StringSifter is a machine learning tool designed to automatically rank strings extracted from malware samples based on their relevance for analysis purposes. The tool processes string output and applies machine learning algorithms to prioritize strings that are most likely to be useful for malware researchers and analysts. The tool provides two main command-line utilities: flarestrings, which mimics the functionality of GNU binutils' strings command, and rank_strings, which accepts piped input to rank extracted strings. StringSifter can be used in combination where flarestrings extracts strings from a binary sample and pipes the output to rank_strings for relevance ranking. Built with Python 3.9+ requirements, StringSifter is available through PyPi for standard installation or can be developed from source using poetry. The tool includes unit testing capabilities and supports command-line operations for integration into malware analysis workflows. The ranking system helps analysts focus on the most relevant strings first, potentially reducing the time spent manually reviewing large volumes of string data during malware analysis sessions.