Comparison Overview
Geomatics Unit - ULiège

Geomatics Unit - ULiège
Quartier Agora, Liège, Liège, 4020, BE
Last Update: 27/01/2026
The Geomatics Unit brings together researchers and teachers in the field of geomatics. It is part of the Department of Geography (Faculty of Sciences) at the University of Liege. The Unit enjoys strong international recognition. It also plays an important role with Belg...

Aarhus University
Nordre Ringgade 1 DK- Aarhus, Aarhus, 8000, DK
Last Update: 01/04/2026
About Aarhus University Aarhus University is a leading international research university covering all scientific areas with a staff of 11.000 employees and 44.500 students, the majority are post-graduate students enrolled on Master’s and PhD programmes. Aarhus Univer...
Compliance Ranges Comparison

Geomatics Unit - ULiège







Aarhus University






Benchmark & Cyber Underwriting Signals
Incidents vs Research Industry Avg (This Year)
No incidents recorded for Geomatics Unit - ULiège in 2026.
Incidents vs Research Industry Avg (This Year)
No incidents recorded for Aarhus University in 2026.
Incident History - Geomatics Unit - ULiège (X = Date, Y = Severity)
Geomatics Unit - ULiège cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Aarhus University (X = Date, Y = Severity)
Aarhus University cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

Geomatics Unit - ULiège

Aarhus 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.