Fuzzer's internal coverage metrics are sufficient for your needs
Quick Reference
Task Command/Pattern
LLVM coverage instrumentation (C/C++) -fprofile-instr-generate -fcoverage-mapping
GCC coverage instrumentation -ftest-coverage -fprofile-arcs
cargo-fuzz coverage (Rust) cargo +nightly fuzz coverage
The following workflow represents best practices for integrating coverage analysis into your fuzzing campaigns:
[Fuzzing Campaign] | v [Generate Corpus] | v [Coverage Analysis] | +---> Coverage Increased? --> Continue fuzzing with larger corpus | +---> Coverage Decreased? --> Fix harness or investigate SUT changes | +---> Coverage Plateaued? --> Add dictionary entries or seed inputs
Key principle: Use the corpus generated after each fuzzing campaign to calculate coverage, rather than real-time fuzzer statistics. This approach provides reproducible, comparable measurements across different fuzzing tools.
Step-by-Step Step 1: Build with Coverage Instrumentation
Choose your instrumentation method based on toolchain:
LLVM/Clang (C/C++):
clang++ -fprofile-instr-generate -fcoverage-mapping \ -O2 -DNO_MAIN \ main.cc harness.cc execute-rt.cc -o fuzz_exec
GCC (C/C++):
g++ -ftest-coverage -fprofile-arcs \ -O2 -DNO_MAIN \ main.cc harness.cc execute-rt.cc -o fuzz_exec_gcov
Rust:
rustup toolchain install nightly --component llvm-tools-preview cargo +nightly fuzz coverage fuzz_target_1
Step 2: Create Execution Runtime (C/C++ only)
For C/C++ projects, create a runtime that executes your corpus:
// execute-rt.cc
include
include
include
include
extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size);
void load_file_and_test(const char filename) { FILE file = fopen(filename, "rb"); if (file == NULL) { printf("Failed to open file: %s\n", filename); return; }
fseek(file, 0, SEEK_END);
long filesize = ftell(file);
rewind(file);
uint8_t *buffer = (uint8_t*) malloc(filesize);
if (buffer == NULL) {
printf("Failed to allocate memory for file: %s\n", filename);
fclose(file);
return;
}
long read_size = (long) fread(buffer, 1, filesize, file);
if (read_size != filesize) {
printf("Failed to read file: %s\n", filename);
free(buffer);
fclose(file);
return;
}
LLVMFuzzerTestOneInput(buffer, filesize);
free(buffer);
fclose(file);
}
int main(int argc, char **argv) {
if (argc != 2) {
printf("Usage: %s
DIR *dir = opendir(argv[1]);
if (dir == NULL) {
printf("Failed to open directory: %s\n", argv[1]);
return 1;
}
struct dirent *entry;
while ((entry = readdir(dir)) != NULL) {
if (entry->d_type == DT_REG) {
char filepath[1024];
snprintf(filepath, sizeof(filepath), "%s/%s", argv[1], entry->d_name);
load_file_and_test(filepath);
}
}
closedir(dir);
return 0;
}
Step 3: Execute on Corpus
LLVM (C/C++):
LLVM_PROFILE_FILE=fuzz.profraw ./fuzz_exec corpus/
GCC (C/C++):
./fuzz_exec_gcov corpus/
Rust: Coverage data is automatically generated when running cargo fuzz coverage.
