Binary authorship attribution refers to the process of discovering information related to the author(s) of anonymous binary code on the basis of stylometric characteristics extracted from the code. However, in practice, authorship attribution for binary code still requires considerable manual and error-prone reverse engineering analysis, which can be a daunting task given the sheer volume and complexity of today’s malware. In this chapter, we propose BinAuthor, a novel and the first compiler-agnostic method for identifying the authors of program binaries. Having filtered out unrelated functions (compiler and library) to detect user-related functions, it converts user-related functions into a canonical form to eliminate compiler/compilation effects. Then, it leverages a set of features based on collections of authors’ choices made during coding. These features capture an author’s programming coding habits.