For Heads-of · Practitioner
Misinformation and confabulation
A model states false or fabricated information with the same linguistic confidence as accurate information.
- high
- llm
- hallucination
- misinformation
- owasp-llm
How it happens
A model generates plausible-sounding but false content, such as a fabricated citation, a wrong figure, or a non-existent policy clause, because its objective is fluent continuation, not verified accuracy.
Why it matters
Confabulated output carries the same confident tone as correct output, so it passes casual review, and is particularly dangerous in high-stakes domains like legal research, financial analysis, or medical triage.
Mitigating controls
The controls that address this risk, ranked by effectiveness.
Human-in-the-loop review
Mandatory human approval gate for high-consequence or irreversible AI-generated actions before they take effect.
Factuality and hallucination verification
Automated or human fact-checking of AI-generated output against a trusted source before it is relied on for a consequential decision.
Framework and clause references
| Framework | Clause | Title |
|---|---|---|
| NIST Generative AI Profile (NIST AI 600-1) | Confabulation | Confabulation |
| OWASP Top 10 for LLM Applications | LLM07 | Misinformation |
Related resources
The external sources behind this risk, from the Resources library.