
Confidently Wrong: AI Hallucinations Threaten Cybersecurity
AI hallucinations are confidently plausible yet factually incorrect outputs that can mislead security decisions, causing missed threats, false positives, and risky remediation. A 2025 AA-Omniscience benchmark found most models favor confident, incorrect answers over correct ones on hard questions. Mitigation includes enforcing human review before actions, auditing training data as a security asset, enforcing least-privilege access, investing in prompt engineering, and centering identity security in AI governance.












