AI-Powered Reverse Engineering Tools — Using Large Language Models & Neural Networks for Binary Analysis & Patching

[Blacksec]

AI-POWERED REVERSE ENGINEERING LLMs for Binary Analysis • Neural Networks • Automated Decompilation • AI Patching​

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AI RE: Artificial intelligence is transforming reverse engineering. This guide covers using LLMs for binary analysis, identifying algorithms, generating patches, and understanding obfuscated code. The tools and techniques here are bleeding edge — most reversed haven't adopted them yet.

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AI TOOLS FOR RE

Tool	Type	Model	Capability	Accuracy	Cost
BinGPT	IDA Pro plugin	GPT-4 / Claude	Function renaming, pseudo-code generation, logic explanation	85-95%	OpenAI API cost
GhidraNNScript	Ghidra script	Local BERT model	Type reconstruction, variable naming	70-80%	Free (local)
Decomp2Code	Standalone	Fine-tuned CodeLlama	Converts decompiled C to readable C with variable names	75-85%	Free (local)
PatchAssist	Standalone	GPT-4	Generates patches from description: "NOP the license check"	90%	OpenAI API cost
SigFinder AI	x64dbg plugin	CNN classifier	Identifies cryptographic functions from byte patterns	92%	Free (local)
AutoUnpack ML	Standalone	Random Forest	Predicts packer type and OEP location	88%	Free

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USING GPT-4/CLAUDE FOR RE

Prompt engineering for binary analysis:

1. Function analysis (copy from IDA):
   "Analyze this decompiled function. Rename it and explain what it does:
   [paste decompiled C code]
   Identify: purpose, parameters, return value, key operations"

2. Algorithm identification:
   "Identify the encryption algorithm from this implementation:
   [paste code with constants]
   Look for: S-box patterns, round constants, key schedule structure"

3. Patch generation:
   "For this license check function, generate a patch that:
   - Always returns valid (true)
   - Is minimal (1-2 byte change)
   - Does not affect other functionality
   Code:
   [paste function]
   Output: offset, original bytes, patch bytes, explanation"

4. Obfuscated code analysis:
   "This code is obfuscated with control flow flattening:
   [paste flattened code]
   Identify: the original control flow, state variable, dispatcher
   Can you reconstruct the original switch statement?"

5. Protocol reverse engineering:
   "Analyze this network packet handler:
   [paste handler code]
   Identify: packet structure, field offsets, magic bytes, checksum algorithm"

Pro tips:
  - Include context: function names it calls, strings it references, XREFs
  - Show the IDA graph view (visual helps LLMs understand flow)
  - For large functions, break into chunks (200-300 lines max)
  - Use system prompt: "You are an expert reverse engineer..."
  - Cross-reference with Ghidra output (two tools, two perspectives)

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CASE STUDY: REVERSING CUSTOM VM WITH AI

Challenge: A CrackMe with custom VM bytecode interpreter
Goal: Understand the VM and generate keygen

Step 1: Feed the VM dispatcher to GPT-4
  "This is the dispatch loop of a custom VM:
  [paste dispatcher code]
  Identify: opcodes, operand types, register model, memory model"

Step 2: AI analysis result:
  "This is a stack-based VM with 4 registers (R0-R3):
  - Opcode 0x10: PUSH immediate (2-byte operand)
  - Opcode 0x11: PUSH register (1-byte operand)
  - Opcode 0x20: POP to register
  - Opcode 0x30: ADD (pop two, push result)
  - Opcode 0x31: SUB
  - Opcode 0x32: XOR
  - Opcode 0x40: CMP (pop two, set flags)
  - Opcode 0x50: JMP (2-byte offset)
  - Opcode 0x51: JZ (jump if zero)
  - Opcode 0x60: READ_INPUT (pop address, read char input)
  - Opcode 0x70: OUTPUT (pop value, print as char)
  - Opcode 0xFF: HALT"

Step 3: Feed the bytecode:
  "This is the bytecode for the VM. Decompile it to pseudo-code:
  [paste hex dump]

Step 4: AI produces:
  "Decompiled VM bytecode:
  R0 = 0
  loop:
    R1 = get_input_byte(R0)
    if R1 == 0: goto success
    R2 = R1 XOR 0xAB
    R3 = R0 XOR 0xCD
    R2 = R2 + R3
    check_byte(R0) == R2
    if not equal: goto fail
    R0 = R0 + 1
    goto loop
  success: print 'Valid key'
  fail: print 'Invalid key'"

Step 5: Write keygen:
  def generate_key(length):
      key = []
      for i in range(length):
          c = (check_bytes[i] ^ 0xAB) - (i ^ 0xCD) 
          key.append(c & 0xFF)
      return bytes(key)

Time with AI: 45 minutes
Time without AI (estimated): 8-12 hours

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TOOLS DOWNLOAD

AI-RE toolkit: [URL="https://mega.nz/file/BlackSec_AI_RE_Tools_2026"]File on MEGA[/URL]
Size: 850 MB | Password: AIRE2026
Includes: All plugins + scripts + local models + prompt templates + tutorials

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AI won't replace reverse engineers. But reverse engineers who use AI will replace those who don't. ​

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