Comparison Overview
General Secretariat GS-FDF

General Secretariat GS-FDF
Bundesgasse 3, Berna, undefined, 3011, CH
Last Update: 13/03/2026
The General Secretariat acts as the intermediary between the head of department and the federal offices, and between the cantons, journalists and communication officers. It plans and coordinates the department’s items of business for Parliamentand the Federal Council. I...

State of Tennessee
US
Last Update: 02/04/2026
State government is the largest employer in Tennessee, with approximately 43,500 employees in the three branches of government. The State of Tennessee has approximately 1,300 different job classifications in areas such as administrative, health services, historic preser...
Compliance Ranges Comparison

General Secretariat GS-FDF







State of Tennessee






Benchmark & Cyber Underwriting Signals
Incidents vs Government Administration Industry Avg (This Year)
No incidents recorded for General Secretariat GS-FDF in 2026.
Incidents vs Government Administration Industry Avg (This Year)
No incidents recorded for State of Tennessee in 2026.
Incident History - General Secretariat GS-FDF (X = Date, Y = Severity)
General Secretariat GS-FDF cyber incidents detection timeline including parent company and subsidiaries.
Incident History - State of Tennessee (X = Date, Y = Severity)
State of Tennessee cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

General Secretariat GS-FDF

State of Tennessee
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.