Comparison Overview
Benton County, WA Government

Benton County, WA Government
620 Market St, Prosser, 99350, US
Last Update: 31/03/2026
Benton County is located in south-central Washington. The county seat is located in Prosser, and its largest city is Kennewick. Benton County was created on March 8, 1905 and was named after U.S. Senator Thomas Hart Benton. Benton County operates under the plural execut...

Department of Health (Philippines)
San Lazaro Compound, Rizal Avenue, Santa Cruz, Manila City, 1014, PH
Last Update: 01/04/2026
The Philippine Department of Health (abbreviated as DOH; Filipino: Kagawaran ng Kalusugan) is the executive department of the Philippine government responsible for ensuring access to basic public health services by all Filipinos through the provision of quality health c...
Compliance Ranges Comparison

Benton County, WA Government







Department of Health (Philippines)






Benchmark & Cyber Underwriting Signals
Incidents vs Government Administration Industry Avg (This Year)
No incidents recorded for Benton County, WA Government in 2026.
Incidents vs Government Administration Industry Avg (This Year)
No incidents recorded for Department of Health (Philippines) in 2026.
Incident History - Benton County, WA Government (X = Date, Y = Severity)
Benton County, WA Government cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Department of Health (Philippines) (X = Date, Y = Severity)
Department of Health (Philippines) cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

Benton County, WA Government

Department of Health (Philippines)
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.