Bradford-Scott Data, LLC reported a data breach to the Montana Attorney General. The breach was reported on 2024-02-13. The breach occurred from 5/19/2023 to 5/28/2023. 66 Montana residents were affected.
Affected (this filing): 66
Clustered 2 filings across 2 jurisdictions · filing window Feb 13, 2024 → Feb 29, 2024. View entity profile → Other incidents for this victim →
incident inc_fa207906db2e4ce2 · merge_method human · 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
May 19, 2023
When the intrusion reportedly occurred, per the linked filings
Dec 10, 2023
Reported by MAINE AG filing
Bradford-Scott Data, LLC reported a data breach to the Montana Attorney General. The breach was reported on 2024-02-13. The breach occurred from 5/19/2023 to 5/28/2023. 66 Montana residents were affected.
Affected (this filing): 66
Bradford-Scott Data, LLC, a service provider, experienced an external system breach on May 19, 2023, discovered on December 10, 2023. The incident affected 36 Maine residents, compromising their names and Social Security numbers. The company notified the affected individuals on February 26-27, 2024, and offered 12 months of identity theft protection services through IDX.
Affected (this filing): 36
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.