elastic CVE Vulnerabilities & Metrics

Uncontrolled Resource Consumption (CWE-400) in Kibana can lead denial of service via Excessive Allocation (CAPEC-130)

Uncontrolled Resource Consumption (CWE-400) in Elasticsearch can lead denial of service via Excessive Allocation (CAPEC-130)

Uncontrolled Resource Consumption (CWE-400) in Elasticsearch can lead denial of service via Excessive Allocation (CAPEC-130)

Uncontrolled Resource Consumption (CWE-400) in Elasticsearch can lead denial of service via Excessive Allocation (CAPEC-130)

Uncontrolled Resource Consumption (CWE-400) in Elasticsearch can lead denial of service via Excessive Allocation (CAPEC-130)

Uncontrolled Resource Consumption (CWE-400) in Elasticsearch can lead to denial of service via Excessive Allocation (CAPEC-130).

Uncontrolled Resource Consumption (CWE-400) in Elasticsearch can lead to denial of service via Excessive Allocation (CAPEC-130).

Incorrect Authorization (CWE-863) in Kibana can lead to privilege escalation via Input Data Manipulation (CAPEC-153). Elasticsearch cluster privilege declarations originating from integration packages were not validated before being used to mint credentials for enrolled Elastic Agents. A user holding Fleet management privileges could therefore cause every Elastic Agent on a targeted policy to receive a credential carrying arbitrarily elevated Elasticsearch cluster privileges, up to and including full cluster administration.

Incorrect Authorization (CWE-863) in Elastic Cloud on Kubernetes (ECK) can lead to unauthorized modification of data via Metadata Spoofing (CAPEC-690). An actor holding limited Kubernetes permissions confined to a single namespace could cause attacker-controlled certificate material to be included in the Elasticsearch client trust bundle managed by ECK in a separate namespace.

Incorrect Permission Assignment for Critical Resource (CWE-732) in Elastic Agent can lead to local privilege escalation via Replace Binaries (CAPEC-642). On Windows systems where Elastic Agent is installed in unprivileged mode, resources used by the agent service are created with access controls broader than required. A local user could take advantage of this to cause the service to execute code of their choosing, ultimately obtaining SYSTEM-level privileges on the host.

Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal') (CWE-22) in Elastic Maps Server can lead to information disclosure via Path Traversal (CAPEC-126). An unauthenticated attacker able to reach the service over the network could cause it to return the contents of files outside its intended content directory that are readable by the server process.

Missing Authorization (CWE-862) in Kibana can lead to information disclosure via Privilege Abuse (CAPEC-122). An authorization control was not applied to a Kibana Entity Store configuration operation, allowing an authenticated user with elevated Kibana privileges to indirectly cause a background task to read from Elasticsearch indices that user is not authorized to access. Derived entity data from those indices is then exposed through the entity store output.

Incomplete Cleanup (CWE-459) in Elastic Cloud on Kubernetes (ECK) can lead to unauthorized access via Privilege Abuse (CAPEC-122). Authentication credentials persist after a cross-namespace association has been denied by RBAC enforcement, allowing a low-privileged tenant to retain unauthorized read access to the associated Elasticsearch cluster.

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.

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.

Improper Handling of Highly Compressed Data (CWE-409) in APM Server can lead to a persistent denial of service via Excessive Allocation (CAPEC-130). An authenticated user with write access to source map content could store specially crafted, highly compressed content that exhausts the memory available to APM Server when it is later processed, terminating the process. The condition recurs on every restart until the stored content is removed.

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 resources via Path Traversal (CAPEC-126). A low-privileged user could cause a subsequent action taken by a higher-privileged user in the Fleet administration interface to act on an unintended target, resulting in the deletion of resources including accounts with elevated privileges.

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.

Allocation of Resources Without Limits or Throttling (CWE-770) in Filebeat can lead to a denial of service via Excessive Allocation (CAPEC-130). An attacker able to reach the Filebeat HTTP ingestion endpoint could send specially crafted compressed requests that exhaust the memory resources of the Filebeat process.

Incorrect Authorization (CWE-863) in Fleet Server can lead to a denial of service of agent upload operations via Privilege Abuse (CAPEC-122). Fleet Server does not correctly verify session ownership during multi-part data upload operations, allowing any authenticated agent to interfere with the active upload sessions belonging to other enrolled agents.

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.

Observable Response Discrepancy (CWE-204) in the Kibana Osquery feature can lead to information disclosure via Query System for Information (CAPEC-54). An authenticated user holding Osquery live-query privileges could determine whether a scheduled query identifier exists in a Kibana space they are not authorized to access.

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 Elasticsearch custom inference service can lead to information disclosure via Privilege Abuse (CAPEC-122). A user holding only inference execution privileges could cause outbound inference traffic to be directed to a destination of their choosing and could cause administrator-provisioned credentials to be exposed.

Incorrect Authorization (CWE-863) in Kibana can lead to unauthorized disclosure, modification, and deletion of data via Accessing Functionality Not Properly Constrained by ACLs (CAPEC-1). Where two authenticated principals originating from different authentication realms share the same username value, one could read, modify, and delete the other's private Elastic AI Assistant Knowledge Base entries.

Inconsistent Interpretation of HTTP Requests ('HTTP Request Smuggling') (CWE-444) in Elasticsearch can lead to information disclosure via HTTP Request Smuggling (CAPEC-33). Under specific proxy deployment configurations, a network attacker could obtain confidential responses intended for other authenticated users.

Missing Authorization (CWE-862) in Kibana can lead to information disclosure via Exploiting Incorrectly Configured Access Control Security Levels (CAPEC-180). An authenticated user holding minimal Elasticsearch privileges could bypass Kibana feature authorization and space access controls, resulting in the unauthorized disclosure of Fleet deployment metadata from the default Kibana space.

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.

Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal') (CWE-22) in Kibana can lead to the unauthorized deletion of privileged resources via Path Traversal (CAPEC-126). A low-privileged user holding tag creation privileges could cause a subsequent administrative action in the tag management interface to act on an unintended target, resulting in the deletion of privileged resources including administrative accounts and other organizational assets. Exploitation requires an administrator to interact with the affected 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 holding only low, read-level Agent Builder privileges could submit a specially crafted request that causes Kibana to consume an unbounded amount of memory, terminating the process and denying service to all users of the instance.

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.

Deserialization of Untrusted Data (CWE-502) in the Elasticsearch machine learning component can lead to remote code execution via Object Injection (CAPEC-586). A specially crafted trained model artifact could cause attacker-controlled logic to execute with a materially broader system-call surface than intended. Exploitation requires an authenticated user with sufficient privileges to create and deploy trained models.

Uncaught Exception (CWE-248) in Kibana can lead to a denial of service via Input Data Manipulation (CAPEC-153). An authenticated user holding only the low-privileged feature access required to use the Observability AI Assistant can submit a specially crafted request that produces an unhandled error condition, terminating the Kibana process and denying service to all users and spaces on that instance until it is restarted.

Incorrect Authorization (CWE-863) in Kibana can lead to unauthorized modification of data via Accessing Functionality Not Properly Constrained by ACLs (CAPEC-1). An authenticated user holding only Security Solution read access in a Kibana space could enumerate and change the state of Entity Store maintainer tasks, silently disabling Entity Analytics maintenance for that space.

Incorrect Authorization (CWE-863) in Kibana Entity Analytics can lead to a loss of security monitoring via Accessing Functionality Not Properly Constrained by ACLs (CAPEC-1). An authenticated user holding only read-level Security feature access, and no Elasticsearch privileges, could stop the recurring Privilege Monitoring engine task for a Kibana space. Privileged user monitoring then stops producing data for that space while the engine continues to report a healthy state to operators.

Improper Handling of Highly Compressed Data (CWE-409) in Kibana can lead to a denial of service via Excessive Allocation (CAPEC-130). An authenticated user holding Streams management privileges could supply specially crafted content that expands to a far larger volume of data during processing, exhausting the memory available to Kibana. The Kibana process is terminated by the host and remains unavailable to all users until the service is restarted.

Improper Neutralization of Special Elements in Data Query Logic (CWE-943) in Kibana can lead to information disclosure via NoSQL Injection (CAPEC-676). An authenticated user with access to the affected query functionality could submit specially crafted input that alters the intended query logic, returning data the user is not authorized to read.

Incorrect Authorization (CWE-863) in Kibana can lead to privilege escalation via Exploiting Incorrectly Configured Access Control Security Levels (CAPEC-180). A user holding workflow edit permissions could cause scheduled workflow executions to run with the privileges of a different, higher-privileged user, allowing access to and modification of data beyond their own authorization scope.

Allocation of Resources Without Limits or Throttling (CWE-770) in Elasticsearch can lead to a denial of service via Excessive Allocation (CAPEC-130). A user with elevated privileges can submit a specially crafted request that causes excessive memory consumption, which may render the affected node 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.

A local vulnerability in the Winlogbeat Windows installer caused runtime files to be placed in a directory writable by unprivileged users. A low-privileged attacker with existing access to the system could pre-position malicious filesystem links, causing a subsequent elevated Winlogbeat operation to write to or delete arbitrary files. Successful exploitation could result in a denial of service.

Authorization Bypass Through User-Controlled Key (CWE-639) in Kibana can lead to unauthorized data modification via Accessing Functionality Not Properly Constrained by ACLs (CAPEC-1). Under certain conditions, an authenticated user could reference another user's AI Assistant conversation identifier to access or modify a conversation they do not own. Successful exploitation requires knowledge of a hard-to-guess identifier.

A flaw in Elasticsearch allows a low-privileged authenticated user to submit a single small request containing a forged opaque identifier. Elasticsearch decodes and deserializes the identifier before confirming that it was legitimately issued by the cluster, and a size value carried inside the identifier drives an allocation that is neither capped nor accounted for by the available memory-usage controls. The resulting out-of-memory condition is fatal and terminates the affected node process, resulting in a denial of service.

