Comparison Overview
St. Luke's Health System

St. Luke's Health System
190 East Bannock Street, Boise, Idaho, US, 83712
Last Update: 01/04/2026
As the only Idaho-based, not-for-profit health system, St. Luke’s Health System is dedicated to our mission “To improve the health of people in the communities we serve.” Today that means not only treating you when you’re sick or hurt, but doing everything we can to hel...

Lehigh Valley Health Network
1200 S Cedar Crest Blvd, Allentown, Pennsylvania, US, 18103
Last Update: 03/04/2026
Lehigh Valley Health Network, part of Jefferson Health, is proud to be part of a leading integrated academic health care delivery system. Together, we’re among the top 15 not-for-profit health systems in the U.S., with 65,000 colleagues, 32 hospitals and more than 700 ...
Compliance Ranges Comparison

St. Luke's Health System







Lehigh Valley Health Network






Benchmark & Cyber Underwriting Signals
Incidents vs Hospitals and Health Care Industry Avg (This Year)
No incidents recorded for St. Luke's Health System in 2026.
Incidents vs Hospitals and Health Care Industry Avg (This Year)
No incidents recorded for Lehigh Valley Health Network in 2026.
Incident History - St. Luke's Health System (X = Date, Y = Severity)
St. Luke's Health System cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Lehigh Valley Health Network (X = Date, Y = Severity)
Lehigh Valley Health Network cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

St. Luke's Health System

Lehigh Valley 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.