Comparison Overview
Hrvatski Telekom

Hrvatski Telekom
Radnička 21, Zagreb, Zagreb, 10000, HR
Last Update: 06/01/2026
Hrvatski Telekom is the market leader and the only company in Croatia providing the full range of telecommunications services, fixed line and mobile telephone services, data transmission, internet and international communications. We are fully committed to customer sati...

AT&T
208 S. Akard Street, Dallas, 75202, US
Last Update: 17/07/2026
We understand that our customers want an easier, less complicated life. We’re using our network, labs, products, services, and people to create a world where everything works together seamlessly, and life is better as a result. How will we continue to drive for thi...
Compliance Ranges Comparison

Hrvatski Telekom







AT&T






Benchmark & Cyber Underwriting Signals
Incidents vs Telecommunications Industry Avg (This Year)
No incidents recorded for Hrvatski Telekom in 2026.
Incidents vs Telecommunications Industry Avg (This Year)
AT&T has 669.23% more incidents than the average of all companies with at least one recorded incident.
Incident History - Hrvatski Telekom (X = Date, Y = Severity)
Hrvatski Telekom cyber incidents detection timeline including parent company and subsidiaries.
Incident History - AT&T (X = Date, Y = Severity)
AT&T cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

Hrvatski Telekom

AT&T
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.