Comparison Overview
The Nature Conservancy in Alaska
The Nature Conservancy in Alaska
715 L St, Anchorage, 99501, US
Last Update: 31/01/2026
We work in communities to help nature and people. In Alaska, where people and the natural world are so inextricably linked, our approach helps create lasting results. All across the 49th state, The Nature Conservancy is at work protecting the Alaska we know and love.
IEEE
455 Hoes Lane, Piscataway, 08854, US
Last Update: 01/04/2026
IEEE is the world’s largest technical professional organization and is a public charity dedicated to advancing technological innovation and excellence for the benefit of humanity. IEEE and its members inspire a global community through its highly cited publications, con...
Compliance Ranges Comparison
The Nature Conservancy in Alaska
IEEE
Benchmark & Cyber Underwriting Signals
Incidents vs Non-profit Organizations Industry Avg (This Year)
No incidents recorded for The Nature Conservancy in Alaska in 2026.
Incidents vs Non-profit Organizations Industry Avg (This Year)
No incidents recorded for IEEE in 2026.
Incident History - The Nature Conservancy in Alaska (X = Date, Y = Severity)
The Nature Conservancy in Alaska cyber incidents detection timeline including parent company and subsidiaries.
Incident History - IEEE (X = Date, Y = Severity)
IEEE cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
The Nature Conservancy in Alaska
IEEE
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.