Comparison Overview
Kempinski Hotels

Kempinski Hotels
Maximilianstrasse 17, Munich, 80539, DE
Last Update: 01/04/2026
Founded in Germany in 1897, Kempinski Hotels has long reflected the finest traditions of European hospitality. Today, as ever, Kempinski is synonymous with distinctive luxury. Located in many of the world's most well-known cities and resorts, the Kempinski collection i...

Accor
82 rue Henri Farman, Issy-les-Moulineaux, Paris Region, FR, 92130
Last Update: 14/06/2026
We are Accor We are more than 290,000 hospitality experts placing people at the heart of what we do, creating emotion for our guests, and nurturing passion for service and achievement beyond limits. Building on the strength of our teams and of our fully integrated ecos...
Compliance Ranges Comparison

Kempinski Hotels







Accor






Benchmark & Cyber Underwriting Signals
Incidents vs Hospitality Industry Avg (This Year)
No incidents recorded for Kempinski Hotels in 2026.
Incidents vs Hospitality Industry Avg (This Year)
No incidents recorded for Accor in 2026.
Incident History - Kempinski Hotels (X = Date, Y = Severity)
Kempinski Hotels cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Accor (X = Date, Y = Severity)
Accor cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

Kempinski Hotels

Accor
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.