Max Trans LLC reported a data breach to the Indiana Attorney General. The breach occurred on 2024-11-29 and was reported on 2025-01-27. 1 Indiana residents were affected. 2,200 individuals affected in total.
Affected (this filing): 2,200
Clustered 2 filings across 2 jurisdictions · filing window Jan 27, 2025 → Jan 28, 2025. View entity profile → Other incidents for this victim →
incident inc_b7292a66c95942d4 · 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.
Government ID
IN ME
all State AG
Earliest sighting first · deep chronology in Litigation Timeline
Nov 29, 2024
When the intrusion reportedly occurred, per the linked filings
Jan 2, 2025
Reported by MAINE AG filing
Max Trans LLC reported a data breach to the Indiana Attorney General. The breach occurred on 2024-11-29 and was reported on 2025-01-27. 1 Indiana residents were affected. 2,200 individuals affected in total.
Affected (this filing): 2,200
Max Trans, LLC reported a data breach to the Maine Attorney General, indicating that an external system breach (hacking) occurred on November 29, 2024. The breach was discovered on January 2, 2025, and affected 2 Maine residents. The company offered 12 months of credit monitoring services through Equifax to those affected.
Affected (this filing): 2
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.