Orgill, Inc. reported a data breach to the Montana Attorney General. The breach was reported on 2021-12-08. The breach occurred from 10/28/2021 to 10/31/2021. 2 Montana residents were affected.
Affected (this filing): 2
Clustered 2 filings across 2 jurisdictions · filed Dec 8, 2021. View entity profile → Other incidents for this victim →
incident inc_ffeebee19c994978 · 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
Oct 28, 2021
When the intrusion reportedly occurred, per the linked filings
Oct 31, 2021
Reported by MAINE AG filing
Orgill, Inc. reported a data breach to the Montana Attorney General. The breach was reported on 2021-12-08. The breach occurred from 10/28/2021 to 10/31/2021. 2 Montana residents were affected.
Affected (this filing): 2
Orgill, Inc. reported a data breach to the Maine Attorney General, indicating that an external system breach (hacking) occurred on October 28, 2021. The breach was discovered on October 31, 2021. The incident affected 4 Maine residents, compromising their names and Social Security numbers. In response, Orgill, Inc. began notifying affected individuals on December 8, 2021, and offered one year of identity theft protection services through Experian.
Affected (this filing): 4
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.