Clustered 2 filings across 2 jurisdictions · filed Aug 11, 2022. View entity profile → Other incidents for this victim →
incident inc_cec2041579354989 · merge_method deterministic · confidence 100%
Discovered → first regulatory filing
Range of discovered_at dates across filings
PII · Identity (basic)
Time between earliest and latest filing
Not recorded for this incident
Leak precedence · Materiality delta · SEC filing delay — no leak-site claim in this cluster; no SEC 8-K in this cluster.
CA ME
all State AG
Earliest sighting first · deep chronology in Litigation Timeline
Dec 21, 2021 → Dec 29, 2021
When the intrusion reportedly occurred, per the linked filings
Dec 29, 2021
Reported by CALIFORNIA AG filing
Apr 20, 2022
Reported by MAINE AG filing
Biolase, Inc. reported a data breach occurring between Dec 21-29, 2021, where an unauthorized actor accessed the network and exfiltrated files containing names and other personal information. The company engaged forensic specialists, notified law enforcement, and provided credit monitoring via Equifax to affected individuals across multiple US states.
Biolase, Inc. reported an external system breach (hacking) occurring between December 21, 2021, and December 29, 2021. The incident compromised the names and Social Security Numbers of 7,316 individuals, including 31 Maine residents. The breach was discovered on April 20, 2022. Biolase notified affected consumers in writing on August 11, 2022, and provided 12 months of credit monitoring and identity theft restoration services through Equifax.
Affected (this filing): 7,316
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.