A flaw in Elasticsearch allows a low-privileged authenticated user to submit a single request containing a crafted user-supplied input. A specific internal component validates the input using a recursive routine and applies no bound to the length of the value being validated, so the validation causes the thread to exhaust its stack. The resulting fatal error is not handled by the surrounding execution paths and terminates the affected node process, producing a denial of service.

A flaw in Elasticsearch allows a low-privileged authenticated user who can index documents to submit a single small document containing a crafted user-supplied input. Processing one such document occupies a worker thread from a bounded pool for a disproportionate amount of time, degrading the availability of indexing operations on the affected node.

A flaw in Elasticsearch allows an authenticated user holding only read privileges to submit a small search request containing a crafted user-supplied input. Processing that input causes a specific internal component to allocate memory without any upper bound, and the allocation occurs outside the scope of the existing memory accounting controls that were intended to constrain it. The resulting out-of-memory condition is fatal and terminates the affected node process, causing a denial of service.

A flaw in Elasticsearch allows an authenticated user with the privileges required to invoke the simulate pipeline API endpoint (https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-ingest-simulate) to submit a request that causes a self-referential data structure to be created. When a specific internal component later processes that structure, the operation recurses without bound and raises a fatal error that is not handled by the surrounding execution path, terminating the affected node process and resulting in a denial of service.

Kibana Agent Builder does not correctly verify that the requesting user holds the privileges required by a separate Kibana feature before it creates and runs a tool that invokes that feature's functionality. This allows privilege escalation and could lead to disclosure of sensitive information that the user is not authorized to read.

Kibana Agent Builder A2A JSON-RPC API endpoint derives the identifier of a stored conversation from a user-supplied input, and the ownership check on that identifier does not distinguish between a conversation that does not exist and one that exists but belongs to another user. As a result, an authenticated user holding only the Agent Builder read privilege can supply an identifier already in use by another user in the same space and cause that user's conversation to be replaced and reassigned to the requesting account. The original owner permanently loses access to the conversation and its history. The impact is limited to loss of integrity and availability of the affected conversation; the attacker does not read the overwritten content.

Elasticsearch does not apply its configurable input length restriction to a user-supplied pattern accepted by an intervals query. Compiling a deeply nested pattern drives unbounded recursion that exhausts the thread stack and raises a fatal error, terminating the Elasticsearch node process and causing a denial of service for that node. An authenticated user holding only read-only privileges on a single searchable index can trigger the condition with one small search request.

Elasticsearch does not validate a size value taken from a user-supplied input before that value is used to reserve memory for an internal data structure. An authenticated user holding only read privileges can submit a single small crafted request to a product API endpoint that causes the node to attempt an excessively large allocation. The resulting memory exhaustion raises a fatal error that terminates the Elasticsearch node process, causing a denial of service for the affected node and degrading cluster health. The defect is not volumetric, so a single request is sufficient regardless of the heap size configured on the target node.

Relative Path Traversal (CWE-23) in Kibana can lead to the unauthorized deletion of Kibana resources via Relative Path Traversal (CAPEC-139). Kibana Fleet accepted a user-supplied identifier for a Fleet Server host configuration without rejecting relative traversal sequences. The identifier is stored as provided and is later incorporated into the request that Kibana issues when that configuration is removed.

Improper Control of Generation of Code ('Code Injection') (CWE-94) in Fleet Server can lead to the execution of attacker-supplied script content via Code Injection (CAPEC-242). Kibana accepted an identifier for an output configuration without restricting it to safe characters. That identifier is later placed into a server-side script that Fleet Server builds as part of routine agent policy processing, so script syntax embedded in the identifier became part of the script that was executed rather than being treated as data.

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.

Allocation of Resources Without Limits or Throttling (CWE-770) in Kibana can lead to a denial of service via Excessive Allocation (CAPEC-130). A user-supplied list of document fields accepted by the Kibana Playground for RAG feature was neither bounded in length nor de-duplicated before it was used to assemble the response for each matching document. A single crafted request could therefore make Kibana build a response far larger than the data it was derived from, and the resulting processing and memory pressure exhausts the resources of the Kibana instance.

Incorrect Authorization (CWE-863) in Kibana can lead to unauthorized deletion of Synthetics private locations via Accessing Functionality Not Properly Constrained by ACLs (CAPEC-1). Synthetics private locations can be shared with more than one space, and deleting one removes it from every space it is shared with. The safeguard that prevented the deletion of a private location still in use evaluated only the monitors visible in the requesting user's own space, so monitors that depend on the private location in other spaces were not taken into account. As a result, an authenticated Kibana user holding the Synthetics write privilege in a single space could delete a private location that other spaces still depend on, even where the user has no access to those spaces. Deleting the private location removes the shared configuration and stops the monitors in the other spaces from running, which suppresses the availability monitoring those spaces rely on.

The Elastic Security capability that suggests existing field values while a user authors endpoint policy artifacts queries Elastic Defend event data with Kibana's internal Elasticsearch account instead of the account of the requesting user. Only Kibana feature privileges are verified, and the caller's Elasticsearch index privileges are not. An authenticated user who holds Elastic Security feature privileges but no read access to the Elastic Defend event indices can therefore retrieve field values from that data, including process command line arguments, which commonly contain tokens, credentials, connection strings, and other sensitive operational detail from protected hosts.

A Kibana Machine Learning capability that removes a saved object from the current space accepts machine learning trained models as a target, but it verifies only the privileges that apply to anomaly detection jobs and data frame analytics jobs. A user whose role grants create anomaly detection jobs and data frame analytics jobs without the trained model privilege can therefore remove a trained model from a space. The model itself is not deleted and remains available in its other spaces, and the change can be reversed by a suitably privileged user.

A lower privileged user who holds only the privilege to read agent policies can read the entire configuration of a configured Fleet proxy. This would normally require the Fleet privilege to read settings.The proxy configuration possibly contains proxy authentication credentials and private key material that they should not be authorized to view.

The state that Kibana stores for an Observability Onboarding flow is not bound to the user who created the flow, and the routes that read and update that state do not verify ownership. An authenticated user who holds only generic read access to the space can therefore discover the onboarding flows of other users, read their onboarding state, and write arbitrary progress data into them. A tampered flow can also cause the owner's onboarding view to fail with a server error.

Allocation of Resources Without Limits or Throttling (CWE-770) in Kibana can lead to a denial of service via Excessive Allocation (CAPEC-130). A specially crafted request submitted by an authenticated user with minimal privileges to a validation capability of the Observability log analysis feature causes Kibana to perform an unbounded amount of concurrent work. This can exhaust the memory available to the Kibana process and make Kibana unavailable to all users until it is restarted. The severity of the outcome depends on the resources allocated to the deployment; on well-provisioned deployments a single request may cause degraded performance and elevated memory pressure rather than a full outage, but the request is inexpensive to repeat.

Authorization Bypass Through User-Controlled Key (CWE-639) in Kibana can lead to unauthorized query execution against Elastic Agents that are assigned to a Kibana space the requesting user has no access to, via Accessing Functionality Not Properly Constrained by ACLs (CAPEC-1). A user who is authorized to run Osquery live queries in one space can have a query carried out on hosts belonging to another space, resulting in disclosure of information from those hosts to the Osquery results data stream.

Missing Authorization (CWE-862) in Kibana can lead to unauthorized execution of Osquery and Elastic Defend response actions on managed hosts via Accessing Functionality Not Properly Constrained by ACLs (CAPEC-1). A Kibana user who is able to author and evaluate Elastic Security detection rules can cause response actions to be carried out against enrolled agents without holding the Osquery live query privileges or the Elastic Defend response action privileges that normally govern those capabilities. Depending on the response action involved, this can result in disclosure of information from the affected hosts or in unauthorized changes to their state.

Missing Authorization (CWE-862) in Kibana can lead to unauthorized execution of Elastic Defend response actions on managed hosts via Accessing Functionality Not Properly Constrained by ACLs (CAPEC-1). A Kibana user who holds only detection rule authoring privileges for the Elastic Security solution can associate automated endpoint response actions with a detection rule, even though the dedicated Endpoint response action privileges that govern those capabilities (host isolation, process operations, and execute operations) have not been granted to that user. When such a rule generates alerts, the associated response actions are carried out against the matching hosts.

Inefficient Algorithmic Complexity (CWE-407) in Kibana can lead to denial of service via Input Data Manipulation (CAPEC-153). A specially crafted, deeply nested expression submitted to a Kibana TSVB visualization is evaluated with a worst-case cost that grows disproportionately with the size of the input. Because the evaluation runs synchronously, a single request consumes the Kibana request-processing thread indefinitely, and Kibana stops responding to all further requests until the service is restarted.

Missing Authorization (CWE-862) in Kibana can lead to information disclosure via Accessing Functionality Not Properly Constrained by ACLs (CAPEC-1). An internal Kibana data retrieval capability used by Elastic Defend endpoint response actions did not enforce the Security Solution and endpoint privileges that its user-facing equivalents require, and it retrieved data with elevated internal permissions rather than the permissions of the requesting user. As a result, an authenticated low-privileged Kibana user with no Security Solution privileges, endpoint privileges and no Elasticsearch privileges on the underlying data, could read endpoint response action records and the corresponding response content returned by managed hosts.

Uncaught Exception (CWE-248), resulting from Improper Input Validation (CWE-20), in Kibana can lead to denial of service via Input Data Manipulation (CAPEC-153). An authenticated user holding only low-privileged access can cause an internal error condition in Kibana by supplying specially crafted data. The resulting error is raised on an execution path so it propagates as an uncaught exception and terminates the Kibana process. Kibana is unavailable to all users until the service is restarted, and the condition can be triggered repeatedly.

