Clustered 2 filings across 2 jurisdictions · filing window Jan 12, 2026 → Jan 13, 2026. View entity profile → Other incidents for this victim →
incident inc_72b82aeed8ae4fb1 · 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.
IN TX
all State AG
Earliest sighting first · deep chronology in Litigation Timeline
Oct 1, 2025
When the intrusion reportedly occurred, per the linked filings
Dec 1, 2025
Reported by TEXAS AG filing
Carranco & Lawson PC reported a data breach to the Indiana Attorney General. The breach occurred on 2025-10-01 and was reported on 2026-01-12. 1 Indiana residents were affected. 474 individuals affected in total.
Affected (this filing): 474
Carranco & Lawson, P.C. based in Laredo, Texas, a financial services entity reported a data breach to the Texas Attorney General. The breach was discovered on 2025-12-01 and reported on 2026-01-13. 447 Texas residents were affected. 474 individuals affected in total. Types of information involved: Name of individual;Social Security Number Information. Consumers were notified via U.S. Mail.
Affected (this filing): 447
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.