snailsploit/claude-red

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.

소스 보기

사용 방법

  1. 설치 명령을 복사하고 자신의 에이전트 환경에 설치하기 전에 소스 패키지를 확인하세요.
  2. 필요한 도구, 인증 정보, 지원 환경은 원본 문서에서 확인하세요.
  3. 입력과 원하는 산출물을 설명하고 출처와 결과를 대조하세요.
npx skills add https://github.com/snailsploit/claude-red --skill offensive-fuzzing

시작 전 확인

  • 설치에는 모델 구독, API 한도, 파일 접근 권한이 포함되지 않습니다.
  • 별점 수와 설치 수는 활동 지표이며 독립적인 품질·보안 검증이 아닙니다.
원본 Skill 문서

원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.

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

bash
# 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++):

cpp
#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):

cpp
#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`):

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

macOS IPC (Mach message fuzzing):

c
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):

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

libFuzzer:

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

Binary-only (QEMU):

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

Snapshot (AFL++ Nyx):

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

Ensemble (AFL++ + Honggfuzz sharing corpus):

bash
# 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

bash
# 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

json
{
  "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:

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

EDR / Windows Scanning Engines

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

cpp
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:

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

IOCTL fuzzing pattern:

cpp
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):

cpp
// 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

bash
# 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

yaml
- 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:

bash
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:

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

Kernel KASAN/KMSAN:

bash
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

관련 작업

같은 저장소의 Skills

더 많은 Skills

모든 Skills
snailsploit
커뮤니티

offensive-anti-forensics

Anti-forensics and evidence destruction techniques for red team operators conducting authorized engagements. Covers log clearing on Windows (wevtutil, Clear-EventLog, ETW provider patching) and Linux (journal truncation, utmp/wtmp binary editing, syslog manipulation), timestamp manipulation via Timestomp and SetMACE to defeat timeline analysis, filesystem-level anti-forensics including NTFS Alternate Data Streams for payload hiding and secure deletion with sdelete/shred, memory artifact removal

설치 수
1
GitHub Stars
7.6천
업데이트
10월 12일
snailsploit
커뮤니티

offensive-container-escape

Container escape and breakout techniques targeting Docker, containerd, and Podman runtimes. Covers privileged container breakout via host filesystem mount and nsenter, Docker socket abuse through /var/run/docker.sock, Linux capability exploitation including CAPSYSADMIN, CAPSYSPTRACE, and CAPNETADMIN, cgroup v1 notifyonrelease escape, runc CVEs such as CVE-2019-5736 and CVE-2024-21626 Leaky Vessels, kernel exploits from within containers, and Dockerfile misconfigurations like --privileged and hos

설치 수
1
GitHub Stars
7.6천
업데이트
10월 12일
snailsploit
커뮤니티

offensive-osint

Comprehensive OSINT methodology skill for offensive security, red team intelligence gathering, and bug bounty reconnaissance. Covers domain recon, email harvesting, social media profiling, GitHub/code leaks, Shodan/Censys enumeration, breach data lookup, employee profiling, infrastructure mapping, cryptocurrency tracing, geospatial intelligence, and AI-assisted analysis workflows. Use when performing reconnaissance against a target domain or organization, investigating a person or entity, tracin

설치 수
1
GitHub Stars
7.6천
업데이트
10월 12일
snailsploit
커뮤니티

offensive-persistence

Comprehensive persistence tradecraft for authorized red team engagements covering Windows and Linux mechanisms. Windows techniques include registry Run/RunOnce keys, scheduled tasks, WMI event subscriptions, DLL search order hijacking, COM object hijacking, Startup folder drops, service creation, Security Support Provider (SSP) DLL injection, and Active Directory persistence (AdminSDHolder abuse, DCShadow, Golden Ticket, Silver Ticket, Skeleton Key, SID History injection). Linux techniques inclu

설치 수
1
GitHub Stars
7.6천
업데이트
10월 12일