跳到正文
FunCoding

搜索

搜索文档、Skill 和 MCP

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.

文档与办公7.4kSkills/fuzzing/offensive-fuzzing/SKILL.md

安装

把这段话发给 Claude Code、Codex 或 Cursor。智能体会先检查安全性,你确认后才安装。

读取 https://funcoding.ai/skills/snailsploit/claude-red/offensive-fuzzing/install.md ,按里面的步骤帮我安装这个 Skill。

SKILL.md

Offensive Fuzzing

Fuzzer Types

TypeCoverageSpeedTools
BlackBoxPoorFastPeach, Boofuzz
GreyBoxGoodFastAFL++, Honggfuzz, libFuzzer, WinAFL
SnapshotGoodFastestNyx, wtf, Snapchange
WhiteBoxBestSlowKLEE, QSYM, SymSan
EnsembleBestFastAFL++ + Honggfuzz + libFuzzer

GreyBox sub-variants: Directed (AFLGo, UAFuzz), Grammar (AFLSmart, Tlspuffin), Concolic (QSYM, Driller), Kernel (syzkaller, kAFL, wtf).

Core Workflow

Research target → Choose analyses → Build harness → Seed corpus → Instrument → Fuzz → Triage crashes → Report

1. Research Target

  • Map all input surfaces (files, network, IPC, syscalls, IOCTL)
  • Identify high-value areas: previously patched code, complex parsers, newly added code, input ingestion points
  • For kernel modules: look beyond copy_from_user — DMA-BUF ops, page fault handlers, VM operation structs, allocation callbacks

2. Instrument and Build

# AFL++ (preferred for GreyBox)
CC=afl-clang-fast CXX=afl-clang-fast++ cmake -DCMAKE_BUILD_TYPE=Release .. && make -j

# libFuzzer + ASan/UBSan (C/C++)
cmake -DCMAKE_CXX_FLAGS="-fsanitize=fuzzer,address,undefined -O1 -g" ..

# CmpLog build for hard compares
AFL_LLVM_CMPLOG=1 CC=afl-clang-fast CXX=afl-clang-fast++ make clean all

Windows (MSVC): Project Properties → C/C++ → Address Sanitizer: Yes (/fsanitize=address)

3. Write Harness

libFuzzer (C++):

#include <cstdint>
#include <cstddef>
extern "C" int LLVMFuzzerTestOneInput(const uint8_t* data, size_t size) {
    parse_or_process(data, size);
    return 0;
}

Honggfuzz HF_ITER (persistent mode — preferred for large targets):

#include "honggfuzz.h"
int main(int argc, char** argv) {
    initialize_target(); // runs once
    for (;;) {
        size_t len; uint8_t *buf;
        HF_ITER(&buf, &len);
        FILE* s = fmemopen(buf, len, "r");
        target_function(s);
        fclose(s);
        reset_target_state();
    }
}

AFL++ persistent mode (__AFL_LOOP):

while (__AFL_LOOP(10000)) {
    // re-read input and process
}

macOS IPC (Mach message fuzzing):

void *lib_handle = dlopen("libexample.dylib", RTLD_LAZY);
pFunction = dlsym(lib_handle, "DesiredFunction");

4. Build Seed Corpus

  • Pull from target's test suite, bug reports, and real-world samples
  • Web-crawl (Common Crawl) for file formats; filter by MIME type
  • Minimize: afl-cmin -i raw_corpus -o seeds -- ./target @@
  • Trim inputs: afl-tmin -i crash -o crash.min -- ./target @@

5. Launch Fuzzing

AFL++ parallel (primary + secondary with cmplog):

afl-fuzz -M f1 -i seeds -o findings -x dict.txt -- ./target @@
afl-fuzz -S s1 -i seeds -o findings -c 0 -- ./target @@

libFuzzer:

./target_libfuzzer corpus/ -max_total_time=3600 -workers=4

Binary-only (QEMU):

afl-fuzz -Q -i seeds -o findings -- target.exe @@

Snapshot (AFL++ Nyx):

NYX_MODE=1 AFL_MAP_SIZE=1048576 afl-fuzz -i seeds -o findings -- ./target_nyx @@

Ensemble (AFL++ + Honggfuzz sharing corpus):

# Terminal 1
afl-fuzz -M fuzzer1 -i seeds -o sync_dir -- ./target @@
# Terminal 2
../honggfuzz/honggfuzz -i sync_dir/fuzzer1/queue -W sync_dir/hfuzz \
  --linux_perf_ipt_block -t 10 -- ./target ___FILE___

6. Monitor and Unstick

If progress stalls:

  • Enable CmpLog: -c 0 on AFL++ secondaries
  • Add dictionary: -x dict.txt or AFL_TOKEN_FILE
  • Switch to directed fuzzing (AFLGo) targeting specific BBs/functions
  • Use concolic assistance (QSYM, Driller) on hard branches
  • Snapshot the target to increase exec/s
  • AFL_MAP_SIZE=1048576, -L 0 for MOpt scheduler

