Clustered 2 filings across 2 jurisdictions · filing window Nov 3, 2025 → Nov 6, 2025. View entity profile → Other incidents for this victim →
incident inc_bdd944d1677f4c46 · 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.
IN NH
all State AG
Earliest sighting first · deep chronology in Litigation Timeline
Sep 6, 2025
When the intrusion reportedly occurred, per the linked filings
Oct 3, 2025
Reported by NEW HAMPSHIRE AG filing
Priester Holdings LLC reported a data breach to the Indiana Attorney General. The breach occurred on 2025-09-06 and was reported on 2025-11-03. 5 Indiana residents were affected. 345 individuals affected in total.
Affected (this filing): 345
Priester Holdings, LLC notified the New Hampshire Attorney General of unauthorized network access occurring on September 6, 2025. The breach affected approximately two New Hampshire residents, exposing names and Social Security numbers. The company contained the network, engaged forensic investigators, and provided one year of complimentary credit monitoring to affected individuals.
Affected (this filing): 2
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.