Files
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Digital Publisher
Digital Commons at St. Mary's
Publication Date
Spring 2026
Keywords
Artificial Intelligence (AI), Reverse Engineering, Cybersecurity, Analyzing systems
Description
Reverse engineering plays a vital role in cybersecurity by helping analysts examine unknown binaries, investigate malware, identify vulnerabilities, and better protect sensitive systems. However, once a program is compiled and stripped, the meaningful names that describe its behavior are lost, leaving behind generic function labels like FUN_00401a30. Analysts must then manually interpret decompiled code, trace call chains, and infer program behavior function by function, which is slow and mentally demanding on large binaries. To address this challenge, this project introduces A.I.R.E., a local Ghidra extension that extracts contextual evidence from stripped functions and uses a locally hosted language model to generate confidence-aware naming suggestions while keeping the analyst in control
Format
Size
1 poster
City
San Antonio, Texas
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Included in
Artificial Intelligence and Robotics Commons, Cybersecurity Commons, Information Security Commons, Software Engineering Commons