7. Triage Crashes

# 1. Minimize
afl-tmin -i crash -o crash.min -- ./target @@
# 2. Symbolize
ASAN_OPTIONS=abort_on_error=1:symbolize=1 ./target crash.min 2>asan.log
# 3. Hash + bucket
./cov-tool --bbids ./target crash.min > cov.hash
./bucket.py --key "$(cat cov.hash)" --log asan.log --out triage/

Sanitizer env quick reference:

ASAN_OPTIONS=abort_on_error=1:symbolize=1:detect_stack_use_after_return=1
UBSAN_OPTIONS=print_stacktrace=1:halt_on_error=1
TSAN_OPTIONS=halt_on_error=1:history_size=7
MSAN_OPTIONS=poison_in_dtor=1:track_origins=2

Oracle Selection

Bug ClassOracle
Memory safetyASan, HWASan (AArch64, lower overhead)
Uninitialized readsMSan
ConcurrencyTSan
Undefined behaviorUBSan
Type safetyTypeSan
Heap hardeningScudo Hardened Allocator
Logic bugsDifferential / idempotency oracles
Kernel memoryKASAN, KMSAN, KCSAN
Kernel UBKUBSan (CONFIG_UBSAN_TRAP=y)
CFIKCFI (-fsanitize=kcfi, Clang 18)
Binary-onlyQASAN (QEMU+ASan), DynamoRIO

Property oracle patterns:

  • Idempotency: f(x) == f(f(x))
  • Differential: compare two impls, bucket on output mismatch
  • Invariants: monotonic lengths, checksum equality, schema validation post-parse

Specialized Targets

Kernel (Linux) — syzkaller

{
  "target": "linux/arm64",
  "http": ":56700",
  "workdir": "/path/to/workdir",
  "kernel_obj": "/path/to/kernel",
  "image": "/path/to/rootfs.ext3",
  "sshkey": "/path/to/id_rsa",
  "procs": 8,
  "enable_syscalls": ["openat$module_name", "ioctl$IOCTL_CMD", "mmap"],
  "type": "qemu",
  "vm": { "count": 4, "cpu": 2, "mem": 2048 }
}
  • Limit enable_syscalls to deepen coverage on specific subsystems
  • Use syz-extract to pull constants for custom modules
  • Enable CONFIG_KASAN=y, CONFIG_KCFI=y, CONFIG_DEBUG_INFO_BTF=y
  • Use kcov filters and syz_cover_filter to direct coverage
  • Network fuzzing: inject via TUN/TAP + pseudo-syscalls (syz_emit_ethernet)
  • Crash decode: ./scripts/decode_stacktrace.sh vmlinux ... < dmesg.log

syzkaller repro:

syz-execprog -repeat=0 -procs=1 -cover=0 -debug target.repro

EDR / Windows Scanning Engines

WTF snapshot harness skeleton (mpengine.dll / mini-filter):

g_Backend->SetBreakpoint("nt!KeBugCheck2", [](Backend_t *Backend) {
    const uint64_t BCode = Backend->GetArg(0);
    Backend->Stop(Crash_t(fmt::format("crash-{:#x}", BCode)));
});

FilterConnectionPort fuzzing:

HANDLE hPort;
FilterConnectCommunicationPort(L"\\PortName", 0, NULL, 0, NULL, &hPort);
FilterSendMessage(hPort, fuzzData, sizeof(fuzzData), NULL, 0, &bytesReturned);

IOCTL fuzzing pattern:

HANDLE hDev = CreateFile(L"\\\\.\\DeviceName", GENERIC_READ|GENERIC_WRITE, ...);
DeviceIoControl(hDev, ioctlCode, inputBuf, inputLen, outBuf, outLen, &ret, NULL);
  • Take snapshots after initialization, right before parse/dispatch loop
  • Use IDA Lighthouse for coverage visualization
  • Monitor: DRIVER_VERIFIER_DETECTED_VIOLATION (0xc4), IRQL_NOT_LESS_OR_EQUAL (0xa)
  • WinDbg: .symfix; !analyze -v; k; !heap -p -a @rax

Cross-platform mpengine.dll on Linux (loadlibrary + HF_ITER + Intel PT):

// Bypass Lua VM to avoid stability issues
insert_function_redirect((void*)luaV_execute_address, my_lua_exec, HOOK_REPLACE_FUNCTION);
for (;;) {
    HF_ITER(&buf, &len);
    ScanDescriptor.UserPtr = fmemopen(buf, len, "r");
    __rsignal(&KernelHandle, RSIG_SCAN_STREAMBUFFER, &ScanParams, sizeof ScanParams);
}

Rust

# Full Rust fuzzing pipeline
cargo test                                         # 1. property tests
cargo +nightly miri test                           # 2. UB via interpreter
cargo +nightly careful test                        # 3. runtime bounds checks
cargo fuzz run fuzz_target_1 -- -max_total_time=3600  # 4. libFuzzer crashes
RUSTFLAGS="--cfg loom" cargo test --release        # 5. concurrency (if needed)
cargo fuzz coverage fuzz_target_1                  # 6. coverage report

Focus unsafe blocks on: Vec::from_raw_parts, unchecked indexing, transmute size mismatches, pointer arithmetic, FFI integer truncation.

