Comparison Overview
VDL ETS

VDL ETS
Automotive Campus 59, Helmond, North Brabant, NL, 5708 JZ
Last Update: 02/04/2026
VDL Enabling Transport Solutions (VDL ETS) richt zich op het onderzoeken, ontwikkelen, protobouwen en testen van nieuwe mogelijkheden of concepten voor met name transport gerelateerde activiteiten van VDL-bedrijven. Het doel is om milieuvriendelijke, innovatieve hard- e...

Rencol Components Ltd.
Unit 2, Avonbridge Trading Estate, Bristol, BS11 9QD, GB
Last Update: 01/04/2026
Following 100 years of successful design and manufacturing experience in plastic and metals, Rencol Components has built a truly global supply chain - rapidly expanding our range of high-quality, competitively-priced industrial components. Rencol has developed a mature...
Compliance Ranges Comparison

VDL ETS







Rencol Components Ltd.






Benchmark & Cyber Underwriting Signals
Incidents vs Industrial Machinery Manufacturing Industry Avg (This Year)
No incidents recorded for VDL ETS in 2026.
Incidents vs Industrial Machinery Manufacturing Industry Avg (This Year)
No incidents recorded for Rencol Components Ltd. in 2026.
Incident History - VDL ETS (X = Date, Y = Severity)
VDL ETS cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Rencol Components Ltd. (X = Date, Y = Severity)
Rencol Components Ltd. cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

VDL ETS

Rencol Components Ltd.
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.