Clustered 2 filings across 2 jurisdictions · filed Mar 7, 2025. View entity profile → Other incidents for this victim →
incident inc_8fe674e17551441d · merge_method deterministic · confidence 100%
Discovered → first regulatory filing
Time between earliest and latest filing
Not recorded for this incident
Discovery variance · Leak precedence · Materiality delta · SEC filing delay — no leak-site claim in this cluster; no SEC 8-K in this cluster; needs two dated filings.
PII · PCI · Identity (basic)
IN MD
all State AG
Earliest sighting first · deep chronology in Litigation Timeline
Nov 25, 2024
When the intrusion reportedly occurred, per the linked filings
Nov 25, 2024
Reported by MARYLAND AG filing
Barrett-Jackson Holdings LLC reported a data breach to the Indiana Attorney General. The breach occurred on 2024-11-25 and was reported on 2025-03-07. 145 Indiana residents were affected. 205 individuals affected in total.
Affected (this filing): 205
Barrett-Jackson Holdings, LLC notified the Maryland Attorney General of a cyber incident occurring on or around November 25, 2024. The breach affected one Maryland resident, exposing their name and payment card data. The investigation is ongoing, and the company is providing 12 months of complimentary credit monitoring services to the affected individual.
Affected (this filing): 1
About this clustering
DisclosureLens links filings into incidents through layered matchers: deterministic rules (same source document, multistate filings of one breach, tight-window same-victim pairs), a weighted-similarity scorer for cross-source candidates, and an operator review queue for everything uncertain. Each link records its own method and confidence — shown per filing in the timeline below. The system defaults to NOT merging when uncertain, because a false merge (collapsing two unrelated breaches) is more harmful than a false split (showing related filings separately); uncertain pairs route to human review instead of auto-merging. Filing summaries shown in the timeline are AI-generated extracts — verify each against its linked source.