Comparison Overview
Leidos Gibbs & Cox

Leidos Gibbs & Cox
N/A
Last Update: 11/12/2025
Leidos Gibbs & Cox is an engineering and design firm specializing naval architecture, marine engineering, and consulting engineering. The firm is headquartered in Arlington, Virginia with offices in New York City; Chesapeake, Virginia; Newport News, Virginia; New Orlean...

Hapag-Lloyd AG
Ballindamm 25, Hamburg, DE, 20095
Last Update: 01/04/2026
About Hapag-Lloyd With a fleet of 313 modern container ships and a total transport capacity of 2.5 million TEU, Hapag-Lloyd is one of the world’s leading liner shipping companies. In the Liner Shipping segment, the Company has around 14,000 employees and 400 offices in ...
Compliance Ranges Comparison

Leidos Gibbs & Cox







Hapag-Lloyd AG






Benchmark & Cyber Underwriting Signals
Incidents vs Maritime Transportation Industry Avg (This Year)
No incidents recorded for Leidos Gibbs & Cox in 2026.
Incidents vs Maritime Transportation Industry Avg (This Year)
No incidents recorded for Hapag-Lloyd AG in 2026.
Incident History - Leidos Gibbs & Cox (X = Date, Y = Severity)
Leidos Gibbs & Cox cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Hapag-Lloyd AG (X = Date, Y = Severity)
Hapag-Lloyd AG cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

Leidos Gibbs & Cox

Hapag-Lloyd AG
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.