AI Risk Wire

Risks

Made-up output relied on

False output is acted on as if true.

NIST AI 600-1 · ConfabulationOWASP LLM09

5incidents (primary) · 0 more as secondary
0read for controls · 5 not yet
0fixes reported
0repeats after a fix

Incidents per quarter

2025-Q3: 0 · 2025-Q4: 0 · 2026-Q1: 0 · 2026-Q2: 0 · 2026-Q3: 2 · 2026-Q4: 3

Developers

Deloitte · 1
OpenAI · 1

Where the chain broke

LayerHeldDid not holdNot mentionedAttacker's ownNot read yet
L1 Model
Model provider
––––5
L2 Harness
Agent framework vendor
––––5
L3 Application
Deployer
––––5
L4 Infrastructure / target
Organisation hit
––––5

Controls for this risk, by layer

HeldFailedGot aroundMissing

ControlHeldFailedGot aroundMissingNot mentionedDid not hold, last 6 quartersAdded in fixesMost common reason
Human approval for high-impact actions
L3 Application
––––––
People told they are dealing with AI
L3 Application
––––––
Output filtering and redaction
L3 Application
––––––
Grounding and fact checks
L3 Application
–––––1

4 of 4 controls for this risk not yet seen holding.

Fixes reported and what followed

IncidentFix addsAfter
LR-2026-0079 2026-09-15 ·
Advice in source, not a fix by the party
Grounding and fact checks–

Incidents

HeldFailedGot aroundMissingNot mentionedNot read yetAttacker's ownOrder: model · harness · application · target