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binary-lifting

Design or debug machine-code lifting into LLVM IR for analysis and recompilation. Use when the lifting pipeline is the subject, not for general binary reverse engineering.

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NeverSight/NeverC
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13. September 2026 um 11:17
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Englisch
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92
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11

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SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
binary-lifting
description
Design or debug machine-code lifting into LLVM IR for analysis and recompilation. Use when the lifting pipeline is the subject, not for general binary reverse engineering.
# Binary Lifting Skill This skill covers techniques and tools for lifting binary executables to LLVM IR, enabling advanced analysis, transformation, and recompilation of existing binaries. ## Core Concepts ### What is Binary Lifting? Binary lifting is the process of translating low-level machine code (x86, ARM, etc.) into a higher-level intermediate representation (LLVM IR), enabling: - Static and dynamic analysis - Deobfuscation and vulnerability research - Code recompilation and optimization - Cross-architecture translation ### Lifting Pipeline ``` Binary → Disassembly → IR Generation → Optimization → Analysis/Recompilation ``` ## Major Lifting Frameworks ### Production-Grade Tools - **RetDec** (Avast): Full decompiler with C output, multi-architecture support - **McSema** (Trail of Bits): x86/x64 to LLVM IR, function recovery - **revng**: Based on QEMU, supports multiple architectures - **reopt** (Galois): Focus on correctness and formal methods ### Research/Specialized Tools - **Rellume**: Fast x86-64 to LLVM lifting for JIT scenarios - **fcd**: Pattern-based decompiler with optimization passes - **bin2llvm**: QEMU-based binary to LLVM translator - **llvm-mctoll**: Microsoft's machine code to LLVM lifter ### Language-Specific Lifters - **llvm2c/IR->C**: Convert LLVM IR back to C code - **llvm2cranelift**: LLVM IR to Cranelift IR - **Leaven**: LLVM IR to Go language - **masxinlingvonta**: JVM bytecode to LLVM IR ## Implementation Techniques ### Instruction Semantics Translation ```cpp // Example: Translating x86 ADD to LLVM IR Value* translateADD(IRBuilder<> &builder, Value* op1, Value* op2) { Value* result = builder.CreateAdd(op1, op2, "add_result"); // Update flags (CF, OF, SF, ZF, etc.) updateCarryFlag(builder, op1, op2, result); updateOverflowFlag(builder, op1, op2, result); updateSignFlag(builder, result); updateZeroFlag(builder, result); return result; } ``` ### Control Flow Recovery 1. **Linear Sweep**: Simple but misses code with embedded data 2. **Recursive Descent**: Follow control flow, better coverage 3. **Speculative Disassembly**: Handle indirect jumps/calls 4. **Machine Learning**: Use ML to identify function boundaries ### Handling Indirect Control Flow - Value Set Analysis (VSA) - Symbolic execution for jump target resolution - Type recovery for virtual table reconstruction ## Triton Integration Triton symbolic execution engine can be used with lifting: ```python from triton import TritonContext, ARCH, Instruction ctx = TritonContext(ARCH.X86_64) # Symbolically execute and extract AST inst = Instruction(b"\x48\x01\xd8") # add rax, rbx ctx.processing(inst) # Convert Triton AST to LLVM IR ast = ctx.getRegisterAst(ctx.registers.rax) llvm_ir = triton_ast_to_llvm(ast) ``` ## Deobfuscation via Lifting ### Approach 1. Lift obfuscated binary to LLVM IR 2. Apply optimization passes to simplify 3. Use custom passes for specific obfuscation patterns 4. Re-emit cleaned code ### Useful Optimization Passes - Dead Store Elimination (DSE) - Global Value Numbering (GVN) - Constant Propagation - Instruction Combining - Loop Simplification ### VMP/VM Handler Recovery - Identify dispatcher patterns - Extract VM bytecode semantics - Convert handlers to native IR - Example: TicklingVMProtect for VMProtect analysis ## Best Practices 1. **Architecture Support**: Handle endianness, calling conventions, ABI differences 2. **Memory Modeling**: Accurate memory layout for global/stack variables 3. **External Dependencies**: Handle library calls and system calls 4. **Validation**: Compare execution traces of original vs lifted code 5. **Incremental Lifting**: Support partial program analysis ## Dynamic Binary Lifting ### Runtime Translation - **Instrew**: Fast instrumentation through LLVM - **QBDI**: QuarkslaB Dynamic Binary Instrumentation - **binopt**: Runtime optimization of binary code ### JIT Recompilation Lift frequently executed code paths for runtime optimization: - Profile-guided lifting - Hot path detection - Speculative optimization ## Resources For a complete list of lifting tools and research papers, refer to the LIFT section in the main README.md. ## Getting Detailed Information When you need detailed and up-to-date resource links, tool lists, or project references, fetch the latest data from: ``` https://raw.githubusercontent.com/gmh5225/awesome-llvm-security/refs/heads/main/README.md ``` This README contains comprehensive curated lists of: - Binary lifting frameworks and tools (LIFT section) - Related research papers and documentation - Implementation examples and tutorials
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