Probabilistic output is an AI response generated from statistical likelihoods, not fixed rules. The model predicts the most likely next token or answer based on its training data and the prompt, so the result can vary across runs even when the question looks the same. This makes the output flexible and useful, but also less deterministic than traditional software.
In cybersecurity, that variability matters because security teams often rely on AI for drafting alerts, summarizing logs, analyzing incidents, or supporting policy work. A probabilistic system can miss details, invent facts, or change wording in ways that affect interpretation. Attackers may exploit that uncertainty with prompt manipulation, while defenders must verify AI-generated conclusions before acting on them. Good practice includes human review, grounded sources, logging, and testing for consistency on high-risk tasks.