Comparison Overview
Nature Open Library

Nature Open Library
N/A
Last Update: 15/01/2026
Nature Open Library is a Pierre Fabre initiative aiming to valorize the potential of natural products in Life Sciences. It is a way to share our plant natural extracts library and our expertise, from plant sourcing to final product delivery, with scientific actors (biot...

Bristol Myers Squibb
3401 Princeton Pike, Lawrence Township, 08648, US
Last Update: 20/05/2026
At Bristol Myers Squibb, we work every day to transform patients’ lives through science. That work inspires some of the most interesting, meaningful, and life-changing careers you’ll experience. Join us and pursue innovative ideas alongside some of the brightest minds i...
Compliance Ranges Comparison

Nature Open Library







Bristol Myers Squibb






Benchmark & Cyber Underwriting Signals
Incidents vs Pharmaceutical Manufacturing Industry Avg (This Year)
No incidents recorded for Nature Open Library in 2026.
Incidents vs Pharmaceutical Manufacturing Industry Avg (This Year)
No incidents recorded for Bristol Myers Squibb in 2026.
Incident History - Nature Open Library (X = Date, Y = Severity)
Nature Open Library cyber incidents detection timeline including parent company and subsidiaries.
Incident History - Bristol Myers Squibb (X = Date, Y = Severity)
Bristol Myers Squibb cyber incidents detection timeline including parent company and subsidiaries.
Notable Incidents

Nature Open Library

Bristol Myers Squibb
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.