| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| 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 to affected Entity Analytics endpoints containing an oversized input value that causes excessive resource consumption, which may render Kibana unavailable. |
| Improper Access Control (CWE-284) in Kibana can lead to unauthorized modification of Entity Analytics Watchlist configuration and potential information disclosure. A low-privileged authenticated user with read-only Security Solution access could perform write operations on watchlist data that should require elevated privileges. Under specific deployment conditions, this could also allow such a user to access data beyond their authorized scope. |
| Authorization Bypass Through User-Controlled Key (CWE-639) in Kibana can lead to unauthorized information disclosure and case attachment integrity compromise via Privilege Abuse (CAPEC-122). An inconsistency in Kibana's file access authorization logic allows a low-privileged authenticated user to retrieve, modify, and delete case attachments that belong to feature areas they are not authorized to access. Because the access control check and the resource retrieval use different resolution mechanisms, an authenticated attacker with limited file management permissions can obtain the contents of, modify, or delete protected case attachments — such as those associated with Security Solution cases — without holding the privileges required to access those features. |
| Uncontrolled Resource Consumption (CWE-400) in Kibana can lead to denial of service via Excessive Allocation (CAPEC-130). An authenticated low-privileged user can exploit an uncontrolled resource consumption vulnerability in Kibana's Canvas functionality by sending a specially crafted request, causing the Kibana server process to terminate and resulting in a denial of service for all users of the affected Kibana instance. |
| Missing Authorization (CWE-862) in Kibana allows an authenticated user to access and modify Cloud Connect configuration and service settings without the required feature privileges, via direct requests to insufficiently protected product endpoints. |
| Unintended Proxy or Intermediary ('Confused Deputy') (CWE-441) in Kibana can lead to unauthorized information exposure via Accessing Functionality Not Properly Constrained by ACLs (CAPEC-1). Under certain conditions, a lower-privileged user can cause data from sources they are not authorized to access to be processed using another user's privileges. |
| 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. |
| Incomplete List of Disallowed Inputs (CWE-184) in Kibana can allow an authenticated attacker with access to the Reporting feature to bypass outbound request restrictions configured by an administrator, causing the reporting service to send requests to network destinations that should be denied by the configured security policy. |
| Missing Authorization (CWE-862) in Kibana can lead to unauthorized information disclosure via Privilege Abuse (CAPEC-122). A user with limited feature privileges can access workflow execution outputs in their Kibana space without the authorization required to do so through the documented API. The accessible data may include sensitive information returned by workflow steps, such as results from connected data sources that the caller would not otherwise be 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. |
| 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. |
| 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. |
| Missing Authorization (CWE-862) in Kibana can lead to unauthorized cross-space information disclosure via user-supplied input that circumvents space-level access control. |
| Improper Input Validation (CWE-20) in Kibana can lead to a denial of service via Input Data Manipulation (CAPEC-153). An authenticated user can submit a specially crafted Fleet policy input that is not correctly validated, which can render Fleet agent, server, and policy management functionality 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 can submit a specially crafted bulk deletion request that causes excessive resource consumption, which may render Kibana unavailable. |
| Insertion of Sensitive Information into Log File (CWE-532) in Kibana can lead to information disclosure. When the optional application performance monitoring (APM) instrumentation is enabled, sensitive request header values could be recorded in application logs, where they may be accessible to operators with log access. |
| Improper Output Neutralization for Logs (CWE-117) in Kibana can lead to log injection via Log Injection-Tampering-Forging (CAPEC-93). An attacker can supply specially crafted input that is written to log files without proper neutralization. When the log files are subsequently viewed in a terminal that interprets control sequences, the injected content may alter the displayed log data. |
| Server-Side Request Forgery (CWE-918) in Kibana allows authenticated users with connector management privileges to bypass the operator-configured connection allowlist. By configuring a Webhook connector with a crafted target, an attacker can cause Kibana to issue outbound requests to destinations that the egress restriction controls were intended to block. |
| Uncontrolled Resource Consumption (CWE-400) in Kibana can lead to denial of service via Excessive Allocation (CAPEC-130). An authenticated low-privileged user can cause Kibana to consume exponentially increasing amounts of memory by submitting a specially crafted Timelion visualization expression containing deeply chained function calls. The resulting data structure grows without bound, exhausting available memory and causing the Kibana service to crash 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 user can send a specially crafted compressed request payload that is processed prior to authorization checks, causing excessive memory and CPU resource consumption that can result in a Kibana instance becoming unresponsive or crashing. |
