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Reverse engineering arm binaries

Skill meltedinhex/analyst-ai-pack/skills/reverse-engineering-arm-binaries

Reverse engineers ARM/AArch64 malware by identifying the architecture and instruction set state (ARM/Thumb), parsing ELF/Mach-O ARM headers, and orienting analysis around the ARM calling convention. Activates for requests to reverse ARM binaries, analyze AArch64 malware, or handle ARM/Thumb instruction-set decoding.From its SKILL.md

Install
npx -y skills add meltedinhex/analyst-ai-pack --skill reverse-engineering-arm-binaries

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SKILL.md

2.7 KB, 487 tokens by cl100k_base, as published. Nobody here has run it

Reverse Engineering ARM Binaries

When to Use

  • You have an ARM (32-bit) or AArch64 (64-bit) binary — IoT/mobile/Linux malware — and need to identify the architecture, instruction-set state, and entry point before disassembly.
  • You need to handle ARM/Thumb interworking correctly.

Do not use an x86 mindset for calling conventions/registers — ARM differs. This skill reads the binary statically and executes nothing.

Prerequisites

  • The ARM binary (ELF or Mach-O), read inertly. Capstone optional for instruction decoding.

Safety & Handling

  • Read bytes statically; analyze on an isolated host (and emulate via QEMU separately if needed).

Workflow

Step 1: Identify architecture and format

python scripts/analyst.py identify sample.bin

Parses ELF/Mach-O headers to report ARM vs AArch64, endianness, entry point, and (for ELF) whether the entry is Thumb (low bit set in e_entry or $t mapping symbols).

Step 2: Set the correct disassembly mode

Disassemble AArch64 as A64; for 32-bit ARM, switch between ARM and Thumb per the entry/mapping symbols.

Step 3: Orient around the calling convention

Track arguments in r0-r3/x0-x7, return in r0/x0, and syscalls via svc with the syscall number in r7/x8.

Step 4: Proceed with analysis

Identify functions, strings, and syscalls; pair with emulation if dynamic insight is needed.

Validation

  • Architecture (ARM/AArch64) and endianness are read from the header.
  • The entry point and ARM/Thumb state are reported.
  • Disassembly mode matches the detected state.

Pitfalls

  • Missing Thumb state and decoding Thumb as ARM (garbage output).
  • Big-endian ARM (rare but real) mis-parsed as little-endian.
  • Statically linked musl/uClibc inflating the function set on IoT samples.

References

What ships with it: 3 files

4.0 KB alongside SKILL.md, 1 of them executable

references/

scripts/

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