Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal') (CWE-22) in the Kibana Fleet feature can lead to the unauthorized deletion of internal resources via Path Traversal (CAPEC-126). A low-privileged user holding Fleet write access could cause a subsequent administrative delete action to act on unintended internal resources. Exploitation requires an administrator to interact with the affected Fleet interface.
Allocation of Resources Without Limits or Throttling (CWE-770) in Kibana can lead to a denial of service via Excessive Allocation (CAPEC-130). An authenticated user with low-level privileges could submit a specially crafted request that causes Kibana to consume an unbounded amount of memory, rendering it unavailable to all users.
Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal') (CWE-22) in the Kibana Fleet feature can lead to the unauthorized deletion of privileged resources via Path Traversal (CAPEC-126). A low-privileged user holding Fleet Settings write access could cause a subsequent administrative action to act on unintended internal resources, resulting in the deletion of privileged resources such as user accounts and other organizational assets. Exploitation requires an administrator to interact with the affected Fleet interface.
Incorrect Authorization (CWE-863) in the Kibana machine learning feature can lead to information disclosure via Exploiting Incorrectly Configured Access Control Security Levels (CAPEC-180). An authenticated user holding machine learning job management privileges within a single Kibana space could cause a job's saved object to become accessible across all spaces in the Kibana instance, without holding access rights to those additional spaces.
Missing Authorization (CWE-862) in Kibana can lead to information disclosure via Privilege Abuse (CAPEC-122). An authorization control was not applied to an internal Kibana APM integration function, allowing any authenticated Kibana user to read APM server credentials that should be restricted to users holding APM or Fleet administrative privileges.
Missing Authorization (CWE-862) in the Kibana Entity Store feature can lead to unauthorized credential creation via Accessing Functionality Not Properly Constrained by ACLs (CAPEC-1). An authenticated user holding only low-privilege Security feature access could invoke an administrative operation that creates and persists Elasticsearch API keys under the caller's identity, bypassing the elevated cluster and Kibana privileges that the documented Entity Store setup flow requires.
Execution with Unnecessary Privileges (CWE-250) in the Kibana machine learning feature can lead to information disclosure via Privilege Abuse (CAPEC-122). An operation available to users holding only read access to the machine learning feature was performed with an internal service identity rather than the identity of the requesting user. Such a user could therefore receive data from Elasticsearch indices they are not authorized to read. No Elasticsearch cluster or index privileges are required.
Allocation of Resources Without Limits or Throttling (CWE-770) in Kibana can lead to a denial of service via Excessive Allocation (CAPEC-130). An authenticated user can submit a specially crafted request that causes excessive resource consumption, which may render Kibana unavailable.
Allocation of Resources Without Limits or Throttling (CWE-770) in Kibana can lead to a denial of service via Excessive Allocation (CAPEC-130). An authenticated user with low-level permissions could submit a specially crafted request that causes excessive resource consumption, which may render Kibana unavailable.
Missing Authorization (CWE-862) in Kibana can lead to cross-space information disclosure and unauthorized data modification via Privilege Abuse (CAPEC-122). Kibana Machine Learning carries out its Elasticsearch operations with elevated internal permissions and relies on a per-request space filter to keep the machine learning data of one space separated from another. Part of the Machine Learning functionality did not apply that filter, so operations issued from one space were carried out against the machine learning data of every space in the deployment.