Comparison Overview
The Suburban Collection
The Suburban Collection
1795 Maplelawn, Troy, 48084, US
Last Update: 24/03/2026
The Suburban Collection was established in 1948 when Richard Fischer opened Suburban Motors as a single point Oldsmobile dealership in Birmingham, MI. Suburban has since grown to more than 2,500 team members representing 33 brands at more than 50 locations throughout Mi...
Discount Tire
20225 N. Scottsdale Rd., Scottsdale, AZ, US, 85255
Last Update: 02/04/2026
With more than 1,200 stores in the United States, Discount Tire has grown to become the leading independent retailer of tires and wheels. The company was founded in 1960 when founder Bruce T. Halle rented a building on Stadium Boulevard in Ann Arbor, MI. Although the in...
Compliance Ranges Comparison
The Suburban Collection
Discount Tire
Benchmark & Cyber Underwriting Signals
Incidents vs Motor Vehicle Manufacturing Industry Avg (This Year)
No incidents recorded for The Suburban Collection in 2026.
Incidents vs Motor Vehicle Manufacturing Industry Avg (This Year)
No incidents recorded for Discount Tire in 2026.
Incident History - The Suburban Collection (X = Date, Y = Severity)
The Suburban Collection cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Discount Tire (X = Date, Y = Severity)
Discount Tire cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
The Suburban Collection
Discount Tire
FAQ
Latest Global CVEs
Uncontrolled Resource Consumption (CWE-400) in Kibana can lead to denial of service via Excessive Allocation (CAPEC-130). A low-privileged authenticated user can send a specially crafted request to a Kibana machine learning feature, causing the server to exhaust available memory and become unavailable to all users.
Uncontrolled Resource Consumption (CWE-400) in Kibana can lead to denial of service via Excessive Allocation (CAPEC-130). An authenticated attacker with low-privilege access can trigger a denial of service condition in Kibana by sending a specially crafted, oversized request payload. Processing this user-supplied input requires resource-intensive memory allocation that can exhaust the available heap memory in the Kibana process, causing it to crash and become unavailable to all users.
Authorization Bypass Through User-Controlled Key (CWE-639) in Kibana can lead to information disclosure via user-supplied identifiers that reference scheduled query result data from Kibana Spaces the requester is not authorized to access.
Incorrect Authorization (CWE-863) in Kibana can lead to integrity compromise of Machine Learning audit and notification records via Accessing Functionality Not Properly Constrained by ACLs (CAPEC-1). A vulnerability exists in Kibana's Machine Learning functionality where a Machine Learning management endpoint performs an insufficient authorization check. The endpoint validates only a coarse privilege level but does not verify that the requesting user has access to the specific Machine Learning job or notification resources provided in the request. As a result, a low-privileged user with Machine Learning access in any Kibana space can manipulate Machine Learning audit and notification records for arbitrary jobs—including jobs in other spaces or belonging to other users—by leveraging Kibana's internally elevated credentials to write to restricted Machine Learning system indices that the user cannot access directly.
Uncontrolled Recursion (CWE-674) in Elasticsearch can lead to denial of service via a specially crafted search request submitted by a low-privileged authenticated user. A user with read-level index access can submit a request that triggers unbounded recursive processing within the Elasticsearch query evaluation component, causing a fatal error that terminates the affected node. In single-node deployments, this results in complete service outage; in multi-node clusters, it causes repeated node restarts and sustained availability degradation.