the original binary. Binary level mutation has been explored previously [16], [4]. The major challenge on binary mutation tools is practical and scalable binary rewriting which in turn imposes limitation on the binary mutation operators. In order to generate mutants from the original binary, the mutation tool needs to restore a higher level code representation like assembly and then apply the mutation operator which may change the instructions address layout. Binary rewriting has found many applications in program analysis, security and etc. Mutation analysis is another application of binary rewriting which requires generation working mutants by making changes at instruction level.Binary rewriting techniques have been extensively incorporated in security enforcement tools like [25], [37], [38], [15] where the instructions are aligned, inserted or replaced to enforce measurements like control flow integrity or fault isolation and etc. In recent years reliable binary rewriting techniques (like Ddisasm [17] or Ramblr [33]) have been proposed which expand the domain of such measurements applications to the programs available only in binary format. Previously researchers have demonstrated the applicability of reassembleable disassembly for binary mutation [16]. They used Uroboros [34] and were able to mutate binaries from SPEC CPU. Limitations imposed by Uroboros obstructs the practicality of such application, more specifically authors reported fragility of the tool in a way that it worked for specific compilation options. Their implemented mutation operators are limited to only conditional jump and move instructions.In this paper, we revisit the notion of binary mutation in light of recent advancements in binary rewriting to implement a practical binary mutation tool that can support real-world binaries. Additionally, we employ a richer set of mutation operators that span over conditional, logical, and arithmetic instructions in order to have a more rigorous evaluation of the test harness. Our binary mutation tool named SN4KE is accessible at https://github.com/pwnslinger/sn4ke/.The rest of the paper is as follows: in section II we discuss the related work on the subject of binary mutation analysis of tests. section III presents our approach and design of SN4KE, specifically the set of mutation operators and the binary rewriting engine. section IV describes our evaluation of SN4KE on SPEC CPU benchmarks and the comparison of performance of the two binary rewriting tools we used. section V discusses some of interesting challenges we had in adapting rev.ng for our purpose. Finally, section VII concludes the paper.