Comparison Overview
Camp Ripley

Camp Ripley
15000 Minnesota Highway 115, Little Falls, MN, 56345, US
Last Update: 05/12/2025
Camp Ripley, is a 53,000-acre regional training installation featuring numerous ranges and state-of-the-art facilities to support military and civilian agency training requirements.

Army National Guard
111 S George Mason Dr, Arlington, 22204, US
Last Update: 01/04/2026
Welcome to the Army National Guard's page on LinkedIn. The Army National Guard, also known as the National Guard, is one component of The Army (which consists of the Active Army, the Army National Guard, and the Army Reserve). National Guard Soldiers serve both commun...
Compliance Ranges Comparison

Camp Ripley







Army National Guard






Benchmark & Cyber Underwriting Signals
Incidents vs Armed Forces Industry Avg (This Year)
No incidents recorded for Camp Ripley in 2026.
Incidents vs Armed Forces Industry Avg (This Year)
No incidents recorded for Army National Guard in 2026.
Incident History - Camp Ripley (X = Date, Y = Severity)
Camp Ripley cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Army National Guard (X = Date, Y = Severity)
Army National Guard cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

Camp Ripley

Army National Guard
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.