Clustered 2 filings across 2 jurisdictions · filing window Jan 8, 2025 → Jan 13, 2025. View entity profile → Other incidents for this victim →
incident inc_58bf88c06a5d4c55 · 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
Nov 22, 2024
When the intrusion reportedly occurred, per the linked filings
Nov 22, 2024
Reported by NEW HAMPSHIRE AG filing
Kafene Inc reported a data breach to the Indiana Attorney General. The breach occurred on 2024-11-22 and was reported on 2025-01-08. 118 Indiana residents were affected. 6,283 individuals affected in total.
Affected (this filing): 6,283
Kafene, Inc. notified the New Hampshire Attorney General of a data security incident discovered on November 22, 2024. An unauthorized actor gained access to the network and potentially downloaded files. One New Hampshire resident was affected. Kafene engaged forensic investigators, notified the FBI, and offered credit monitoring services.
Affected (this filing): 1
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.