Allocation of Resources Without Limits or Throttling (CWE-770) in Kibana can lead to denial of service via Excessive Allocation (CAPEC-130). A specially crafted, malformed payload submitted to a Kibana visualization feature by an authenticated user holding only low-privileged access is not correctly validated before use. Processing the request causes unbounded memory growth in the Kibana process, which is terminated by the host once available memory is exhausted. Kibana then becomes unavailable to all users until the service is restarted.

Cross-Site Request Forgery (CWE-352) in Kibana can lead to privilege escalation via Cross Site Request Forgery (CAPEC-62). A user who is permitted to create visualizations can save a specially crafted Vega visualization that, when it is opened by another user, causes authenticated requests to be issued to Kibana in the context of the viewing user's session.

Authorization Bypass Through User-Controlled Key (CWE-639) in Fleet Server can lead to information disclosure via Manipulating User-Controlled Variables (CAPEC-77). The authorization decision for artifact downloads relied on a client-supplied value that was persisted without being validated against the server-side record of the requesting agent's assignment. An authenticated party in possession of a valid enrolled agent credential could therefore retrieve a policy the agent is not assigned to.

Memory Allocation with Excessive Size Value (CWE-789) in the ES|QL query processing of Elasticsearch can lead to denial of service via Excessive Allocation (CAPEC-130). An authenticated user able to submit ES|QL queries could send a specially crafted query whose evaluation allocates an unbounded amount of heap memory, exhausting the available heap on the receiving node and causing the node to become unavailable.

Improperly Controlled Modification of Dynamically-Determined Object Attributes (CWE-915) in the case management functionality of Elastic Security in Kibana can lead to unauthorized modification of case data by an authenticated user who has not been granted case editing privileges, via Manipulating User-Controlled Variables (CAPEC-77). Object attributes accepted by the case management API were not subject to the same authorization enforcement applied in the user interface, so a low-privileged user could alter case records they were only entitled to view.

Allocation of Resources Without Limits or Throttling (CWE-770) in Kibana can lead to denial of service via Excessive Allocation (CAPEC-130). An authenticated user who is authorized to manage maintenance windows could submit a specially crafted, malformed payload that causes the Kibana process to consume excessive resources. Kibana becomes unresponsive for all users and does not recover without manual intervention.

Allocation of Resources Without Limits or Throttling (CWE-770) in Kibana can lead to denial of service via Excessive Allocation (CAPEC-130). An authenticated user with read-only privileges to the alerting feature could submit a specially crafted, malformed payload that causes the Kibana process to consume excessive resources. A single request is sufficient to leave Kibana unable to serve requests for all users until the process is restarted.

Authorization Bypass Through User-Controlled Key (CWE-639) in Kibana can lead to information disclosure via Accessing Functionality Not Properly Constrained by ACLs (CAPEC-1). An authenticated user who is authorized to read alerting rules in a single Kibana space could retrieve alerting rule execution telemetry that belongs to spaces the user is not authorized to access. The disclosed telemetry includes rule identifiers, rule names, space identifiers, execution outcomes, timestamps, and execution counters.

Cleartext Storage of Sensitive Information in an Environment Variable (CWE-526) in Elastic Cloud on Kubernetes (ECK) can lead to information disclosure via Retrieve Embedded Sensitive Data (CAPEC-37). When ECK reconciles a Fleet Server resource that authenticates to Elasticsearch with a service account token, the token is written into the generated workload specification in cleartext rather than being referenced from the Kubernetes Secret that ECK maintains for the other credentials on the same path. Any principal able to read workload specifications in the affected namespace can therefore read a live Elasticsearch credential, even when Kubernetes RBAC does not grant that principal access to Secrets.

Uncontrolled Recursion (CWE-674) in Elasticsearch can lead to denial of service via Serialized Data with Nested Payloads (CAPEC-230). An authenticated user holding only read privileges on a single index can submit one specially crafted search request whose deeply nested structure is processed without a depth limit, exhausting the thread stack and terminating the affected node.

Memory Allocation with Excessive Size Value (CWE-789) in Elasticsearch can lead to denial of service via Excessive Allocation (CAPEC-130). An authenticated user holding only read privileges on a single index can submit one small, specially crafted search request that causes an excessively large memory allocation, exhausting the JVM heap and terminating the affected node.

Kibana Agent Builder determines whether a caller owns a private agent by comparing a stable user identifier when one is recorded, and falling back to a comparison of the username when it is not. A username is not unique across Elasticsearch authentication realms, so two distinct principals that share a username in different realms are treated as the same owner. This discloses the configuration and instructions of an agent the caller does not own, and allows that agent to be altered or removed.

The native inference process that Elasticsearch uses to evaluate uploaded machine learning models accepts a model operation that computes a memory address from an offset supplied inside the model, without validating that the offset stays within the bounds of the underlying storage. A user with the privileges required to upload and deploy a trained model can craft a model that reads and writes memory outside the intended allocation. The result is heap corruption that crashes the inference process, and, with sufficient control over the heap layout, could allow arbitrary code execution in the context of that process.

The Elastic Cloud on Kubernetes (ECK) operator reads a list of secret references from an annotation on secrets it manages, and it accepts the namespace recorded in each reference without validating that the reference is authorized for the resource being reconciled. A user whose Kubernetes permissions are limited to their own namespace can write that annotation, trigger a reconcile, and cause the operator to use its cluster-wide secret permissions to copy the contents of a secret from any other namespace into a secret the user can read.

Elasticsearch does not enforce an upper bound on a user-supplied count accepted by a search highlighting option, and the allocation derived from that count is not accounted against any circuit breaker. An authenticated user holding only read privileges on a single searchable index can submit one small search request that causes the node to reserve an excessively large internal data structure. The allocation occurs before the existing highlighting safety limits are evaluated, so memory exhaustion raises a fatal error that terminates the Elasticsearch node process. This results in a denial of service for the affected node and degrades cluster routing and health. The defect is not volumetric and does not depend on the size of the indexed data, so a single request is sufficient.

Uncontrolled Recursion (CWE-674) in Elasticsearch can lead to denial of service via Input Data Manipulation (CAPEC-153). An authenticated user holding only low-privileged index creation permissions can submit a single request containing a specially crafted, malformed custom analysis definition that is resolved recursively without a cycle or depth check, exhausting the thread stack and terminating the affected node.

Uncontrolled Recursion (CWE-674) in the Elasticsearch wildcard matching helper can lead to a denial of service via Excessive Allocation (CAPEC-130). The matcher used to resolve wildcard patterns against names is implemented recursively and had no bound on recursion depth or on the total number of match operations performed. A search request containing a wildcard pattern with a large number of wildcard groups, evaluated against a sufficiently long name, exhausts the thread stack. Elasticsearch treats a stack overflow as an unrecoverable condition and shuts the node down, so the request terminates the affected node rather than failing gracefully.

Observable Discrepancy (CWE-203) in Kibana Fleet can lead to information disclosure via Excavation (CAPEC-116). Fleet removes the Elasticsearch API key value of an enrolled Elastic Agent from the responses of its agent listing capability, but that capability accepted caller-supplied filter expressions over the stored field that holds the value, and evaluated them with Kibana's own internal Elasticsearch privileges rather than the caller's. Because the number of matching agents is reported back to the caller, the difference between a matching and a non-matching filter formed a side channel from which the full API key value could be reconstructed one character at a time with a short sequence of requests.

Improper Privilege Management (CWE-269) in Kibana Fleet can lead to privilege escalation via Privilege Escalation (CAPEC-233). An integration policy may optionally declare extra data streams that the integration writes to, which Fleet adds to the Elasticsearch API key issued to Elastic Agents enrolled in the corresponding agent policy. The resulting key allows new documents to be inserted and index mappings to be extended for specific indices. The key does not allow reading, updating, or deleting existing documents

Incorrect Authorization (CWE-863) in Kibana Fleet can lead to privilege escalation via Privilege Abuse (CAPEC-122). Fleet restricts some callers to managing integration policies for one specific integration. When an existing integration policy was updated, that restriction was evaluated against the integration recorded on the stored policy rather than against the replacement integration supplied with the update. An authenticated user holding only the Elastic Defend endpoint policy management privilege was therefore able to convert an endpoint policy they administer into a policy for a different integration, and to supply that integration's configuration at the same time.

Authorization Bypass Through User-Controlled Key (CWE-639) in Kibana can lead to unauthorized cross-space access via Accessing Functionality Not Properly Constrained by ACLs (CAPEC-1). The result is disclosure of inference output from a trained model in a different space that the user is not authorized to list, read, or use, which exposes the behavior of a model. The same pattern also reached the deployment stop and deployment update operations, allowing an active trained model deployment in another space to be stopped or to have its allocated resources altered.

Uncaught Exception (CWE-248) in Kibana Cases can lead to denial of service via Input Data Manipulation (CAPEC-153). Malformed link syntax stored in a case comment was not rejected or sanitized when the comment was later formatted for display, and the resulting unhandled error prevented the affected case from being displayed. An authenticated user holding privileges to comment on a case could store such a comment, after which that case became inaccessible to every user who opened it until the stored comment was removed.

Allocation of Resources Without Limits or Throttling (CWE-770) in Kibana can lead to denial of service via Excessive Allocation (CAPEC-130). A query expression accepted by a connector reporting operation was processed without any limit on its size, and an oversized expression caused the Kibana process to spend an unbounded amount of time evaluating it. An authenticated user with read-only privileges was able to send a single request that left Kibana unable to serve any user until the process was restarted.

