Comparison Overview
WTW Financial, Executive & Professional Risks

WTW Financial, Executive & Professional Risks
51 Lime Street, London, EC3M 7DQ, GB
Last Update: 02/04/2026
We have teams of experts worldwide that advise senior management on Financial Lines of business such as Executive and Professional Risks, Credit, Political and Terrorism insurance. We have teams based in Great Britain, North America, Western Europe, Asia, Latin America,...

Progressive Insurance
300 North Commons Blvd, Mayfield Village, 44143, US
Last Update: 04/04/2026
Every journey has a beginning, and wherever you are on your career path, we want to help you along the way. At Progressive, we exist to help people move forward and live fully. We strive to create a welcoming and flexible work environment for everyone, where employees ...
Compliance Ranges Comparison

WTW Financial, Executive & Professional Risks







Progressive Insurance






Benchmark & Cyber Underwriting Signals
Incidents vs Insurance Industry Avg (This Year)
No incidents recorded for WTW Financial, Executive & Professional Risks in 2026.
Incidents vs Insurance Industry Avg (This Year)
No incidents recorded for Progressive Insurance in 2026.
Incident History - WTW Financial, Executive & Professional Risks (X = Date, Y = Severity)
WTW Financial, Executive & Professional Risks cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Progressive Insurance (X = Date, Y = Severity)
Progressive Insurance cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

WTW Financial, Executive & Professional Risks

Progressive Insurance
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.