Comparison Overview
Mercy
Mercy
15740 South Outer Forty Road, Chesterfield, 63017 , US
Last Update: 29/03/2026
At Mercy, care is more than a job - it’s a calling. Every day, our caregivers bring compassion, skill and purpose to the communities we serve across Arkansas, Kansas, Missouri and Oklahoma. Whether you're building your career at the bedside, in a clinic or supporting c...
St. Luke's University Health Network
801 Ostrum Street, Bethlehem, 18015, US
Last Update: 30/03/2026
Founded in 1872, St. Luke’s University Health Network (SLUHN) is a fully integrated, regional, non-profit network of more than 23,000 employees providing services at 16 campuses and 350+ outpatient sites. With annual net revenue of $4 billion, the Network’s service area...
Compliance Ranges Comparison
Mercy
St. Luke's University Health Network
Benchmark & Cyber Underwriting Signals
Incidents vs Hospitals and Health Care Industry Avg (This Year)
No incidents recorded for Mercy in 2026.
Incidents vs Hospitals and Health Care Industry Avg (This Year)
No incidents recorded for St. Luke's University Health Network in 2026.
Incident History - Mercy (X = Date, Y = Severity)
Mercy cyber incidents detection timeline including parent company and subsidiaries.
Incident History - St. Luke's University Health Network (X = Date, Y = Severity)
St. Luke's University Health Network cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
Mercy
St. Luke's University Health Network
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.