Sagent Pharmaceuticals reported a data breach to the Indiana Attorney General. The breach occurred on 2026-02-11 and was reported on 2026-04-17. 4 Indiana residents were affected. 1,383 individuals affected in total.
Affected (this filing): 1,383
Clustered 2 filings across 2 jurisdictions · filing window Apr 17, 2026 → Apr 23, 2026. View entity profile → Other incidents for this victim →
incident inc_3a35c9a69f00428d · 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.
PII · Identity (basic)
IN ME
all State AG
Earliest sighting first · deep chronology in Litigation Timeline
Feb 11, 2026
When the intrusion reportedly occurred, per the linked filings
Mar 23, 2026
Reported by MAINE AG filing
Sagent Pharmaceuticals reported a data breach to the Indiana Attorney General. The breach occurred on 2026-02-11 and was reported on 2026-04-17. 4 Indiana residents were affected. 1,383 individuals affected in total.
Affected (this filing): 1,383
Sagent Pharmaceuticals reported an external system breach (hacking) discovered on March 23, 2026, that occurred on February 11, 2026. The incident affected one Maine resident. Consumer notification was sent on April 17, 2026, with credit monitoring services provided through Equifax for 12 months.
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.