Comparison Overview
Centre de Médecine Préventive (Assurance Maladie)

Centre de Médecine Préventive (Assurance Maladie)
2, Rue du Doyen Jacques Parisot, Vandoeuvre-lès-Nancy, Grand Est, 54500, FR
Last Update: 02/02/2026
Créé en 1969, le Centre de Médecine Préventive est un organisme de la Sécurité Sociale. Il compte 10 sites d’examens de santé répartis en Grand-Est et la Champagne Ardenne. Il participe à la mise en œuvre de la politique de prévention de l’Assurance Maladie et remplit d...

City of Amsterdam
Postbus 202, Amsterdam, 1000 AE, NL
Last Update: 03/04/2026
Working for Amsterdam means working for the most beautiful city in the world. Think of its rich history, the role Amsterdam plays internationally, and events such as Sail, Gay Pride and King’s Day. Of course everybody wants to visit Amsterdam, or work or live here. As ...
Compliance Ranges Comparison

Centre de Médecine Préventive (Assurance Maladie)







City of Amsterdam






Benchmark & Cyber Underwriting Signals
Incidents vs Government Administration Industry Avg (This Year)
No incidents recorded for Centre de Médecine Préventive (Assurance Maladie) in 2026.
Incidents vs Government Administration Industry Avg (This Year)
No incidents recorded for City of Amsterdam in 2026.
Incident History - Centre de Médecine Préventive (Assurance Maladie) (X = Date, Y = Severity)
Centre de Médecine Préventive (Assurance Maladie) cyber incidents detection timeline including parent company and subsidiaries.
Incident History - City of Amsterdam (X = Date, Y = Severity)
City of Amsterdam cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

Centre de Médecine Préventive (Assurance Maladie)

City of Amsterdam
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.