re-triton

MCP server exposing the Triton library for symbolic execution, taint analysis, and constraint solving.

Tools

Tool	What it does
`check_triton`	Confirm Triton is importable
`emulate_function`	Concrete emulation (no sym)
`symbolic_explore`	Symbolic execution through a function
`solve_constraint`	Z3-based constraint solver
`taint_analysis`	Taint tracking through a function
`find_magic_bytes`	Solve for input that matches target bytes

Install

pip install -e ./servers/re-triton

The pyproject.toml pins triton @ git+https://github.com/JonathanSalwan/Triton, which pulls Quarkslab's binary-analysis framework directly from its source repo. The PyPI triton package is the GPU compiler and is not what re-triton needs. Building Triton from source requires CMake + a C++ toolchain; the install can take a few minutes the first time.

Best-effort on Windows — if the source build doesn't install, the server will return a clean "Triton not available" error from check_triton.

Why Triton

Triton is the easiest of the symbolic-execution frameworks to embed in a Python tool. It pairs with the capstone disassembly (which we already use in re-lief). For binary-only symbolic exec on x86/x64/AArch64, this is the right choice. For more advanced use cases (deep program analysis, complex constraints), angr is the gold standard — that's a v2 candidate.

Note on raw bytes

Triton operates on raw machine code, not files. The MCP tools accept code_b64 (base64-encoded bytes) — the caller (Claude Code, via re-rizin.disassemble_function and friends) extracts the relevant bytes from the binary.