Comparison Overview
Usher Institute, The University of Edinburgh

Usher Institute, The University of Edinburgh
5-7 Little France Road, Edinburgh, EH16 4UX, GB
Last Update: 04/12/2025
The Usher Institute works with people, populations and their data to understand and advance the health of individuals and populations through innovative collaborations in a global community. It sits within the School of Population Health Sciences, College of Medicine a...

Texas A&M University
805 Rudder Tower, College Station, TX, US, 77843
Last Update: 19/06/2026
Texas A&M University has a proud history that stretches back to 1876 when The Agricultural and Mechanical College of Texas became the first public institution of higher learning in the state of Texas. Nestled in the heart of the Houston-Dallas-Austin triangle, Texas A&M...
Compliance Ranges Comparison

Usher Institute, The University of Edinburgh







Texas A&M University






Benchmark & Cyber Underwriting Signals
Incidents vs Higher Education Industry Avg (This Year)
No incidents recorded for Usher Institute, The University of Edinburgh in 2026.
Incidents vs Higher Education Industry Avg (This Year)
No incidents recorded for Texas A&M University in 2026.
Incident History - Usher Institute, The University of Edinburgh (X = Date, Y = Severity)
Usher Institute, The University of Edinburgh cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Texas A&M University (X = Date, Y = Severity)
Texas A&M University cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

Usher Institute, The University of Edinburgh

Texas A&M University
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.