fuzzing-test
SolidGenerate Go fuzz tests (Go 1.18+ testing.F) for specified code when users ask for fuzzing/模糊测试/fuzz test generation, parser robustness, round-trip, or differential fuzzing. Always run an applicability gate first; if the target is not suitable, explain concrete reasons and stop without writing fuzz test code.
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Quality Score: 85/100
Skill Content
Details
- Author
- johnqtcg
- Repository
- johnqtcg/awesome-skills
- Created
- 6 months ago
- Last Updated
- yesterday
- Language
- Python
- License
- MIT
Integrates with
Similar Skills
Semantically similar based on skill content — not just same category
fuzzgpt
Use when you want to fuzz any software target — library, compiler, interpreter, parser, kernel/syscall, DB engine, SMT solver, binary/file format, or network protocol — by priming an LLM with that target's HISTORICAL bug-triggering code to generate unusual, edge-case inputs (history-driven LLM fuzzing). FuzzGPT-derived: retrieval replaces fine-tuning (Deng et al., arXiv:2304.02014): mine bug reports → auto-label each snippet's buggy fuzz target → few-shot / zero-shot / retrieval generation → crash + differential oracles. Trigger on "FuzzGPT", "fuzz this library/compiler/parser/protocol", "generate edge-case test programs", "history-driven fuzzing", or when pairing with vuln-research to turn a target's bug history into fresh fuzzing inputs. Target-agnostic: the "fuzz target" is whatever unit you point generation at — an API in the paper's DL study, but equally a compiler flag, SQL feature, syscall, opcode, or protocol field.
offensive-fuzzing
Practical offensive fuzzing methodology covering target identification, fuzzer selection (AFL++, libFuzzer, Honggfuzz, Boofuzz, syzkaller), harness writing, corpus curation, mutation strategies, coverage measurement, and crash triage. Use when setting up or running fuzz campaigns against any target: file parsers, network protocols, kernel drivers, EDR engines, embedded firmware, or language runtimes.
offensive-fuzzing
Practical offensive fuzzing methodology covering target identification, fuzzer selection (AFL++, libFuzzer, Honggfuzz, Boofuzz, syzkaller), harness writing, corpus curation, mutation strategies, coverage measurement, and crash triage. Use when setting up or running fuzz campaigns against any target: file parsers, network protocols, kernel drivers, EDR engines, embedded firmware, or language runtimes.