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Triton - Triton is a Dynamic Binary Analysis (DBA) framework

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, 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. Open issues or pull requests are always better than troll =).

manticore - Symbolic execution tool

Manticore is a symbolic execution tool for analysis of binaries and smart contracts. Manticore is supported on Linux and requires Python 2.7. Ubuntu 16.04 is strongly recommended. Ethereum smart contract analysis requires the solc program in your $PATH.

stack-guard - A toy implementation of 'Stack Guard' on top of the LLVM compiler toolchain

A toy implementation of 'Stack Guard' on top of the LLVM compiler toolchain.Instrumentation code is added during compilation process to insert and verify stack canaries. Local variables (on the stack) are reordered to prevent buffers overflowing into other local variables. Vulnerable buffers are identified by performing a simple version of static taint analysis. Dependencies are maintained between function calls and pointer manipulations.

Tigress_protection - Playing with the Tigress binary protection

Tigress is a diversifying virtualizer/obfuscator for the C language that supports many novel defenses against both static and dynamic reverse engineering and de-virtualization attacks. In particular, Tigress protects against static de-virtualization by generating virtual instruction sets of arbitrary complexity and diversity, by producing interpreters with multiple types of instruction dispatch, and by inserting code for anti alias analysis. Tigress protects against dynamic de-virtualization by merging the real code with bogus functions, by inserting implicit flow, and by creating slowly-executing reenetrant interpreters. Tigress implements its own version of code packing through the use of runtime code generation. Finally, Tigress' dynamic transformation provides a generalized form of continous runtime code modification. If you want more information, you can checkout our solve-vm.py script.

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