The increasing complexity of software systems and the growing importance of reverse engineering in cybersecurity have driven the development of advanced analysis tools. This thesis presents an innovative approach to automated ARM binary analysis using a Python-based framework. The developed script integrates libraries such as r2pipe, networkx, and pygraphviz, to facilitate the dissection and comprehensive understanding of ARM32 binaries. The primary objectives are to identify critical system calls, extract and map strings, and construct a function call graph for network analysis, revealing insights into binary structures and their interdependencies. The methodology begins with leveraging r2pipe to interact programmatically with Radare2, a powerful open-source reverse engineering tool.