Thresholding is the use of a confidence cutoff to decide when an automated system should act, defer, or escalate. In security tools, a classifier may score an event as phishing, malware, or benign; only scores above a set threshold trigger blocking, quarantine, or an analyst alert. Scores below the threshold may be ignored or sent to a fallback path for human review.
This matters because cyber systems are often judged on speed and false positives as much as accuracy. A threshold that is too low can let weak signals drive risky automation, while one that is too high can miss real attacks and flood teams with noise. Attackers can exploit poor thresholding by crafting borderline inputs that evade detection or trigger unnecessary responses. Good thresholding is usually paired with logging, tuning, and clear escalation rules.