AI Risk Wire

Risks

Silent wrong state or drift

The system reports success, or keeps running, while its output or the state it left is wrong.

NIST AI 600-1 · No exact NIST AI 600-1 categoryMAS AI risk management guidelines (2026)NIST AI RMF MEASURE 2.4

2incidents (primary) · 2 more as secondary
0read for controls · 2 not yet
0fixes reported
0repeats after a fix

Incidents per month

2 so far in 2026; 0 in the same span of 2025.

Jan 2026: 0Feb 2026: 0Mar 2026: 0Apr 2026: 0May 2026: 0Jun 2026: 0Jul 2026: 0Aug 2026: 0Sep 2026: 11Oct 2026: 11Nov 2026: 0 Jan 26FebMarAprMayJunJulAugSepOctNovto date

Developers

Anthropic · 1

Where the chain broke

Part of the systemIncidents where the control was not effective or did not existIncidents where the control was effectiveIncidents where sources don't mention the controlIncidents not yet checked for controls
L1 Model
Model provider
2
L2 Harness
Agent framework vendor
2
L3 Application
Deployer
2
L4 Infrastructure / target
Organisation hit
2

Controls for this risk, by layer

ControlIncidents where the control was not effective or did not existIncidents where the control was effectiveIncidents where sources don't mention the controlMost common reason it was not effective
Change review and separation of duties
L3 Application
Activity logs
L3 Application
Live behaviour monitoring
L3 Application
Drift monitoring
L3 Application
Independent check of task results
L3 Application
Grounding and fact checks
L3 Application

6 of 6 controls for this risk not yet recorded as effective.

Fixes reported and what followed

No remediation reported for incidents of this risk.

Incidents

EffectiveNot effectiveNot effective (bypassed)Did not existNot stated in sourcesNot yet checkedAttacker's ownOrder: model · harness · application · target

Also under this risk as a secondary risk: LR-2026-0603, LR-2026-0481