Comparison Overview
Apollo: delivering our electronic health record

Apollo: delivering our electronic health record
London, GB
Last Update: 01/03/2026
Apollo is our name for an ambitious programme to introduce Epic (a leading electronic patient records system) across Guy’s and St Thomas’ and at King's College Hospital. Epic is due to launch on 5 October 2023. It will transform the way that we work by replacing our ...

The Cigna Group
900 Cottage Grove Rd, Bloomfield, 06002, US
Last Update: 02/04/2026
The Cigna Group is a global health company committed to creating a better future built on the vitality of every individual and every community. We relentlessly challenge ourselves to partner and innovate solutions for better health. The Cigna Group includes products a...
Compliance Ranges Comparison

Apollo: delivering our electronic health record







The Cigna Group






Benchmark & Cyber Underwriting Signals
Incidents vs Hospitals and Health Care Industry Avg (This Year)
No incidents recorded for Apollo: delivering our electronic health record in 2026.
Incidents vs Hospitals and Health Care Industry Avg (This Year)
No incidents recorded for The Cigna Group in 2026.
Incident History - Apollo: delivering our electronic health record (X = Date, Y = Severity)
Apollo: delivering our electronic health record cyber incidents detection timeline including parent company and subsidiaries.
Incident History - The Cigna Group (X = Date, Y = Severity)
The Cigna Group cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

Apollo: delivering our electronic health record

The Cigna Group
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.