Comparison Overview
Opening Ceremony

Opening Ceremony
undefined, New York, undefined, undefined, US
Last Update: 04/04/2026
Opening Ceremony was founded in 2002 by two friends from UC Berkeley, Carol Lim and Humberto Leon, as a place to share their passions for travel, art, and fashion. Inspired by a trip to Hong Kong, the two decided to leave their jobs in corporate fashion to realize their...

URBN (Urban Outfitters, Anthropologie Group, Free People & Nuuly)
5000 South Broad Street, Philadelphia, 19112, US
Last Update: 01/04/2026
URBN Urban Outfitters, Inc. (www.urbn.com) is a portfolio of global consumer brands comprised of Anthropologie, Anthropologie Weddings, Free People, FP Movement, Terrain, Urban Outfitters, Nuuly, Reclectic, and Menus & Venues. At URBN, we Lead with Creativity…. Creativi...
Compliance Ranges Comparison

Opening Ceremony







URBN (Urban Outfitters, Anthropologie Group, Free People & Nuuly)






Benchmark & Cyber Underwriting Signals
Incidents vs Retail Apparel and Fashion Industry Avg (This Year)
No incidents recorded for Opening Ceremony in 2026.
Incidents vs Retail Apparel and Fashion Industry Avg (This Year)
No incidents recorded for URBN (Urban Outfitters, Anthropologie Group, Free People & Nuuly) in 2026.
Incident History - Opening Ceremony (X = Date, Y = Severity)
Opening Ceremony cyber incidents detection timeline including parent company and subsidiaries.
Incident History - URBN (Urban Outfitters, Anthropologie Group, Free People & Nuuly) (X = Date, Y = Severity)
URBN (Urban Outfitters, Anthropologie Group, Free People & Nuuly) cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

Opening Ceremony

URBN (Urban Outfitters, Anthropologie Group, Free People & Nuuly)
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.