Comparison Overview
Synopsys - Security IP
Synopsys - Security IP
400 March Road, Ottawa, K2K 3H4, CA
Last Update: 05/03/2026
Synopsys provides a broad portfolio of highly integrated security IP solutions that use a common set of standards-based building blocks and security concepts to enable the most efficient silicon design and highest levels of security for a range of products in the mobile...
Palo Alto Networks
3000 Tannery Way, SANTA CLARA, 95054, US
Last Update: 02/07/2026
Palo Alto Networks, the global cybersecurity leader, is shaping the cloud-centric future with technology that is transforming the way people and organizations operate. Our mission is to be the cybersecurity partner of choice, protecting our digital way of life. We help ...
Compliance Ranges Comparison
Synopsys - Security IP
Palo Alto Networks
Benchmark & Cyber Underwriting Signals
Incidents vs Computer and Network Security Industry Avg (This Year)
Synopsys - Security IP has 11.5% fewer incidents than the average of same-industry companies with at least one recorded incident.
Incidents vs Computer and Network Security Industry Avg (This Year)
Palo Alto Networks has 566.67% more incidents than the average of all companies with at least one recorded incident.
Incident History - Synopsys - Security IP (X = Date, Y = Severity)
Synopsys - Security IP cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Palo Alto Networks (X = Date, Y = Severity)
Palo Alto Networks cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents
Synopsys - Security IP
Palo Alto Networks
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.