Security backlogs often become overwhelming due to inconsistent severity labeling from various tools, leading to chaos in issue prioritization. Large language models (LLMs) can help by analyzing and scoring issues based on detailed context rather than relying solely on scanner outputs, providing a more informed approach to triage and prioritization.