Uncontrolled Resource Consumption (CWE-400) in Elasticsearch can lead to denial of service via Exponential Data Expansion (CAPEC-197). An authenticated user may submit a specially crafted query to the ES|QL engine that causes exponential CPU consumption during query evaluation. Because the resource exhaustion persists beyond query completion, repeated requests can fully exhaust the available query worker resources, rendering ES|QL queries unavailable until the node is restarted.

Missing Authorization (CWE-862) in Kibana can lead to unauthorized cross-space information disclosure via user-supplied input that circumvents space-level access control.

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.

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.

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 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.

Reachable Assertion (CWE-617) in Elasticsearch can lead to denial of service via Input Data Manipulation (CAPEC-153). A specially crafted search request containing a null value in a specific query clause causes an internal assertion to be raised during query parsing. Because Elasticsearch treats assertion failures as fatal errors, this terminates the affected node process. A low-privileged authenticated user with read access to at least one index can exploit this condition with a single request to cause a node to terminate, disrupting search availability. In a single-node deployment this fully stops Elasticsearch; in a multi-node cluster it reduces cluster capacity for each affected node.

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.

Uncontrolled Resource Consumption (CWE-400) in Elasticsearch can lead to denial of service via Excessive Allocation (CAPEC-130). A user with search privileges can submit a specially crafted search request that causes a data node to exhaust available heap memory, resulting in node unavailability and cluster degradation. An attacker could leverage this vulnerability to cause cluster downtime requiring manual intervention to restore service.

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.

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.

Uncontrolled Resource Consumption (CWE-400) in Elasticsearch can lead to denial of service via Excessive Allocation (CAPEC-130). A low-privileged authenticated user with permission to execute EQL sequence queries against an index they control can send a specially crafted query that triggers excessive memory consumption, causing the Elasticsearch node to crash.

Incorrect Authorization (CWE-863) in Elasticsearch can allow an authenticated user with limited index privileges to exploit insufficient authorization controls in the ingest simulation feature. By targeting indices they are not authorized to access directly, the user can cause those indices' configured ingest pipelines to execute and return their output, potentially disclosing data processed or enriched by those pipelines. Additionally, the same feature can be used to retrieve index mapping metadata for indices the user are not authorized to access directly.

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.

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 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.

Uncontrolled Resource Consumption (CWE-400) in Elasticsearch can lead to a denial of service via Excessive Allocation (CAPEC-130). An authenticated user can submit a specially crafted bulk request that causes sustained high CPU consumption, which can render the affected node unable to process requests.

Incorrect Authorization (CWE-863) in Kibana can lead to unauthorized information disclosure via Accessing Functionality Not Properly Constrained by ACLs (CAPEC-1). Under certain conditions, a low-privileged authenticated user can access response action data that they are not authorized to view.

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 Fleet Server can lead to a denial of service via Excessive Allocation (CAPEC-130). An attacker can submit a specially crafted request to an upload endpoint that causes excessive memory consumption, which may render Fleet Server unavailable.

Allocation of Resources Without Limits or Throttling (CWE-770) in Elasticsearch can lead to a denial of service via Excessive Allocation (CAPEC-130). A user with elevated privileges can submit a specially crafted machine learning request that causes excessive memory consumption, which may render the affected node unavailable.

Uncontrolled Recursion (CWE-674) in Elasticsearch can lead to a denial of service via Excessive Allocation (CAPEC-130). An authenticated user can submit a specially crafted query that causes excessive resource consumption while the request is processed, which may render the affected node 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.

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.

Improper Input Validation (CWE-20) in the Kibana Fleet agent policy management feature can lead to privilege escalation. An authenticated user with Fleet management privileges can manipulate agent policy configuration by injecting values into a configuration override mechanism that is not adequately validated. An attacker can cause Elastic Agents to be issued API keys with elevated Elasticsearch privileges, potentially granting unauthorized read and write access to sensitive Elasticsearch security indices beyond what is intended for the Fleet management role.

Uncontrolled Resource Consumption (CWE-400) in Kibana can lead to denial of service via Excessive Allocation (CAPEC-130). An authenticated user with viewer-level access can submit a request containing an oversized input value to an analytics collections management endpoint. Kibana will consume excessive CPU and memory resources while processing the request. This results in Kibana becoming unavailable to all users until the service is manually recovered.

Server-Side Request Forgery (CWE-918) in Kibana can allow an authenticated user with connector management privileges to bypass the operator-configured connector allowlist, causing the Kibana server to issue outbound requests to destinations the egress 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 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.

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.

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.

Improper Neutralization of Input During Web Page Generation (CWE-79) in Kibana can lead to stored HTML injection. A user with write access to an Elasticsearch index could persist crafted markup which, when subsequently rendered through an affected Kibana view by another user, was not sufficiently sanitized. Successful exploitation could result in unauthorized UI manipulation and outbound network requests issued from the viewing user's browser session.

Uncontrolled Resource Consumption (CWE-400) in Kibana can lead to a denial of service via Excessive Allocation (CAPEC-130). An authenticated user holding a low-privileged role can submit a specially crafted, oversized payload to an internal Kibana API, causing the Kibana process to exhaust available resources and become unresponsive to all users until the service recovers or is restarted.

Operation on a Resource after Expiration or Termination (CWE-672) in Kibana can lead to unauthorized information disclosure. A logic error in how expiration timestamps were validated allowed a time-bounded access token to remain usable beyond its intended validity window, enabling an unauthenticated actor in possession of the token to retrieve the associated content after expiration.

A path traversal vulnerability was identified in Kibana's dashboard management functionality. An authenticated user with limited permissions could create a dashboard with a specially crafted identifier. When an administrator subsequently attempts to delete this dashboard through the Kibana interface, the deletion request is redirected to an unintended internal endpoint, potentially resulting in the unauthorized deletion of user accounts or other resources. Exploitation requires an administrator to perform a delete action on the maliciously crafted dashboard object.

Improper Verification of Cryptographic Signature (CWE-347) in Elastic Package Registry could allow an attacker positioned to intercept network traffic, or to otherwise influence the contents served to a self-hosted registry, to substitute a tampered package without the integrity check failing closed.

Improper Limitation of a Pathname to a Restricted Directory (CWE-22) in Logstash can lead to arbitrary file write and potentially remote code execution via Relative Path Traversal (CAPEC-139). The archive extraction utilities used by Logstash do not properly validate file paths within compressed archives. An attacker who can serve a specially crafted archive to Logstash through a compromised or attacker-controlled update endpoint can write arbitrary files to the host filesystem with the privileges of the Logstash process. In certain configurations where automatic pipeline reloading is enabled, this can be escalated to remote code execution.

Uncontrolled Resource Consumption (CWE-400) in Kibana can lead to denial of service via Excessive Allocation (CAPEC-130). An authenticated user with access to the automatic import feature can submit specially crafted requests with excessively large input values. When multiple such requests are sent concurrently, the backend services become unstable, resulting in service disruption and deployment unavailability for all users.

Server-Side Request Forgery (CWE-918) in Kibana One Workflow can lead to information disclosure. An authenticated user with workflow creation and execution privileges can bypass host allowlist restrictions in the Workflows Execution Engine, potentially exposing sensitive internal endpoints and data.

Execution with Unnecessary Privileges (CWE-250) in Kibana’s Fleet plugin debug route handlers can lead reading index data beyond their direct Elasticsearch RBAC scope via Privilege Abuse (CAPEC-122). This requires an authenticated Kibana user with Fleet sub-feature privileges (such as agents, agent policies, and settings management).

Incorrect Authorization (CWE-863) in Kibana can lead to information disclosure via Privilege Abuse (CAPEC-122). A user with limited Fleet privileges can exploit an internal API endpoint to retrieve sensitive configuration data, including private keys and authentication tokens, that should only be accessible to users with higher-level settings privileges. The endpoint composes its response by fetching full configuration objects and returning them directly, bypassing the authorization checks enforced by the dedicated settings APIs.

Incorrect Authorization (CWE-863) in Kibana can lead to cross-space information disclosure via Privilege Abuse (CAPEC-122). A user with Fleet agent management privileges in one Kibana space can retrieve Fleet Server policy details from other spaces through an internal enrollment endpoint. The endpoint bypasses space-scoped access controls by using an unscoped internal client, returning operational identifiers, policy names, management state, and infrastructure linkage details from spaces the user is not authorized to access.

Improper Validation of Specified Quantity in Input (CWE-1284) in the Timelion visualization plugin in Kibana can lead Denial of Service via Excessive Allocation (CAPEC-130). The vulnerability allows an authenticated user to send a specially crafted Timelion expression that overwrites internal series data properties with an excessively large quantity value.

Missing Authorization (CWE-862) in Kibana’s server-side Detection Rule Management can lead to Unauthorized Endpoint Response Action Configuration (host isolation, process termination, and process suspension) via CAPEC-1 (Accessing Functionality Not Properly Constrained by ACLs). This requires an authenticated attacker with rule management privileges.

Improper Neutralization of Special Elements Used in a Template Engine (CWE-1336) exists in Workflows in Kibana which could allow an attacker to read arbitrary files from the Kibana server filesystem, and perform Server-Side Request Forgery (SSRF) via Code Injection (CAPEC-242). This requires an authenticated user who has the workflowsManagement:executeWorkflow privilege.

Uncontrolled Resource Consumption (CWE-400) in the Timelion component in Kibana can lead Denial of Service via Input Data Manipulation (CAPEC-153)

Inefficient Regular Expression Complexity (CWE-1333) in the AI Inference Anonymization Engine in Kibana can lead Denial of Service via Regular Expression Exponential Blowup (CAPEC-492).

