Comparison Overview
Swiss Federal Office of Personnel FOPER

Swiss Federal Office of Personnel FOPER
Eigerstrasse 71, Bern, undefined, 3007, CH
Last Update: 04/12/2025
Staff, our job. Every day, around 38,000 employees work for the enterprise that is Switzerland. How do we find the best people for the most diverse tasks? What instruments do the departments and federal offices need for personnel management? Which modern forms of work ...

LHH
10151 Deerwood Park Boulevard, Building 200, Suite 400, Jacksonville, Florida, US, 32256
Last Update: 02/04/2026
At LHH, we believe work should be meaningful, fulfilling, and connected. Our vision? To create a beautiful working world—a world where people and businesses are empowered to achieve bold ambitions. That's why we've designed solutions to address each stage of the tal...
Compliance Ranges Comparison

Swiss Federal Office of Personnel FOPER







LHH






Benchmark & Cyber Underwriting Signals
Incidents vs Human Resources Services Industry Avg (This Year)
No incidents recorded for Swiss Federal Office of Personnel FOPER in 2026.
Incidents vs Human Resources Services Industry Avg (This Year)
No incidents recorded for LHH in 2026.
Incident History - Swiss Federal Office of Personnel FOPER (X = Date, Y = Severity)
Swiss Federal Office of Personnel FOPER cyber incidents detection timeline including parent company and subsidiaries.
Incident History - LHH (X = Date, Y = Severity)
LHH cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

Swiss Federal Office of Personnel FOPER

LHH
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.