Coverage Analysis
Measures and interprets what a fuzzing campaign actually reaches, using llvm-cov, lcov...
Install
npx skills add trailofbits/skills --skill coverage-analysis -g -a claude-code -y- Repository
- trailofbits/skills7.9k
- Category
- Engineering
- Updated
- 7d ago
- License
- CC-BY-SA-4.0
- Context cost
- Mediumabout 3,000 tokens
- Runs scripts
- No, instructions only
What it does
Measures and interprets what a fuzzing campaign actually reaches, using llvm-cov, lcov, or a fuzzer's own coverage output. Covers baselining a new campaign, reading coverage reports, and turning uncovered regions into harness, seed, or dictionary work. Use when a fuzzer plateaus, when judging whether a harness is effective, after changing a harness, or when asking why some code is never reached.
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