Embedded / Binary-Only

  • LibAFL: Modular Rust framework; Unicorn engine, snapshot module, LBRFeedback (zero-instrumentation on Intel), SAND decoupled sanitization
  • Retrowrite / QASAN: Binary rewriting for coverage + ASan without source
  • Nautilus: Grammar-based fuzzing for structured formats

Language Ecosystems

  • Go 1.18+: go test -fuzz=Fuzz -run=^$ ./...
  • Python: Atheris (CPython native extension fuzzing)
  • Rust: cargo-fuzz or honggfuzz-rs
  • JS engines: Fuzzilli with extended instrumentation (__builtin_return_address(0) for PC tracking)
  • Wasm runtimes: wasmtime-fuzz, wafl for differential fuzzing across V8/Wasmer/Wasmtime
  • Smart contracts: Echidna, Foundry-fuzz (Solidity); Move-Fuzz (Aptos/Sui)

CI/CD Integration

- name: Build with afl-clang-fast
  run: CC=afl-clang-fast make -j
- name: Fuzz (smoke, 15 min)
  run: timeout 15m afl-fuzz -i seeds -o findings -- ./target @@ || true
- name: Upload crashes
  if: always()
  uses: actions/upload-artifact@v4
  with:
    path: findings/**/crashes/*

Use ClusterFuzzLite for persistent continuous fuzzing; cache corpora between runs.

Crash Analysis Quick Reference

Linux:

ulimit -c unlimited && sysctl -w kernel.core_pattern=core.%e.%p
gdb -q ./target core.* -ex 'bt' -ex 'info reg' -ex q
addr2line -e ./target 0xDEADBEEF

Windows:

# Enable local dumps
New-Item 'HKLM:\SOFTWARE\Microsoft\Windows\Windows Error Reporting\LocalDumps' -Force
# PageHeap
gflags /p /enable target.exe /full

Kernel KASAN/KMSAN:

dmesg -T | egrep -i 'kasan|kmsan' -A 60
./scripts/decode_stacktrace.sh vmlinux /lib/modules/$(uname -r)/build < dmesg.log

Reproducibility: pin CPU governor, disable ASLR only where safe, fix RNG seeds, save input sequences in persistent mode, record binary hashes and sanitizer options with every crash.

Tool Index

ToolUse Case
AFL++General GreyBox, CmpLog, MOpt, Nyx
HonggfuzzIntel PT, crash detection, HF_ITER
libFuzzerIn-process, source available
syzkallerLinux/Windows kernel syscall fuzzing
wtfSnapshot fuzzing, Windows targets
NyxAFL++ snapshot mode (Intel PT)
SnapchangeAWS snapshot fuzzing
LibAFLCustom Rust fuzzing framework
AFLGoDirected fuzzing to target BB/function
kAFLKernel + OS fuzzing
JackalopeBinary coverage-guided (Windows/macOS)
cargo-fuzzRust libFuzzer integration
AtherisPython fuzzing
NautilusGrammar-based fuzzing
AFLTriageAutomated crash triage
afl-covCoverage analysis for AFL++
ClusterFuzzDistributed fuzzing infrastructure

相似的 Skill

theme-factory
anthropics/skills180k

theme-factory

Toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors/fonts that you can apply to any artifact that has been creating, or can generate a new theme on-the-fly.

文档与办公

canvas-design
anthropics/skills180k

canvas-design

Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.

文档与办公

doc-coauthoring
anthropics/skills180k

doc-coauthoring

Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.

文档与办公

docx
anthropics/skills180k

docx

Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files) or Word templates (.dotx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', '.dotx', or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx or .dotx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a 'report', 'memo', 'letter', 'template', or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.

文档与办公

pdf
anthropics/skills180k

pdf

Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.

文档与办公

discernment-nudge
anthropics/skills180k

discernment-nudge

After you give a substantive answer or draft that the user may act on — advice or recommendations, drafted artifacts such as goals, plans, pitches, proposals, or emails, estimates or projections, analysis or interpretation of data, factual claims they may rely on, or a multi-step argument — invoke this skill BEFORE finalizing your reply and then, if it applies, append 2-3 short follow-up questions, each tied to something specific in what you just produced, that help the user check key facts, probe the reasoning or assumptions, and notice missing context. Do this at most once per conversation. Skip it when the user asked a trivial how-to or simple lookup, wants a purely educational explanation, asked you only to format, convert, or assemble a file from content they provided, is writing code they will run, is doing creative writing or casual chat, or already asked you to double-check, cite, or review — the skill file explains these boundaries and the exact output format.

文档与办公