MCPInstall

rev-unicorn-debug

Debug and emulate specific code fragments or functions using the Unicorn engine. Activate when the user wants to emulate a function with Unicorn, trace binary execution without running the full program, decrypt or decode data by emulating the algorithm, or bypass environment dependencies (JNI, syscalls, libc) during emulation.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/p4nda0s/reverse-skills --skill rev-unicorn-debug
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads rev-unicorn-debug automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

rev-unicorn-debug - Unicorn Emulation Debugger

Debug and emulate specific code fragments or functions using the Unicorn engine. Analyze context dependencies (JNI, syscalls, library functions) and simulate them through hook mechanisms to complete the user's debugging goal.


Core Principles

  1. Load file raw first — do NOT parse ELF/PE/Mach-O headers. Read the file as raw bytes and map directly into Unicorn memory. We only need to emulate specific functions, not the entire binary. If raw loading fails (code references segments at specific addresses), then parse minimally — only map the segments needed.
  2. Identify context dependencies — analyze the target code for external calls (JNI, syscalls, libc, imports) and hook them to provide simulated responses.
  3. Use callbacks extensively — leverage Unicorn's hook system for debugging, tracing, error recovery, and environment simulation.
  4. Iterative fix — when emulation crashes, use the callback info to diagnose and fix (map missing memory, hook unhandled calls, fix register state).
  5. Minimal trace output — prefer block-level tracing over instruction-level. Only enable instruction trace on small targeted ranges. Use counters and summaries instead of per-step logging.

Environment Simulation Strategy

Before emulating, read the target function and identify what it calls. Hook external dependencies by address and simulate in Python:

CategoryExamplesSimulation Strategy
libcmalloc, free, memcpy, strlen, printfHook address, implement logic in Python (bump allocator for malloc)
JNIGetStringUTFChars, FindClass, GetMethodIDBuild fake JNIEnv function table in UC memory, write RET stubs at each entry, hook stub addresses
Syscallsread, write, mmap, ioctlHook UC_HOOK_INTR, dispatch by syscall number
C++ runtimeoperator new, __cxa_throwHook and simulate
Library callspthread_mutex_lock, dlopenHook and return success/stub

Hook pattern: Register a UC_HOOK_CODE callback. When PC hits a known import address, execute the Python simulation, then set PC = LR to skip the original function.


Callback Types to Use

CallbackPurpose
UC_HOOK_CODEIntercept import calls by address; instruction-level trace (use sparingly, narrow range only)
UC_HOOK_BLOCKBlock-level trace (preferred over instruction trace)
UC_HOOK_MEM_UNMAPPEDAuto-map missing pages to recover from unmapped access errors
UC_HOOK_MEM_READ | UC_HOOK_MEM_WRITETrace memory access on targeted data ranges only
UC_HOOK_INTRIntercept SVC/INT for syscall simulation

Iterative Debugging Workflow

When emulation fails, follow this loop:

  1. Run — start emulation, let it crash
  2. Read callback output — which address faulted? What type (read/write/fetch)?
  3. Diagnose:
    • Unmapped memory fetch → missing code page, map it
    • Unmapped memory read/write → missing data section or uninitialized pointer, map or hook
    • Hitting an import stub → identify the function, add a simulation hook
    • Infinite loop → add a code hook with execution counter, stop after threshold
  4. Fix — add the hook / map the memory / adjust registers
  5. Re-run — repeat until the target function completes

Architecture Quick Reference

ArchUc ConstModeSPLRArgsReturnSyscall
ARM64UC_ARCH_ARM64UC_MODE_LITTLE_ENDIANSPX30X0-X7X0X8 + SVC #0
ARM32UC_ARCH_ARMUC_MODE_THUMB / UC_MODE_ARMSPLRR0-R3R0R7 + SVC #0
x86-64UC_ARCH_X86UC_MODE_64RSP(stack)RDI,RSI,RDX,RCX,R8,R9RAXRAX + syscall
x86-32UC_ARCH_X86UC_MODE_32ESP(stack)(stack)EAXEAX + int 0x80
MIPS32UC_ARCH_MIPSUC_MODE_MIPS32 + UC_MODE_BIG_ENDIAN$sp$ra$a0-$a3$v0$v0 + syscall

FAQ

What does the rev-unicorn-debug skill do?

Debug and emulate specific code fragments or functions using the Unicorn engine. Activate when the user wants to emulate a function with Unicorn, trace binary execution without running the full program, decrypt or decode data by emulating the algorithm, or bypass environment dependencies (JNI, syscalls, libc) during emulation.

How do I install rev-unicorn-debug?

Run npx skills add https://github.com/p4nda0s/reverse-skills --skill rev-unicorn-debug in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/rev-unicorn-debug/ (personal) or .claude/skills/rev-unicorn-debug/ (project).

Which AI agents can use rev-unicorn-debug?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is rev-unicorn-debug safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains rev-unicorn-debug?

It is published by p4nda0s in p4nda0s/reverse-skills. It has 1,805 recorded installs.

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