Improper Input Validation (CWE-20) in the internal Content Connectors search endpoint in Kibana can lead Denial of Service via Input Data Manipulation (CAPEC-153)

Improper Validation of Specified Quantity in Input (CWE-1284) in Kibana can allow an authenticated attacker with view-only privileges to cause a Denial of Service via Input Data Manipulation (CAPEC-153). An attacker can send a specially crafted, malformed payload causing excessive resource consumption and resulting in Kibana becoming unresponsive or crashing.

Improper Input Validation (CWE-20) in Kibana's Email Connector can allow an attacker to cause an Excessive Allocation (CAPEC-130) through a specially crafted email address parameter. This requires an attacker to have authenticated access with view-level privileges sufficient to execute connector actions. The application attempts to process specially crafted email format, resulting in complete service unavailability for all users until manual restart is performed.

Allocation of Resources Without Limits or Throttling (CWE-770) in Kibana Fleet can lead to Excessive Allocation (CAPEC-130) via a specially crafted bulk retrieval request. This requires an attacker to have low-level privileges equivalent to the viewer role, which grants read access to agent policies. The crafted request can cause the application to perform redundant database retrieval operations that immediately consume memory until the server crashes and becomes unavailable to all users.

Allocation of Resources Without Limits or Throttling (CWE-770) in Kibana Fleet can lead to Excessive Allocation (CAPEC-130) via a specially crafted request. This causes the application to perform redundant processing operations that continuously consume system resources until service degradation or complete unavailability occurs.

Improper Validation of Array Index (CWE-129) exists in Metricbeat can allow an attacker to cause a Denial of Service through Input Data Manipulation (CAPEC-153) via specially crafted, malformed payloads sent to the Graphite server metricset or Zookeeper server metricset. Additionally, Improper Input Validation (CWE-20) exists in the Prometheus helper module that can allow an attacker to cause a Denial of Service through Input Data Manipulation (CAPEC-153) via specially crafted, malformed metric data.

Improper Authorization (CWE-285) in Kibana can lead to privilege escalation (CAPEC-233) by allowing an authenticated user to bypass intended permission restrictions via a crafted HTTP request. This allows an attacker who lacks the live queries - read permission to successfully retrieve the list of live queries.

Allocation of Resources Without Limits or Throttling (CWE-770) in Elasticsearch can allow an authenticated user with snapshot restore privileges to cause Excessive Allocation (CAPEC-130) of memory and a denial of service (DoS) via crafted HTTP request.

Allocation of Resources Without Limits or Throttling (CWE-770) in Kibana can allow a low-privileged authenticated user to cause Excessive Allocation (CAPEC-130) of computing resources and a denial of service (DoS) of the Kibana process via a crafted HTTP request.

Improper neutralization of input during web page generation ('Cross-site Scripting') (CWE-79) allows an unauthenticated user to embed a malicious script in content that will be served to web browsers causing cross-site scripting (XSS) (CAPEC-63) via a vulnerability a function handler in the Vega AST evaluator.

Improper Authorization (CWE-285) in Kibana can lead to privilege escalation (CAPEC-233) by allowing an authenticated user to change a document's sharing type to "global," even though they do not have permission to do so, making it visible to everyone in the space via a crafted a HTTP request.

Improper neutralization of input during web page generation ('Cross-site Scripting') (CWE-79) allows an authenticated user to embed a malicious script in content that will be served to web browsers causing cross-site scripting (XSS) (CAPEC-63) via a method in Vega bypassing a previous Vega XSS mitigation.

Allocation of Resources Without Limits or Throttling (CWE-770) in Elasticsearch can allow a low-privileged authenticated user to cause Excessive Allocation (CAPEC-130) causing a persistent denial of service (OOM crash) via submission of oversized user settings data.

Improper Validation of Specified Index, Position, or Offset in Input (CWE-1285) in Filebeat Syslog parser and the Libbeat Dissect processor can allow a user to trigger a Buffer Overflow (CAPEC-100) and cause a denial of service (panic/crash) of the Filebeat process via either a malformed Syslog message or a malicious tokenizer pattern in the Dissect configuration.

Improper neutralization of input during web page generation ('Cross-site Scripting') (CWE-79) allows an authenticated user to render HTML tags within a user’s browser via the integration package upload functionality. This issue is related to ESA-2025-17 (CVE-2025-25018) bypassing that fix to achieve HTML injection.

Improper Authentication in Elasticsearch PKI realm can lead to user impersonation via specially crafted client certificates. A malicious actor would need to have such a crafted client certificate signed by a legitimate, trusted Certificate Authority.

Origin Validation Error in Kibana can lead to Server-Side Request Forgery via a forged Origin HTTP header processed by the Observability AI Assistant.

Improper Authorization in Elastic Cloud Enterprise can lead to Privilege Escalation where the built-in readonly user can call APIs that should not be allowed. The list of APIs that are affected by this issue is: post:/platform/configuration/security/service-accounts delete:/platform/configuration/security/service-accounts/{user_id} patch:/platform/configuration/security/service-accounts/{user_id} post:/platform/configuration/security/service-accounts/{user_id}/keys delete:/platform/configuration/security/service-accounts/{user_id}/keys/{api_key_id} patch:/user post:/users post:/users/auth/keys delete:/users/auth/keys delete:/users/auth/keys/_all delete:/users/auth/keys/{api_key_id} delete:/users/{user_id}/auth/keys delete:/users/{user_id}/auth/keys/{api_key_id} delete:/users/{user_name} patch:/users/{user_name}

Improper neutralization of special elements used in a template engine in Elastic Cloud Enterprise (ECE) can lead to a malicious actor with Admin access exfiltrating sensitive information and issuing commands via a specially crafted string where Jinjava variables are evaluated.

Insertion of sensitive information in log file in Elasticsearch can lead to loss of confidentiality under specific preconditions when auditing requests to the reindex API https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-reindex

Improper Neutralization of Input During Web Page Generation in Kibana can lead to stored Cross-Site Scripting (XSS)

Improper Neutralization of Input During Web Page Generation in Kibana can lead to Cross-Site Scripting (XSS)

Improper Neutralization of Input During Web Page Generation in Kibana can lead to Stored XSS via case file upload.

Incorrect authorization in Kibana can lead to privilege escalation via the built-in reporting_user role which incorrectly has the ability to access all Kibana Spaces.

URL redirection to an untrusted site ('Open Redirect') in Kibana can lead to sending a user to an arbitrary site and server-side request forgery via a specially crafted URL.

Improper authorization in Kibana can lead to privilege abuse via a direct HTTP request to a Synthetic monitor endpoint.

A Prototype pollution vulnerability in Kibana leads to arbitrary code execution via crafted HTTP requests to machine learning and reporting endpoints.

Unrestricted file upload in Kibana allows an authenticated attacker to compromise software integrity by uploading a crafted malicious file due to insufficient server-side validation.

Uncontrolled Resource Consumption in Elasticsearch while evaluating specifically crafted search templates with Mustache functions can lead to Denial of Service by causing the Elasticsearch node to crash.

Inclusion of functionality from an untrusted control sphere in Elastic Agent subprocess, osqueryd, allows local attackers to execute arbitrary code via parameter injection. An attacker requires local access and the ability to modify osqueryd configurations.

Unrestricted upload of a file with dangerous type in Kibana can lead to arbitrary JavaScript execution in a victim’s browser (XSS) via crafted HTML and JavaScript files. The attacker must have access to the Synthetics app AND/OR have access to write to the synthetics indices.

Exposure of sensitive information to local unauthorized actors in Elastic Agent and Elastic Security Endpoint can lead to loss of confidentiality and impersonation of Endpoint to the Elastic Stack. This issue was identified by Elastic engineers and Elastic has no indication that it is known or has been exploited by malicious actors.

Prototype Pollution in Kibana can lead to code injection via unrestricted file upload combined with path traversal.

An issue was discovered in Elasticsearch, where a large recursion using the Well-KnownText formatted string with nested GeometryCollection objects could cause a stackoverflow.

A flaw was discovered in Elasticsearch, where a large recursion using the innerForbidCircularReferences function of the PatternBank class could cause the Elasticsearch node to crash. A successful attack requires a malicious user to have read_pipeline Elasticsearch cluster privilege assigned to them.

An issue has been identified where a specially crafted request sent to an Observability API could cause the kibana server to crash. A successful attack requires a malicious user to have read permissions for Observability assigned to them.

Prototype pollution in Kibana leads to arbitrary code execution via a crafted file upload and specifically crafted HTTP requests. In Kibana versions >= 8.15.0 and < 8.17.1, this is exploitable by users with the Viewer role. In Kibana versions 8.17.1 and 8.17.2 , this is only exploitable by users that have roles that contain all the following privileges: fleet-all, integrations-all, actions:execute-advanced-connectors

An allocation of resources without limits or throttling in Kibana can lead to a crash caused by a specially crafted payload to a number of inputs in Kibana UI. This can be carried out by users with read access to any feature in Kibana.

An allocation of resources without limits or throttling in Kibana can lead to a crash caused by a specially crafted request to /api/metrics/snapshot. This can be carried out by users with read access to the Observability Metrics or Logs features in Kibana.

A server side request forgery vulnerability was identified in Kibana where the /api/fleet/health_check API could be used to send requests to internal endpoints. Due to the nature of the underlying request, only endpoints available over https that return JSON could be accessed. This can be carried out by users with read access to Fleet.

An issue was identified in Kibana where a user without access to Fleet can view Elastic Agent policies that could contain sensitive information. The nature of the sensitive information depends on the integrations enabled for the Elastic Agent and their respective versions.

An allocation of resources without limits or throttling in Kibana can lead to a crash caused by a specially crafted request to /api/log_entries/summary. This can be carried out by users with read access to the Observability-Logs feature in Kibana.

An allocation of resources without limits or throttling in Elasticsearch can lead to an OutOfMemoryError exception resulting in a crash via a specially crafted query using an SQL function.