Step 4: Process Coverage Data
LLVM:
Merge raw profile data
llvm-profdata merge -sparse fuzz.profraw -o fuzz.profdata
Generate text report
llvm-cov report ./fuzz_exec \ -instr-profile=fuzz.profdata \ -ignore-filename-regex='harness.cc|execute-rt.cc'
Generate HTML report
llvm-cov show ./fuzz_exec \ -instr-profile=fuzz.profdata \ -ignore-filename-regex='harness.cc|execute-rt.cc' \ -format=html -output-dir fuzz_html/
GCC with gcovr:
Install gcovr (via pip for latest version)
python3 -m venv venv source venv/bin/activate pip3 install gcovr
Generate report
gcovr --gcov-executable "llvm-cov gcov" \ --exclude harness.cc --exclude execute-rt.cc \ --root . --html-details -o coverage.html
Rust:
Install required tools
cargo install cargo-binutils rustfilt
Create HTML generation script
cat <<'EOF' > ./generate_html
!/bin/sh
if [ $# -lt 1 ]; then echo "Error: Name of fuzz target is required." echo "Usage: $0 fuzz_target [sources...]" exit 1 fi FUZZ_TARGET="$1" shift SRC_FILTER="$@" TARGET=$(rustc -vV | sed -n 's|host: ||p') cargo +nightly cov -- show -Xdemangler=rustfilt \ "target/$TARGET/coverage/$TARGET/release/$FUZZ_TARGET" \ -instr-profile="fuzz/coverage/$FUZZ_TARGET/coverage.profdata" \ -show-line-counts-or-regions -show-instantiations \ -format=html -o fuzz_html/ $SRC_FILTER EOF chmod +x ./generate_html
Generate HTML report
./generate_html fuzz_target_1 src/lib.rs
Step 5: Analyze Results
Review the coverage report to identify:
Uncovered code blocks: Areas that may need better seed inputs or dictionary entries Magic value checks: Conditional statements with hardcoded values that block progress Dead code: Functions that may not be reachable through your harness Coverage changes: Compare against baseline to track improvements or regressions Common Patterns Pattern: Identifying Magic Values
Problem: Fuzzer cannot discover paths guarded by magic value checks.
Coverage reveals:
// Coverage shows this block is never executed if (buf == 0x7F454C46) { // ELF magic number // start parsing buf }
Solution: Add magic values to dictionary file:
magic.dict
"\x7F\x45\x4C\x46"
Pattern: Handling Crashing Inputs
Problem: Coverage generation fails when corpus contains crashing inputs.
Before:
./fuzz_exec corpus/ # Crashes on bad input, no coverage generated
After:
// Fork before executing to isolate crashes int main(int argc, char **argv) { // ... directory opening code ...
while ((entry = readdir(dir)) != NULL) {
if (entry->d_type == DT_REG) {
pid_t pid = fork();
if (pid == 0) {
// Child process - crash won't affect parent
char filepath[1024];
snprintf(filepath, sizeof(filepath), "%s/%s", argv[1], entry->d_name);
load_file_and_test(filepath);
exit(0);
} else {
// Parent waits for child
waitpid(pid, NULL, 0);
}
}
}
}
Pattern: CMake Integration
Use Case: Adding coverage builds to CMake projects.
project(FuzzingProject) cmake_minimum_required(VERSION 3.0)
Main binary
add_executable(program main.cc)
Fuzzing binary
add_executable(fuzz main.cc harness.cc) target_compile_definitions(fuzz PRIVATE NO_MAIN=1) target_compile_options(fuzz PRIVATE -g -O2 -fsanitize=fuzzer) target_link_libraries(fuzz -fsanitize=fuzzer)
Coverage execution binary
add_executable(fuzz_exec main.cc harness.cc execute-rt.cc) target_compile_definitions(fuzz_exec PRIVATE NO_MAIN) target_compile_options(fuzz_exec PRIVATE -O2 -fprofile-instr-generate -fcoverage-mapping) target_link_libraries(fuzz_exec -fprofile-instr-generate)
Build:
cmake -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ . cmake --build . --target fuzz_exec
Advanced Usage Tips and Tricks Tip Why It Helps Use LLVM 18+ with -show-directory-coverage Organizes large reports by directory structure instead of flat file list Export to lcov format for better HTML llvm-cov export -format=lcov + genhtml provides cleaner per-file reports Compare coverage across campaigns Store .profdata files with timestamps to track progress over time Filter harness code from reports Use -ignore-filename-regex to focus on SUT coverage only Automate coverage in CI/CD Generate coverage reports automatically after scheduled fuzzing runs Use gcovr 5.1+ for Clang 14+ Older gcovr versions have compatibility issues with recent LLVM Incremental Coverage Updates
