Breaking Down Barriers: How LLMs Enable Software Analysis in Classified Environments

The recent explosion in large language model (LLM) technology has highlighted the challenges of using public generative artificial intelligence tools in classified environments, especially for software analysis. Currently, software analysis falls on the shoulders of static analysis tools and manual code review, which tend to provide limited technical depth and are often time-consuming in practice. In our latest podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Ryan Karl, an SEI embedded engineer, and John Robert, deputy director of the SEI’s Software Solutions Division, discuss their work on using LLMs in unclassified environments to rapidly develop tools that accelerate software analysis in classified environments with improved accuracy for certain software analysis tasks.