Comparison Overview
Edelman Financial Engines

Edelman Financial Engines
3315 Scott Blvd, Santa Clara, 95054, US
Last Update: 24/04/2026
For more than 35 years, Edelman Financial Engines has been helping people move their financial lives forward. Our founders set the tone for our mission – giving individual investors access to sophisticated investment modeling tools that were previously available only t...

Fannie Mae
1100 15th St NW, Washington, District of Columbia, US, 20005
Last Update: 19/06/2026
Fannie Mae creates opportunities for people to buy, refinance, or rent a home. We are a leading source of mortgage financing in all markets and at all times. We ensure the availability of affordable mortgage loans. The financing solutions we develop make homeownership a...
Compliance Ranges Comparison

Edelman Financial Engines







Fannie Mae






Benchmark & Cyber Underwriting Signals
Incidents vs Financial Services Industry Avg (This Year)
Edelman Financial Engines has 14.29% more incidents than the average of same-industry companies with at least one recorded incident.
Incidents vs Financial Services Industry Avg (This Year)
No incidents recorded for Fannie Mae in 2026.
Incident History - Edelman Financial Engines (X = Date, Y = Severity)
Edelman Financial Engines cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Fannie Mae (X = Date, Y = Severity)
Fannie Mae cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

Edelman Financial Engines

Fannie Mae
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.