An issue was discovered where improper authorization controls affected certain queries that could allow a malicious actor to circumvent Document Level Security in Elasticsearch and get access to documents that their roles would normally not allow.

A deserialization issue in Kibana can lead to arbitrary code execution when Kibana attempts to parse a YAML document containing a crafted payload. A successful attack requires a malicious user to have a combination of both specific Elasticsearch indices privileges https://www.elastic.co/guide/en/elasticsearch/reference/current/defining-roles.html#roles-indices-priv  and Kibana privileges https://www.elastic.co/guide/en/fleet/current/fleet-roles-and-privileges.html  assigned to them. The following Elasticsearch indices permissions are required * write privilege on the system indices .kibana_ingest* * The allow_restricted_indices flag is set to true Any of the following Kibana privileges are additionally required * Under Fleet the All privilege is granted * Under Integration the Read or All privilege is granted * Access to the fleet-setup privilege is gained through the Fleet Server’s service account token

A deserialization issue in Kibana can lead to arbitrary code execution when Kibana attempts to parse a YAML document containing a crafted payload. This issue only affects users that use Elastic Security’s built-in AI tools https://www.elastic.co/guide/en/security/current/ai-for-security.html  and have configured an Amazon Bedrock connector https://www.elastic.co/guide/en/security/current/assistant-connect-to-bedrock.html .

A flaw allowing arbitrary code execution was discovered in Kibana. An attacker with access to ML and Alerting connector features, as well as write access to internal ML indices can trigger a prototype pollution vulnerability, ultimately leading to arbitrary code execution.

An issue was discovered whereby Elastic Agent will leak secrets from the agent policy elastic-agent.yml only when the log level is configured to debug. By default the log level is set to info, where no leak occurs.

APM server logs contain document body from a partially failed bulk index request. For example, in case of unavailable_shards_exception for a specific document, since the ES response line contains the document body, and that APM server logs the ES response line on error, the document is effectively logged.

It was discovered by Elastic engineering that when elasticsearch-certutil CLI tool is used with the csr option in order to create a new Certificate Signing Requests, the associated private key that is generated is stored on disk unencrypted even if the --pass parameter is passed in the command invocation.

An issue was discovered in Kibana where a user with Viewer role could cause a Kibana instance to crash by sending a large number of maliciously crafted requests to a specific endpoint.

An issue was discovered by Elastic whereby Watcher search input logged the search query results on DEBUG log level. This could lead to raw contents of documents stored in Elasticsearch to be printed in logs. Elastic has released 8.11.2 and 7.17.16 that resolves this issue by removing this excessive logging. This issue only affects users that use Watcher and have a Watch defined that uses the search input and additionally have set the search input’s logger to DEBUG or finer, for example using: org.elasticsearch.xpack.watcher.input.search, org.elasticsearch.xpack.watcher.input, org.elasticsearch.xpack.watcher, or wider, since the loggers are hierarchical.

It was identified that under certain specific preconditions, an API key that was originally created with a specific privileges could be subsequently used to create new API keys that have elevated privileges.

A high-privileged user, allowed to create custom osquery packs 17 could affect the availability of Kibana by uploading a maliciously crafted osquery pack.

An open redirect issue was discovered in Kibana that could lead to a user being redirected to an arbitrary website if they use a maliciously crafted Kibana URL.

A flaw was discovered in Elasticsearch, affecting document ingestion when an index template contains a dynamic field mapping of “passthrough” type. Under certain circumstances, ingesting documents in this index would cause a StackOverflow exception to be thrown and ultimately lead to a Denial of Service. Note that passthrough fields is an experimental feature.

A flaw was discovered in Kibana, allowing view-only users of alerting to use the run_soon API making the alerting rule run continuously, potentially affecting the system availability if the alerting rule is running complex queries.

It was identified that if a cross-cluster API key https://www.elastic.co/guide/en/elasticsearch/reference/8.14/security-api-create-cross-cluster-api-key.html#security-api-create-cross-cluster-api-key-request-body  restricts search for a given index using the query or the field_security parameter, and the same cross-cluster API key also grants replication for the same index, the search restrictions are not enforced during cross cluster search operations and search results may include documents and terms that should not be returned. This issue only affects the API key based security model for remote clusters https://www.elastic.co/guide/en/elasticsearch/reference/8.14/remote-clusters.html#remote-clusters-security-models  that was previously a beta feature and is released as GA with 8.14.0

An uncaught exception in Elasticsearch >= 8.4.0 and < 8.11.1 occurs when an encrypted PDF is passed to an attachment processor through the REST API. The Elasticsearch ingest node that attempts to parse the PDF file will crash. This does not happen with password-protected PDF files or with unencrypted PDF files.

Incorrect Authorization issue exists in the API key based security model for Remote Cluster Security, which is currently in Beta, in Elasticsearch 8.10.0 and before 8.13.0. This allows a malicious user with a valid API key for a remote cluster configured to use the new Remote Cluster Security to read arbitrary documents from any index on the remote cluster, and only if they use the Elasticsearch custom transport protocol to issue requests with the target index ID, the shard ID and the document ID. None of Elasticsearch REST API endpoints are affected by this issue.

A flaw was discovered in Elasticsearch, where processing a document in a deeply nested pipeline on an ingest node could cause the Elasticsearch node to crash.

An issue was discovered whereby APM Server could log at ERROR level, a response from Elasticsearch indicating that indexing the document failed and that response would contain parts of the original document. Depending on the nature of the document that the APM Server attempted to ingest, this could lead to the insertion of sensitive or private information in the APM Server logs.

An issue was discovered in the Windows Network Drive Connector when using Document Level Security to assign permissions to a file, with explicit allow write and deny read. Although the document is not accessible to the user in Network Drive it is visible in search applications to the user.

An issue was discovered by Elastic, whereby the Detection Engine Search API does not respect Document-level security (DLS) or Field-level security (FLS) when querying the .alerts-security.alerts-{space_id} indices. Users who are authorized to call this API may obtain unauthorized access to documents if their roles are configured with DLS or FLS against the aforementioned index.

An issue was discovered by Elastic whereby sensitive information may be recorded in Kibana logs in the event of an error or in the event where debug level logging is enabled in Kibana. Elastic has released Kibana 8.11.2 which resolves this issue. The messages recorded in the log may contain Account credentials for the kibana_system user, API Keys, and credentials of Kibana end-users, Elastic Security package policy objects which can contain private keys, bearer token, and sessions of 3rd-party integrations and finally Authorization headers, client secrets, local file paths, and stack traces. The issue may occur in any Kibana instance running an affected version that could potentially receive an unexpected error when communicating to Elasticsearch causing it to include sensitive data into Kibana error logs. It could also occur under specific circumstances when debug level logging is enabled in Kibana. Note: It was found that the fix for ESA-2023-25 in Kibana 8.11.1 for a similar issue was incomplete.

An issue was discovered by Elastic whereby sensitive information may be recorded in Kibana logs in the event of an error. Elastic has released Kibana 8.11.1 which resolves this issue. The error message recorded in the log may contain account credentials for the kibana_system user, API Keys, and credentials of Kibana end-users. The issue occurs infrequently, only if an error is returned from an Elasticsearch cluster, in cases where there is user interaction and an unhealthy cluster (for example, when returning circuit breaker or no shard exceptions).

An issue was discovered by Elastic whereby Elastic Agent would log a raw event in its own logs at the WARN or ERROR level if ingesting that event to Elasticsearch failed with any 4xx HTTP status code except 409 or 429. Depending on the nature of the event that Elastic Agent attempted to ingest, this could lead to the insertion of sensitive or private information in the Elastic Agent logs. Elastic has released 8.11.3 and 7.17.16 that prevents this issue by limiting these types of logs to DEBUG level logging, which is disabled by default.

An issue was discovered by Elastic whereby Beats and Elastic Agent would log a raw event in its own logs at the WARN or ERROR level if ingesting that event to Elasticsearch failed with any 4xx HTTP status code except 409 or 429. Depending on the nature of the event that Beats or Elastic Agent attempted to ingest, this could lead to the insertion of sensitive or private information in the Beats or Elastic Agent logs. Elastic has released 8.11.3 and 7.17.16 that prevents this issue by limiting these types of logs to DEBUG level logging, which is disabled by default.

An issue was discovered by Elastic whereby the Documents API of App Search logged the raw contents of indexed documents at INFO log level. Depending on the contents of such documents, this could lead to the insertion of sensitive or private information in the App Search logs. Elastic has released 8.11.2 and 7.17.16 that resolves this issue by changing the log level at which these are logged to DEBUG, which is disabled by default.

An issue was identified that allowed the unsafe deserialization of java objects from hadoop or spark configuration properties that could have been modified by authenticated users. Elastic would like to thank Yakov Shafranovich, with Amazon Web Services for reporting this issue.

It was identified that malformed scripts used in the script processor of an Ingest Pipeline could cause an Elasticsearch node to crash when calling the Simulate Pipeline API.

A local privilege escalation issue was found with the APM Java agent, where a user on the system could attach a malicious plugin to an application running the APM Java agent. By using this vulnerability, an attacker could execute code at a potentially higher level of permissions than their user typically has access to.

An issue was found with how API keys are created with the Fleet-Server service account. When an API key is created with a service account, it is possible that the API key could be created with higher privileges than intended. Using this vulnerability, a compromised Fleet-Server service account could escalate themselves to a super-user.

The Elastic APM .NET Agent can leak sensitive HTTP header information when logging the details during an application error. Normally, the APM agent will sanitize sensitive HTTP header details before sending the information to the APM server. During an application error it is possible the headers will not be sanitized before being sent.

It was discovered that Kibana was not validating a user supplied path, which would load .pbf files. Because of this, a malicious user could arbitrarily traverse the Kibana host to load internal files ending in the .pbf extension.