GCC's gcov instrumentation incrementally updates .gcda files across multiple runs. This is useful for tracking coverage as you add test cases:
First run
./fuzz_exec_gcov corpus_batch_1/ gcovr --html coverage_v1.html
Second run (adds to existing coverage)
./fuzz_exec_gcov corpus_batch_2/ gcovr --html coverage_v2.html
Start fresh
gcovr --delete # Remove .gcda files ./fuzz_exec_gcov corpus/
Handling Large Codebases
For projects with hundreds of source files:
Filter by prefix: Only generate reports for relevant directories
llvm-cov show ./fuzz_exec -instr-profile=fuzz.profdata /path/to/src/
Use directory coverage: Group by directory to reduce clutter (LLVM 18+)
llvm-cov show -show-directory-coverage -format=html -output-dir html/
Generate JSON for programmatic analysis:
llvm-cov export -format=lcov > coverage.json
Differential Coverage
Compare coverage between two fuzzing campaigns:
Campaign 1
LLVM_PROFILE_FILE=campaign1.profraw ./fuzz_exec corpus1/ llvm-profdata merge -sparse campaign1.profraw -o campaign1.profdata
Campaign 2
LLVM_PROFILE_FILE=campaign2.profraw ./fuzz_exec corpus2/ llvm-profdata merge -sparse campaign2.profraw -o campaign2.profdata
Compare
llvm-cov show ./fuzz_exec \ -instr-profile=campaign2.profdata \ -instr-profile=campaign1.profdata \ -show-line-counts-or-regions
Anti-Patterns Anti-Pattern Problem Correct Approach Using fuzzer-reported coverage for comparisons Different fuzzers calculate coverage differently, making cross-tool comparison meaningless Use dedicated coverage tools (llvm-cov, gcovr) for reproducible measurements Generating coverage with optimizations -O3 optimizations can eliminate code, making coverage misleading Use -O2 or -O0 for coverage builds Not filtering harness code Harness coverage inflates numbers and obscures SUT coverage Use -ignore-filename-regex or --exclude to filter harness files Mixing LLVM and GCC instrumentation Incompatible formats cause parsing failures Stick to one toolchain for coverage builds Ignoring crashing inputs Crashes prevent coverage generation, hiding real coverage data Fix crashes first, or use process forking to isolate them Not tracking coverage over time One-time coverage checks miss regressions and improvements Store coverage data with timestamps and track trends Tool-Specific Guidance libFuzzer
libFuzzer uses LLVM's SanitizerCoverage by default for guiding fuzzing, but you need separate instrumentation for generating reports.
Build for coverage:
clang++ -fprofile-instr-generate -fcoverage-mapping \ -O2 -DNO_MAIN \ main.cc harness.cc execute-rt.cc -o fuzz_exec
Execute corpus and generate report:
LLVM_PROFILE_FILE=fuzz.profraw ./fuzz_exec corpus/ llvm-profdata merge -sparse fuzz.profraw -o fuzz.profdata llvm-cov show ./fuzz_exec -instr-profile=fuzz.profdata -format=html -output-dir html/
Integration tips:
Don't use -fsanitize=fuzzer for coverage builds (it conflicts with profile instrumentation) Reuse the same harness function (LLVMFuzzerTestOneInput) with a different main function Use the -ignore-filename-regex flag to exclude harness code from coverage reports Consider using llvm-cov's -show-instantiation flag for template-heavy C++ code AFL++
AFL++ provides its own coverage feedback mechanism, but for detailed reports use standard LLVM/GCC tools.
Build for coverage with LLVM:
clang++ -fprofile-instr-generate -fcoverage-mapping \ -O2 main.cc harness.cc execute-rt.cc -o fuzz_exec
Build for coverage with GCC:
AFL_USE_ASAN=0 afl-gcc -ftest-coverage -fprofile-arcs \ main.cc harness.cc execute-rt.cc -o fuzz_exec_gcov
Execute and generate report:
LLVM approach
LLVM_PROFILE_FILE=fuzz.profraw ./fuzz_exec afl_output/queue/ llvm-profdata merge -sparse fuzz.profraw -o fuzz.profdata llvm-cov report ./fuzz_exec -instr-profile=fuzz.profdata
GCC approach
./fuzz_exec_gcov afl_output/queue/ gcovr --html-details -o coverage.html
Integration tips:
Don't use AFL++'s instrumentation (afl-clang-fast) for coverage builds Use standard compilers with coverage flags instead AFL++'s queue/ directory contains your corpus AFL++'s built-in coverage statistics are useful for real-time monitoring but not for detailed analysis cargo-fuzz (Rust)
cargo-fuzz provides built-in coverage generation using LLVM tools.
