Clustered 2 filings across 2 jurisdictions · filed Oct 20, 2021. View entity profile → Other incidents for this victim →
incident inc_11aa8db37acc437d · merge_method deterministic · confidence 100%
Discovered → first regulatory filing
Range of discovered_at dates across filings
Identity (basic) · Government ID
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.
ME NH
all State AG
Earliest sighting first · deep chronology in Litigation Timeline
May 24, 2021 → May 25, 2021
When the intrusion reportedly occurred, per the linked filings
Sep 22, 2021
Reported by MAINE AG, NEW HAMPSHIRE AG filings
Toyo Tanso, USA experienced an external system breach (hacking) between May 24, 2021, and May 25, 2021. The breach was discovered on September 22, 2021. The compromised information includes names and Social Security numbers. One Maine resident was affected. The company offered one year of credit monitoring and identity theft protection services through Experian.
Affected (this filing): 1
Toyo Tanso, USA notified the New Hampshire Attorney General of a security incident affecting one NH resident. Unauthorized access occurred May 24-25, 2021. The company detected the breach and determined on September 22, 2021, that a resident's SSN and financial account number may have been accessed. Toyo Tanso engaged a cybersecurity firm, notified law enforcement, and offered one year of credit monitoring via 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.