Comparison Overview
The University of Texas at Austin
The University of Texas at Austin
1 University Station, Austin, TX, US, 78712
Last Update: 02/04/2026
The University of Texas at Austin is one of the largest public universities in the United States. Founded in 1883, the University has grown from a single building, eight teachers, two departments and 221 students to a 350-acre main campus with 21,000 faculty and staff, ...
University of South Carolina
Columbia, SC, US, 29208
Last Update: 02/04/2026
With thriving academic and research excellence and a lively, welcoming student experience, the University of South Carolina brings the opportunities of higher education to new generations. South Carolina's unrivaled college experience has been sought by students, facul...
Compliance Ranges Comparison
The University of Texas at Austin
University of South Carolina
Benchmark & Cyber Underwriting Signals
Incidents vs Higher Education Industry Avg (This Year)
No incidents recorded for The University of Texas at Austin in 2026.
Incidents vs Higher Education Industry Avg (This Year)
No incidents recorded for University of South Carolina in 2026.
Incident History - The University of Texas at Austin (X = Date, Y = Severity)
The University of Texas at Austin cyber incidents detection timeline including parent company and subsidiaries.
Incident History - University of South Carolina (X = Date, Y = Severity)
University of South Carolina cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
The University of Texas at Austin
University of South Carolina
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.