Triton: Dynamic Binary Analysis (DBA) framework

by do son · Published November 13, 2018 · Updated November 4, 2024

Triton is a dynamic binary analysis (DBA) framework. It provides internal components like a Dynamic Symbolic Execution (DSE) engine, a Taint Engine, AST representations of the x86 and the x86-64 instructions set semantics, SMT simplification passes, and an SMT Solver Interface, and, the last but not least, Python bindings.

Based on these components, you are able to build program analysis tools, automate reverse engineering and perform software verification. As Triton is still a young project, please, don’t blame us if it is not yet reliable.

Spread Taint
Taint analysis is used to know at each program point what part of memory or register are controllable by the user input. According to the instruction semantics, the taint is spread over the execution. Read more
Dynamic Symbolic Execution
The symbolic execution engine transforms the control flow and the data flow of the program into symbolic expressions. These expressions may be used to know at each program point what values can hold a register or part of memory. Read more
SMT Solver Interface
This component allows you to solve symbolic expressions. As all expressions are on the SMT2-LIB representation, you can plug any SMT solver which supports this format. By default, Triton is interfaced with the Z3 SMT solver. Read more

AST Representations of Semantics
Triton converts the x86 and the x86-64 instruction set semantics into AST representations which allows you to perform precise analysis and allow you to build and modify your own symbolic expressions.
SMT simplification passes
Triton allows you to optimize or translate all SMT AST nodes before the assignment to a register, a memory, or a volatile symbolic expression. This feature allows you to deobfuscate some expressions.
Python Bindings
Build your own tools through a high-level language and communicate with the Pin API and Triton’s components via Python bindings.

Changelog v0.9

Better dealing with path constraints

Lifting To SMT file

Lifting to Python file

Lifting to LLVM file

Lifting to LLVM IR and back

Python from 3.6 to 3.9 comparability

Add new AST optimizations

Add new instructions

Add FPU specification

Add support for Thumb IT instructions

Add the Bitwuzla solver interface

Add a synthesis expression engine

Fix semantics

Fix optimizations

And so many more