Clustered 2 filings across 2 jurisdictions · filed May 27, 2022. View entity profile → Other incidents for this victim →
incident inc_b75a809588e5445a · 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
Dec 15, 2021
When the intrusion reportedly occurred, per the linked filings
Apr 27, 2022
Reported by MAINE AG filing
Acorda Therapeutics Inc reported a data breach to the Montana Attorney General. The breach was reported on 2022-05-27. The breach occurred from 12/15/2021 to 12/16/2021. 9 Montana residents were affected.
Affected (this filing): 9
Acorda Therapeutics, Inc. reported a data breach caused by a phishing incident that occurred on December 15, 2021, and was discovered on April 27, 2022. The breach affected 1,593 individuals, including 3 Maine residents, and involved the compromise of names and Social Security numbers. The company offered 12 months of credit and identity monitoring services through Experian to those affected.
Affected (this filing): 3
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.