J.D. Gilmour & Co. reported a data breach to the Montana Attorney General. The breach was reported on 2024-01-31. The breach occurred from 6/21/2023 to 6/29/2023. 2 Montana residents were affected.
Affected (this filing): 2
Clustered 2 filings across 2 jurisdictions · filed Jan 31, 2024. View entity profile → Other incidents for this victim →
incident inc_8736b34909154676 · 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.
ME MT
all State AG
Earliest sighting first · deep chronology in Litigation Timeline
Jun 21, 2023
When the intrusion reportedly occurred, per the linked filings
Jun 29, 2023
Reported by MAINE AG filing
J.D. Gilmour & Co. reported a data breach to the Montana Attorney General. The breach was reported on 2024-01-31. The breach occurred from 6/21/2023 to 6/29/2023. 2 Montana residents were affected.
Affected (this filing): 2
Financial services firm J.D. Gilmour experienced a business email compromise event on June 29, 2023, which was also the date of discovery. The incident impacted 1 resident of Maine, with the compromised information including Social Security numbers. The company provided notification to the affected individual on January 16, 2024, and offered 12 months of identity theft protection services.
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.