Elastic Security Labs conducted research on the capabilities of Large Language Models (LLMs), specifically Claude Opus 4.6, to reverse engineer obfuscated binaries. The research demonstrates that while LLMs can defeat traditional obfuscation, novel techniques targeting LLM weaknesses—such as context window limits, budget caps, and shortcut biases—can effectively and cheaply disrupt automated static analysis pipelines.