Install prerequisites:
rustup toolchain install nightly --component llvm-tools-preview cargo install cargo-binutils rustfilt
Generate coverage data:
cargo +nightly fuzz coverage fuzz_target_1
Create HTML report script:
cat <<'EOF' > ./generate_html
!/bin/sh
FUZZ_TARGET="$1" shift SRC_FILTER="$@" TARGET=$(rustc -vV | sed -n 's|host: ||p') cargo +nightly cov -- show -Xdemangler=rustfilt \ "target/$TARGET/coverage/$TARGET/release/$FUZZ_TARGET" \ -instr-profile="fuzz/coverage/$FUZZ_TARGET/coverage.profdata" \ -show-line-counts-or-regions -show-instantiations \ -format=html -o fuzz_html/ $SRC_FILTER EOF chmod +x ./generate_html
Generate report:
./generate_html fuzz_target_1 src/lib.rs
Integration tips:
Always use the nightly toolchain for coverage
The -Xdemangler=rustfilt flag makes function names readable
Filter by source files (e.g., src/lib.rs) to focus on crate code
Use -show-line-counts-or-regions and -show-instantiations for better Rust-specific output
Corpus is located in fuzz/corpus/
honggfuzz works with standard LLVM/GCC coverage instrumentation.
Build for coverage:
Use standard compiler, not honggfuzz compiler
clang -fprofile-instr-generate -fcoverage-mapping \ -O2 harness.c execute-rt.c -o fuzz_exec
Execute corpus:
LLVM_PROFILE_FILE=fuzz.profraw ./fuzz_exec honggfuzz_workspace/
Integration tips:
Don't use hfuzz-clang for coverage builds honggfuzz corpus is typically in a workspace directory Use the same LLVM workflow as libFuzzer Troubleshooting Issue Cause Solution error: no profile data available Profile wasn't generated or wrong path Verify LLVM_PROFILE_FILE was set and .profraw file exists Failed to load coverage Mismatch between binary and profile data Rebuild binary with same flags used during execution Coverage reports show 0% Wrong binary used for report generation Use the instrumented binary, not the fuzzing binary no_working_dir_found error (gcovr) .gcda files in unexpected location Add --gcov-ignore-errors=no_working_dir_found flag Crashes prevent coverage generation Corpus contains crashing inputs Filter crashes or use forking approach to isolate failures Coverage decreases after harness change Harness now skips certain code paths Review harness logic; may need to support more input formats HTML report is flat file list Using older LLVM version Upgrade to LLVM 18+ and use -show-directory-coverage incompatible instrumentation Mixing LLVM and GCC coverage Rebuild everything with same toolchain Related Skills Tools That Use This Technique Skill How It Applies libfuzzer Uses SanitizerCoverage for feedback; coverage analysis evaluates harness effectiveness aflpp Uses edge coverage for feedback; detailed analysis requires separate instrumentation cargo-fuzz Built-in cargo fuzz coverage command for Rust projects honggfuzz Uses edge coverage; analyze with standard LLVM/GCC tools Related Techniques Skill Relationship fuzz-harness-writing Coverage reveals which code paths harness reaches; guides harness improvements fuzzing-dictionaries Coverage identifies magic value checks that need dictionary entries corpus-management Coverage analysis helps curate corpora by identifying redundant test cases sanitizers Coverage helps verify sanitizer-instrumented code is actually executed Resources Key External Resources
LLVM Source-Based Code Coverage Comprehensive guide to LLVM's profile instrumentation, including advanced features like branch coverage, region coverage, and integration with existing build systems. Covers compiler flags, runtime behavior, and profile data formats.
llvm-cov Command Guide Detailed CLI reference for llvm-cov commands including show, report, and export. Documents all filtering options, output formats, and integration with llvm-profdata.
gcovr Documentation Complete guide to gcovr tool for generating coverage reports from gcov data. Covers HTML themes, filtering options, multi-directory projects, and CI/CD integration patterns.
SanitizerCoverage Documentation Low-level documentation for LLVM's SanitizerCoverage instrumentation. Explains inline 8-bit counters, PC tables, and how fuzzers use coverage feedback for guidance.
On the Evaluation of Fuzzer Performance Research paper examining limitations of coverage as a fuzzing performance metric. Argues for more nuanced evaluation methods beyond simple code coverage percentages.
Video Resources
Not applicable - coverage analysis is primarily a tooling and workflow topic best learned through documentation and hands-on practice.