RSCA A.I CyberSecurity Scoring
03/12/2025
Access Monitoring Plan
Access Monitoring Plan
No incidents recorded for Research Support Centre, A*STAR in 2026.
No incidents recorded for Research Support Centre, A*STAR in 2026.
No incidents recorded for Research Support Centre, A*STAR in 2026.
PRIVACY POLICY at the University of Copenhagen: https://informationssikkerhed.ku.dk/english/protection-of-information-privacy/privacy-policy/ With over 40,000 students and more than 9,000 employees, the University of Copenhagen is the largest institution of research and education in Denmark. The purpose of the University – to quote the University Statute – is to ’conduct research and provide further education to the highest academic level’. Approximately one hundred different institutes, departments, laboratories, centres, museums, etc., form the nucleus of the University, where professors, lecturers and other academic staff, as well as most of the technical and administrative personnel, carry out their daily work, and where teaching takes place. These activities take place in various environments ranging from the plant world of the Botanical Gardens, through high-technology laboratories and auditoriums, to the historic buildings and lecture rooms of Frue Plads and other locations.
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 University is among the top 100 universities in the world. The aim of the university is to sustain and enhance a high standard in both research and education, which has placed it among the international elite. Aarhus University was established in 1928 as a small private initiative. It has since grown to become a leading public research university with international reach covering all academic fields and address basic, applied and strategic research as well as the research-based consultancy provided to public authorities and private business. One of Aarhus University’s focus areas is talent development. An activity considered so important that it is singled out as one of the four core activities in the Aarhus University strategy alongside excellent research, world-class education and inspiring research-based consultancy. Research at Aarhus University is both organised in traditional departments under the four faculties and in interdisciplinary research centres. In addition, Aarhus University researchers engage in research collaboration under the auspices of Knowledge Management Centres with external partners such as government organisations, private enterprises, NGOs and Aarhus University’s wide range of international partner universities.
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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.
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linkedin_id=axa' -H 'apikey: YOUR_API_KEY_HERE'
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