Human corroboration is a review step in which a person checks the evidence behind an automated output before acting on it. The reviewer is not just clicking approval; they are expected to examine logs, context, and supporting data well enough to confirm, reject, or refine the machine’s recommendation.
In cyber security, human corroboration matters because automated systems can be noisy, incomplete, or manipulated. A SIEM alert, EDR detection, fraud score, or access-risk flag may be useful, but it should not be the only basis for a high-impact action. Attackers also try to exploit weak review chains by flooding analysts with alerts, hiding malicious activity inside normal behavior, or causing false positives that lead to bad decisions. Good defenses use human corroboration to create accountability, reduce false trust in automation, and preserve an evidence trail that can be audited later. If the reviewer cannot see enough evidence to challenge the output, the process is probably a rubber stamp rather than real verification.