Comparison Overview
University of Tehran

University of Tehran
16 Azar Street, Enghlab Avenue, Tehran, 1417466191, IR
Last Update: 01/04/2026
University of Tehran, an iconic institution of higher education in Iran, traces its origins back seven centuries to its foundation as a houza (traditional religious school). Over time, it evolved from this religious structure into a modern academic institution. About a ...

University of California, San Francisco
530 Parnassus Ave, San Francisco, California, US, 94122
Last Update: 01/04/2026
UC San Francisco is driven by the idea that when the best research, the best education and the best patient care converge, great breakthroughs are achieved. We pursue this integrated excellence with singular focus, fueled by collaboration among our top-ranked profession...
Compliance Ranges Comparison

University of Tehran







University of California, San Francisco






Benchmark & Cyber Underwriting Signals
Incidents vs Higher Education Industry Avg (This Year)
No incidents recorded for University of Tehran in 2026.
Incidents vs Higher Education Industry Avg (This Year)
No incidents recorded for University of California, San Francisco in 2026.
Incident History - University of Tehran (X = Date, Y = Severity)
University of Tehran cyber incidents detection timeline including parent company and subsidiaries.
Incident History - University of California, San Francisco (X = Date, Y = Severity)
University of California, San Francisco cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

University of Tehran

University of California, San Francisco
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.