It was discovered that a user with Fleet admin permissions could upload a malicious package. Due to using an older version of the js-yaml library, this package would be loaded in an insecure manner, allowing an attacker to execute commands on the Kibana server.

Kibana contains an embedded version of the Chromium browser that the Reporting feature uses to generate the downloadable reports. If a user with permissions to generate reports is able to render arbitrary HTML with this browser, they may be able to leverage known Chromium vulnerabilities to conduct further attacks. Kibana contains a number of protections to prevent this browser from rendering arbitrary content.

An issue was identified by Elastic whereby sensitive information is recorded in Logstash logs under specific circumstances. The prerequisites for the manifestation of this issue are: * Logstash is configured to log in JSON format https://www.elastic.co/guide/en/logstash/current/running-logstash-command-line.html , which is not the default logging format. * Sensitive data is stored in the Logstash keystore and referenced as a variable in Logstash configuration.

Secret token configuration is never applied when using ECK <2.8 with APM Server >=8.0. This could lead to anonymous requests to an APM Server being accepted and the data ingested into this APM deployment.

A flaw was discovered in Elasticsearch, affecting the _search API that allowed a specially crafted query string to cause a Stack Overflow and ultimately a Denial of Service.

An issue has been identified with how Elasticsearch handled incoming requests on the HTTP layer. An unauthenticated user could force an Elasticsearch node to exit with an OutOfMemory error by sending a moderate number of malformed HTTP requests. The issue was identified by Elastic Engineering and we have no indication that the issue is known or that it is being exploited in the wild.

Elasticsearch generally filters out sensitive information and credentials before logging to the audit log. It was found that this filtering was not applied when requests to Elasticsearch use certain deprecated URIs for APIs. The impact of this flaw is that sensitive information such as passwords and tokens might be printed in cleartext in Elasticsearch audit logs. Note that audit logging is disabled by default and needs to be explicitly enabled and even when audit logging is enabled, request bodies that could contain sensitive information are not printed to the audit log unless explicitly configured.

It was discovered that when acting as TLS clients, Beats, Elastic Agent, APM Server, and Fleet Server did not verify whether the server certificate is valid for the target IP address; however, certificate signature validation is still performed. More specifically, when the client is configured to connect to an IP address (instead of a hostname) it does not validate the server certificate's IP SAN values against that IP address and certificate validation fails, and therefore the connection is not blocked as expected.

An issue was discovered by Elastic whereby sensitive information is recorded in Kibana logs in the event of an error. The issue impacts only Kibana version 8.10.0 when logging in the JSON layout or when the pattern layout is configured to log the %meta pattern. Elastic has released Kibana 8.10.1 which resolves this issue. The error object recorded in the log contains request information, which can include sensitive data, such as authentication credentials, cookies, authorization headers, query params, request paths, and other metadata. Some examples of sensitive data which can be included in the logs are account credentials for kibana_system, kibana-metricbeat, or Kibana end-users.

An issue was discovered in Fleet Server >= v8.10.0 and < v8.10.3 where Agent enrolment tokens are being inserted into the Fleet Server’s log file in plain text. These enrolment tokens could allow someone to enrol an agent into an agent policy, and potentially use that to retrieve other secrets in the policy including for Elasticsearch and third-party services. Alternatively a threat actor could potentially enrol agents to the clusters and send arbitrary events to Elasticsearch.

If Elastic Endpoint (v7.9.0 - v8.10.3) is configured to use a non-default option in which the logging level is explicitly set to debug, and when Elastic Agent is simultaneously configured to collect and send those logs to Elasticsearch, then Elastic Agent API keys can be viewed in Elasticsearch in plaintext. These API keys could be used to write arbitrary data and read Elastic Endpoint user artifacts.

Kibana version 8.7.0 contains an arbitrary code execution flaw. An attacker with All privileges to the Uptime/Synthetics feature could send a request that will attempt to execute JavaScript code. This could lead to the attacker executing arbitrary commands on the host system with permissions of the Kibana process.

Kibana versions 8.0.0 through 8.7.0 contain an arbitrary code execution flaw. An attacker with write access to Kibana yaml or env configuration could add a specific payload that will attempt to execute JavaScript code. This could lead to the attacker executing arbitrary commands on the host system with permissions of the Kibana process.

Filebeat versions through 7.17.9 and 8.6.2 have a flaw in httpjson input that allows the http request Authorization or Proxy-Authorization header contents to be leaked in the logs when debug logging is enabled.

An open redirect issue was discovered in Kibana that could lead to a user being redirected to an arbitrary website if they use a maliciously crafted Kibana URL.

A flaw (CVE-2022-38900) was discovered in one of Kibana’s third party dependencies, that could allow an authenticated user to perform a request that crashes the Kibana server process.

An issue was discovered in the rollback feature of Elastic Endpoint Security for Windows, which could allow unprivileged users to elevate their privileges to those of the LocalSystem account.

An issue was discovered in the rollback feature of Elastic Endpoint Security for Windows, which could allow unprivileged users to elevate their privileges to those of the LocalSystem account.

An issue was discovered in the quarantine feature of Elastic Endpoint Security and Elastic Endgame for Windows, which could allow unprivileged users to elevate their privileges to those of the LocalSystem account.

It was discovered that Kibana was not sanitizing document fields containing HTML snippets. Using this vulnerability, an attacker with the ability to write documents to an elasticsearch index could inject HTML. When the Discover app highlighted a search term containing the HTML, it would be rendered for the user.

An open redirect flaw was found in Kibana versions before 7.13.0 and 6.8.16. If a logged in user visits a maliciously crafted URL, it could result in Kibana redirecting the user to an arbitrary website.

A flaw was discovered in ECE before 3.1.1 that could lead to the disclosure of the SAML signing private key used for the RBAC features, in deployment logs in the Logging and Monitoring cluster.

A flaw was discovered in ECE before 3.4.0 that might lead to the disclosure of sensitive information such as user passwords and Elasticsearch keystore settings values in logs such as the audit log or deployment logs in the Logging and Monitoring cluster. The affected APIs are PATCH /api/v1/user and PATCH /deployments/{deployment_id}/elasticsearch/{ref_id}/keystore

A local privilege escalation (LPE) issue was discovered in the ransomware canaries features of Elastic Endpoint Security for Windows, which could allow unprivileged users to elevate their privileges to those of the LocalSystem account.

A cross-site-scripting (XSS) vulnerability was discovered in the Vega Charts Kibana integration which could allow arbitrary JavaScript to be executed in a victim’s browser.

A Denial of Service flaw was discovered in Elasticsearch. Using this vulnerability, an unauthenticated attacker could forcibly shut down an Elasticsearch node with a specifically formatted network request.

A vulnerability in Kibana could expose sensitive information related to Elastic Stack monitoring in the Kibana page source. Elastic Stack monitoring features provide a way to keep a pulse on the health and performance of your Elasticsearch cluster. Authentication with a vulnerable Kibana instance is not required to view the exposed information. The Elastic Stack monitoring exposure only impacts users that have set any of the optional monitoring.ui.elasticsearch.* settings in order to configure Kibana as a remote UI for Elastic Stack Monitoring. The same vulnerability in Kibana could expose other non-sensitive application-internal information in the page source.

A cross-site-scripting (XSS) vulnerability was discovered in the Data Preview Pane (previously known as Index Pattern Preview Pane) which could allow arbitrary JavaScript to be executed in a victim’s browser.

A flaw was discovered in Kibana in which users with Read access to the Uptime feature could modify alerting rules. A user with this privilege would be able to create new alerting rules or overwrite existing ones. However, any new or modified rules would not be enabled, and a user with this privilege could not modify alerting connectors. This effectively means that Read users could disable existing alerting rules.

A flaw was discovered in Elasticsearch 7.17.0’s upgrade assistant, in which upgrading from version 6.x to 7.x would disable the in-built protections on the security index, allowing authenticated users with “*” index permissions access to this index.

An XSS vulnerability was found in Kibana index patterns. Using this vulnerability, an authenticated user with permissions to create index patterns can inject malicious javascript into the index pattern which could execute against other users

A local privilege escalation issue was found with the APM Java agent, where a user on the system could attach a malicious file to an application running with the APM Java agent. Using this vector, a malicious or compromised user account could use the agent to run commands at a higher level of permissions than they possess. This vulnerability affects users that have set up the agent via the attacher cli 3, the attach API 2, as well as users that have enabled the profiling_inferred_spans_enabled option

An information disclosure via GET request server-side request forgery vulnerability was discovered with the Workplace Search Github Enterprise Server integration. Using this vulnerability, a malicious Workplace Search admin could use the GHES integration to view hosts that might not be publicly accessible.

It was discovered that Kibana’s JIRA connector & IBM Resilient connector could be used to return HTTP response data on internal hosts, which may be intentionally hidden from public view. Using this vulnerability, a malicious user with the ability to create connectors, could utilize these connectors to view limited HTTP response data on hosts accessible to the cluster.

It was discovered that on Windows operating systems specifically, Kibana was not validating a user supplied path, which would load .pbf files. Because of this, a malicious user could arbitrarily traverse the Kibana host to load internal files ending in the .pbf extension. Thanks to Dominic Couture for finding this vulnerability.

Elastic Enterprise Search App Search versions before 7.14.0 are vulnerable to an issue where API keys were missing authorization via an alternate route. Using this vulnerability, an authenticated attacker could utilize API keys belonging to higher privileged users.

Elastic Enterprise Search App Search versions before 7.14.0 was vulnerable to an issue where API keys were not bound to the same engines as their creator. This could lead to a less privileged user gaining access to unauthorized engines.

Elasticsearch before 7.14.0 did not apply document and field level security to searchable snapshots. This could lead to an authenticated user gaining access to information that they are unauthorized to view.

