Arrow Truck Sales, Inc. reported a data breach to the Montana Attorney General. The breach was reported on 2021-01-08. The breach occurred from 11/16/2020 to 11/30/2020. 5 Montana residents were affected.
Affected (this filing): 5
Clustered 3 filings across 3 jurisdictions · filing window Jan 8, 2021 → Feb 26, 2021. View entity profile → Other incidents for this victim →
incident inc_66480d5a868e4714 · merge_method deterministic · confidence 100%
Discovered → first regulatory filing
Range of discovered_at dates across filings
CA ME MT
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.
all State AG
Earliest sighting first · deep chronology in Litigation Timeline
Nov 16, 2020
When the intrusion reportedly occurred, per the linked filings
Nov 30, 2020
Reported by MAINE AG, CALIFORNIA AG filings
Arrow Truck Sales, Inc. reported a data breach to the Montana Attorney General. The breach was reported on 2021-01-08. The breach occurred from 11/16/2020 to 11/30/2020. 5 Montana residents were affected.
Affected (this filing): 5
Arrow Truck Sales, Inc. experienced an external system breach (hacking) on November 16, 2020, discovered on November 30, 2020. The incident compromised names and Social Security Numbers of 2,579 individuals, including one Maine resident. The company provided written notification on January 8, 2021, and offered 24 months of credit monitoring services through Kroll.
Affected (this filing): 2,579
Arrow Truck Sales, Inc. disclosed a cybersecurity incident where an unauthorized third party gained remote access to its network on or about November 30, 2020. The attacker acquired internal company information, including personal data of affected individuals, and posted it on a publicly accessible website. The company engaged outside cybersecurity experts, contacted law enforcement, and enhanced security protections. Affected individuals were offered two years of complimentary identity monitoring services through Kroll.
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.