Clustered 2 filings across 2 jurisdictions · filed Jul 9, 2026. View entity profile → Other incidents for this victim →
incident inc_f0ab2833d01d4e67 · 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.
NH VT
all State AG
Earliest sighting first · deep chronology in Litigation Timeline
Dec 6, 2025
When the intrusion reportedly occurred, per the linked filings
Dec 6, 2025
Reported by NEW HAMPSHIRE AG filing
Brooks, Cook & Associates notified the New Hampshire Attorney General of a cybersecurity incident involving its data center provider. Unauthorized access occurred on December 6, 2025, exposing the names and Social Security numbers of two New Hampshire residents. Notifications were mailed on July 9, 2026, offering credit monitoring services.
Affected (this filing): 2
Brooks, Cook & Associates reported a data breach to the Vermont Attorney General. The breach was reported to the AGO on 2026-07-09. The reporting organization type is Financial Services. 1 Vermont residents were affected. Categories of data breached: Social Security Numbers.
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.