Comparison Overview
St. Peter's International School

St. Peter's International School
Quinta dos Barreleiros CCI 3952, Palmela, Setubal, PT, 2950-201
Last Update: 01/04/2026
St Peters International School is a well-established private day & boarding school in Portugal where every student has access to the best opportunities to achieve their full academic and personal potential, from 4 months to 18 years old. At St Peter’s, we are dedicated...

Toronto District School Board
5050 Yonge Street, Toronto, M2N 5N8, CA
Last Update: 02/04/2026
The Toronto District School Board (TDSB) is the largest and one of the most diverse school boards in Canada, and recognized by Forbes and Statista as one of Canada's Best Employers for Diversity for 2023. We serve more than 239,000 students in 582 schools throughout Tor...
Compliance Ranges Comparison

St. Peter's International School







Toronto District School Board






Benchmark & Cyber Underwriting Signals
Incidents vs Primary and Secondary Education Industry Avg (This Year)
No incidents recorded for St. Peter's International School in 2026.
Incidents vs Primary and Secondary Education Industry Avg (This Year)
No incidents recorded for Toronto District School Board in 2026.
Incident History - St. Peter's International School (X = Date, Y = Severity)
St. Peter's International School cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Toronto District School Board (X = Date, Y = Severity)
Toronto District School Board cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

St. Peter's International School

Toronto District School Board
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.