Comparison Overview
Brunel University London Pathway College

Brunel University London Pathway College
Brunel University London Pathway College, Brunel University, Uxbridge, Greater London, UB8 3PH, GB
Last Update: 11/04/2026
Brunel University London Pathway College offers first-class pathway programmes leading to undergraduate and postgraduate degrees at Brunel University London. Our pathways include Foundation and First Year programmes for candidates who do not meet the direct entry crite...

University of Kentucky
Lexington, KY, US, 40506
Last Update: 02/04/2026
The University of Kentucky is a public, research-extensive, land grant university dedicated to improving people's lives through excellence in teaching, research, health care, cultural enrichment, and economic development for over 150 years. The University of Kentucky...
Compliance Ranges Comparison

Brunel University London Pathway College







University of Kentucky






Benchmark & Cyber Underwriting Signals
Incidents vs Higher Education Industry Avg (This Year)
No incidents recorded for Brunel University London Pathway College in 2026.
Incidents vs Higher Education Industry Avg (This Year)
No incidents recorded for University of Kentucky in 2026.
Incident History - Brunel University London Pathway College (X = Date, Y = Severity)
Brunel University London Pathway College cyber incidents detection timeline including parent company and subsidiaries.
Incident History - University of Kentucky (X = Date, Y = Severity)
University of Kentucky cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

Brunel University London Pathway College

University of Kentucky
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.