Analyze code coverage from fuzzing campaigns to assess harness effectiveness.
npx skills add https://github.com/iiammae/opero --skill coverage-analysis-iiammae
Please help me install this Agent Skill. Skill: coverage-analysis Source: https://github.com/iiammae/opero/tree/main/.agents/skills/coverage-analysis Command: npx skills add https://github.com/iiammae/opero --skill coverage-analysis-iiammae
Coverage analysis helps you understand which parts of your code are being exercised during fuzzing, allowing you to assess harness effectiveness and identify potential blockers.
Run the coverage analysis Skill on your fuzzing campaign with the command: coverage-analysis run -c corpus -b baseline.
High-intent search queries and answers about installing and using this skill.
To measure code coverage in fuzzing campaigns, you can automate analysis using this Skill to evaluate which application parts are executed by fuzzing harnesses. It supports multiple fuzzers and tools like LLVM and GCC to assess harness effectiveness.
Identifying fuzzing blockers during code coverage analysis involves discovering magic value checks and other conditions that hinder fuzzing progress. This Skill automates the detection of these blockers to help evaluate harness effectiveness.
Yes, you can track fuzzing progress and establish a baseline for a new campaign by monitoring how coverage changes with updates to harnesses, fuzzers, or the system under test. Run the analysis using your corpus and baseline inputs.
Yes, code coverage analysis works with both LLVM and GCC coverage tools. The Skill supports multiple fuzzers and code coverage tools, allowing you to assess harness effectiveness across different fuzzing environments.
Yes, you need knowledge of the fuzzer's input format and the system under test to run code coverage analysis. This prerequisite knowledge is required to properly automate the evaluation of harness effectiveness.
To verify harness improvements after migrating between different fuzzers, use this Skill to compare code coverage results against your baseline. This allows you to track fuzzing progress and confirm the effectiveness of your new setup.
ayehiaaAnalyzes code coverage from fuzzing campaigns to identify gaps and bottlenecks.
erenisiklarIdentify and quantify LLVM/GCC code coverage during fuzzing to guide harness improvements for C/C++ and Rust targets.
mohitmishra786Configure GCC cross-compilation toolchains for ARM, RISC-V, and MIPS targets.
Ramprasad4121Analyze code coverage from LLVM and GCC fuzzing campaigns for C/C++ and Rust projects.
