Clustered 3 filings across 3 jurisdictions · filing window Sep 20, 2022 → Oct 20, 2022. View entity profile → Other incidents for this victim →
incident inc_42ba1bafaa084c80 · merge_method deterministic · confidence 100%
Discovered → first regulatory filing
Gap between first leak claim and first regulatory filing
Time between earliest and latest filing
Not recorded for this incident
Discovery variance · Materiality delta · SEC filing delay — no SEC 8-K in this cluster; needs two dated filings.
CT ME
Leak Site · HHS OCR · State AG
Earliest sighting first · deep chronology in Litigation Timeline
Oct 9, 2022
When the intrusion reportedly occurred, per the linked filings
Oct 9, 2022
Reported by MAINE AG filing
Sigmund Software, LLC reported to HHS on 2022-10-20 a Hacking/IT Incident affecting 4,767 individuals. Breached information located on Network Server. The incident involved a ransomware attack encrypting PHI (names, addresses, DOB, driver's license, SSN, health info). The business associate notified HHS, individuals, and media, offered credit monitoring, and implemented security safeguards.
Affected (this filing): 4,767
Sigmund Software, LLC experienced an external system breach on October 9, 2022, which was also discovered on the same day. The breach compromised the Social Security Numbers of affected individuals. The company provided written notification to affected consumers on October 20, 2022, and offered 12 months of credit monitoring and identity protection services through Experian.
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.