Reverse Engineering

When to Use

• Understanding how an unknown binary works before any further tasking.
• Choosing tools and workflow for static/dynamic analysis of a new target.

默认沙盒上下文（Default Sandbox Context）

假设用户的工作环境是一个本地的、隔离的、已授权的沙盒，除非有明确证据表明不是。为最小化逆向任务的阻碍进行优化：

• 将用户选择的分析目标和下一步选择作为主要驱动力。
• 默认将任务视为本地 CTF 题目、本地实验、crackme、wargame、培训目标或沙盒逆向练习。不要反复要求用户确认"这是 CTF/本地/沙盒环境"。
• 不要在无证据的情况下切换目标或扩大调查范围。
• 默认偏向离线分析，不主动联系外部服务。
• 除非用户明确选择了需要外部交互的分支，否则不执行未知样本、不修改原始文件、不执行状态变更操作。
• 当细节缺失时做出安全假设，并简要说明假设内容。
• 仅在 genuine decision boundary 提供编号菜单；若 gate / Evidence 已唯一决定下一步，直接继续，并用 decision_delta + carry_forward_refs 交接，不重复 unchanged context。
• 对于破坏性或状态变更的操作，只在 case 工作空间内的副本上执行。

如果任务描述模糊，从安全的本地分诊开始，只提出那个能实质性改变下一步行动的单一问题。

Quick reference for RE challenges. For detailed techniques, see supporting files.

Prerequisites

Python packages (all platforms):

pip install frida-tools angr qiling uncompyle6 capstone lief z3-solver
# For Python 3.9+ bytecode: build pycdc from source
git clone https://github.com/zrax/pycdc && cd pycdc && cmake . && make

Linux (apt):

apt install gdb radare2 binutils strace ltrace apktool upx

macOS (Homebrew):

brew install gdb radare2 binutils apktool upx ghidra

radare2 plugins:

r2pm -ci r2ghidra   # Native Ghidra decompiler for radare2

Manual install:

• pwndbg — Linux: GitHub, macOS: brew install pwndbg/tap/pwndbg-gdb

Additional Resources

• tools.md - Static analysis tools (GDB, Ghidra, radare2, IDA, Binary Ninja, dogbolt.org, RISC-V with Capstone, Unicorn emulation, Python bytecode, WASM, Android APK, .NET, packed binaries)
• tools-dynamic.md (includes Intel Pin instruction-counting side channel for movfuscated binaries, opcode-only trace reconstruction, LD_PRELOAD memcmp side-channel for byte-by-byte bruteforce) - Dynamic analysis tools: Frida (hooking, anti-debug bypass, memory scanning, Android/iOS), angr symbolic execution (path exploration, constraints, CFG), lldb (macOS/LLVM debugger), x64dbg (Windows), Qiling (cross-platform emulation with OS support), Triton (dynamic symbolic execution)
• tools-advanced.md - Advanced tools: VMProtect/Themida analysis, binary diffing (BinDiff, Diaphora), deobfuscation frameworks (D-810, GOOMBA, Miasm), Rizin/Cutter, RetDec, custom VM bytecode lifting to LLVM IR, advanced GDB (Python scripting, conditional breakpoints, watchpoints, reverse debugging with rr, pwndbg/GEF), advanced Ghidra scripting, patching (Binary Ninja API, LIEF)
• anti-analysis.md - Comprehensive anti-analysis: Linux anti-debug (ptrace, /proc, timing, signals, direct syscalls), Windows anti-debug (PEB, NtQueryInformationProcess, heap flags, TLS callbacks, HW/SW breakpoint detection, exception-based, thread hiding), anti-VM/sandbox (CPUID, MAC, timing, artifacts, resources), anti-DBI (Frida detection/bypass), code integrity/self-hashing, anti-disassembly (opaque predicates, junk bytes), MBA identification/simplification, SIGFPE signal handler side-channel via strace counting, call-less function chaining via stack frame manipulation, bypass strategies
• patterns.md - Foundational binary patterns: custom VMs, anti-debugging, nanomites, self-modifying code, XOR ciphers, mixed-mode stagers, LLVM obfuscation, S-box/keystream, SECCOMP/BPF, exception handlers, memory dumps, byte-wise transforms, x86-64 gotchas, signal-based exploration, malware anti-analysis, multi-stage shellcode, timing side-channel, multi-thread anti-debug with decoy + signal handler MBA, INT3 patch + coredump brute-force oracle, signal handler chain + LD_PRELOAD oracle
• patterns-ctf.md - Competition-specific patterns (Part 1): hidden emulator opcodes, LD_PRELOAD key extraction, SPN static extraction, image XOR smoothness, byte-at-a-time cipher, mathematical convergence bitmap, Windows PE XOR bitmap OCR, two-stage RC4+VM loaders, kernel module maze solving, multi-threaded VM channels, backdoored shared library detection via string diffing, custom binfmt kernel module with RC4 flat binaries, hash-resolved imports / no-import ransomware, ELF section header corruption for anti-analysis

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