In Elasticsearch versions before 7.13.3 and 6.8.17 an uncontrolled recursion vulnerability that could lead to a denial of service attack was identified in the Elasticsearch Grok parser. A user with the ability to submit arbitrary queries to Elasticsearch could create a malicious Grok query that will crash the Elasticsearch node.

All versions of Elastic Cloud Enterprise has the Elasticsearch “anonymous” user enabled by default in deployed clusters. While in the default setting the anonymous user has no permissions and is unable to successfully query any Elasticsearch APIs, an attacker could leverage the anonymous user to gain insight into certain details of a deployed cluster.

A memory disclosure vulnerability was identified in Elasticsearch 7.10.0 to 7.13.3 error reporting. A user with the ability to submit arbitrary queries to Elasticsearch could submit a malformed query that would result in an error message returned containing previously used portions of a data buffer. This buffer could contain sensitive information such as Elasticsearch documents or authentication details.

It was discovered that OpenShift Container Platform's (OCP) distribution of Kibana could open in an iframe, which made it possible to intercept and manipulate requests. This flaw allows an attacker to trick a user into performing arbitrary actions in OCP's distribution of Kibana, such as clickjacking.

Elastic App Search versions after 7.11.0 and before 7.12.0 contain an XML External Entity Injection issue (XXE) in the App Search web crawler beta feature. Using this vector, an attacker whose website is being crawled by App Search could craft a malicious sitemap.xml to traverse the filesystem of the host running the instance and obtain sensitive files.

Kibana versions before 7.12.1 contain a denial of service vulnerability was found in the webhook actions due to a lack of timeout or a limit on the request size. An attacker with permissions to create webhook actions could drain the Kibana host connection pool, making Kibana unavailable for all other users.

In Logstash versions after 6.4.0 and before 6.8.15 and 7.12.0 a TLS certificate validation flaw was found in the monitoring feature. When specifying a trusted server CA certificate Logstash would not properly verify the certificate returned by the monitoring server. This could result in a man in the middle style attack against the Logstash monitoring data.

In Elasticsearch versions before 7.11.2 and 6.8.15 a document disclosure flaw was found when Document or Field Level Security is used. Search queries do not properly preserve security permissions when executing certain cross-cluster search queries. This could result in the search disclosing the existence of documents the attacker should not be able to view. This could result in an attacker gaining additional insight into potentially sensitive indices.

In Kibana versions before 7.12.0 and 6.8.15 a flaw in the session timeout was discovered where the xpack.security.session.idleTimeout setting is not being respected. This was caused by background polling activities unintentionally extending authenticated users sessions, preventing a user session from timing out.

Elasticsearch versions before 7.11.2 and 6.8.15 contain a document disclosure flaw was found in the Elasticsearch suggester and profile API when Document and Field Level Security are enabled. The suggester and profile API are normally disabled for an index when document level security is enabled on the index. Certain queries are able to enable the profiler and suggester which could lead to disclosing the existence of documents and fields the attacker should not be able to view.

A document disclosure flaw was found in Elasticsearch versions after 7.6.0 and before 7.11.0 when Document or Field Level Security is used. Get requests do not properly apply security permissions when executing a query against a recently updated document. This affects documents that have been updated and not yet refreshed in the index. This could result in the search disclosing the existence of documents and fields the attacker should not be able to view.

The Elastic APM agent for Go versions before 1.11.0 can leak sensitive HTTP header information when logging the details during an application panic. Normally, the APM agent will sanitize sensitive HTTP header details before sending the information to the APM server. During an application panic it is possible the headers will not be sanitized before being sent.

Elasticsearch versions before 7.10.0 and 6.8.14 have an information disclosure issue when audit logging and the emit_request_body option is enabled. The Elasticsearch audit log could contain sensitive information such as password hashes or authentication tokens. This could allow an Elasticsearch administrator to view these details.

Elasticsearch versions 7.7.0 to 7.10.1 contain an information disclosure flaw in the async search API. Users who execute an async search will improperly store the HTTP headers. An Elasticsearch user with the ability to read the .tasks index could obtain sensitive request headers of other users in the cluster. This issue is fixed in Elasticsearch 7.10.2

The elasticsearch-operator does not validate the namespace where kibana logging resource is created and due to that it is possible to replace the original openshift-logging console link (kibana console) to different one, created based on the new CR for the new kibana resource. This could lead to an arbitrary URL redirection or the openshift-logging console link damage. This flaw affects elasticsearch-operator-container versions before 4.7.

Elasticsearch versions before 6.8.13 and 7.9.2 contain a document disclosure flaw when Document or Field Level Security is used. Search queries do not properly preserve security permissions when executing certain complex queries. This could result in the search disclosing the existence of documents the attacker should not be able to view. This could result in an attacker gaining additional insight into potentially sensitive indices.

In Elasticsearch before 7.9.0 and 6.8.12 a field disclosure flaw was found when running a scrolling search with Field Level Security. If a user runs the same query another more privileged user recently ran, the scrolling search can leak fields that should be hidden. This could result in an attacker gaining additional permissions against a restricted index.

Elastic Enterprise Search before 7.9.0 contain a credential exposure flaw in the App Search interface. If a user is given the �developer� role, they will be able to view the administrator API credentials. These credentials could allow the developer user to conduct operations with the same permissions of the App Search administrator.

Kibana versions before 6.8.9 and 7.7.0 contains a stored XSS flaw in the TSVB visualization. An attacker who is able to edit or create a TSVB visualization could allow the attacker to obtain sensitive information from, or perform destructive actions, on behalf of Kibana users who edit the TSVB visualization.

The fix for CVE-2020-7009 was found to be incomplete. Elasticsearch versions from 6.7.0 to 6.8.7 and 7.0.0 to 7.6.1 contain a privilege escalation flaw if an attacker is able to create API keys and also authentication tokens. An attacker who is able to generate an API key and an authentication token can perform a series of steps that result in an authentication token being generated with elevated privileges.

Kibana versions before 6.8.9 and 7.7.0 contain a prototype pollution flaw in TSVB. An authenticated attacker with privileges to create TSVB visualizations could insert data that would cause Kibana to execute arbitrary code. This could possibly lead to an attacker executing code with the permissions of the Kibana process on the host system.

Kibana versions 6.7.0 to 6.8.8 and 7.0.0 to 7.6.2 contain a prototype pollution flaw in the Upgrade Assistant. An authenticated attacker with privileges to write to the Kibana index could insert data that would cause Kibana to execute arbitrary code. This could possibly lead to an attacker executing code with the permissions of the Kibana process on the host system.

Elastic App Search versions before 7.7.0 contain a cross site scripting (XSS) flaw when displaying document URLs in the Reference UI. If the Reference UI injects a URL into a result, that URL will be rendered by the web browser. If an attacker is able to control the contents of such a field, they could execute arbitrary JavaScript in the victim�s web browser.

Elasticsearch versions from 6.7.0 before 6.8.8 and 7.0.0 before 7.6.2 contain a privilege escalation flaw if an attacker is able to create API keys. An attacker who is able to generate an API key can perform a series of steps that result in an API key being generated with elevated privileges.

Kibana versions before 6.8.6 and 7.5.1 contain a cross site scripting (XSS) flaw in the coordinate and region map visualizations. An attacker with the ability to create coordinate map visualizations could create a malicious visualization. If another Kibana user views that visualization or a dashboard containing the visualization it could execute JavaScript in the victim�s browser.

Logstash versions before 7.4.1 and 6.8.4 contain a denial of service flaw in the Logstash Beats input plugin. An unauthenticated user who is able to connect to the port the Logstash beats input could send a specially crafted network packet that would cause Logstash to stop responding.

Elasticsearch versions 7.0.0-7.3.2 and 6.7.0-6.8.3 contain a username disclosure flaw was found in the API Key service. An unauthenticated attacker could send a specially crafted request and determine if a username exists in the Elasticsearch native realm.

A local file disclosure flaw was found in Elastic Code versions 7.3.0, 7.3.1, and 7.3.2. If a malicious code repository is imported into Code it is possible to read arbitrary files from the local filesystem of the Kibana instance running Code with the permission of the Kibana system user.

When the Elastic APM agent for Python versions before 5.1.0 is run as a CGI script, there is a variable name clash flaw if a remote attacker can control the proxy header. This could result in an attacker redirecting collected APM data to a proxy of their choosing.

Kibana versions before 6.8.2 and 7.2.1 contain a server side request forgery (SSRF) flaw in the graphite integration for Timelion visualizer. An attacker with administrative Kibana access could set the timelion:graphite.url configuration option to an arbitrary URL. This could possibly lead to an attacker accessing external URL resources as the Kibana process on the host system.

A TLS certificate validation flaw was found in Elastic APM agent for Ruby versions before 2.9.0. When specifying a trusted server CA certificate via the 'server_ca_cert' setting, the Ruby agent would not properly verify the certificate returned by the APM server. This could result in a man in the middle style attack against the Ruby agent.

A race condition flaw was found in the response headers Elasticsearch versions before 7.2.1 and 6.8.2 returns to a request. On a system with multiple users submitting requests, it could be possible for an attacker to gain access to response header containing sensitive data from another user.

Winlogbeat versions before 5.6.16 and 6.6.2 had an insufficient logging flaw. An attacker able to inject certain characters into a log entry could prevent Winlogbeat from recording the event.

A sensitive data disclosure flaw was found in the way Logstash versions before 5.6.15 and 6.6.1 logs malformed URLs. If a malformed URL is specified as part of the Logstash configuration, the credentials for the URL could be inadvertently logged as part of the error message.

A permission issue was found in Elasticsearch versions before 5.6.15 and 6.6.1 when Field Level Security and Document Level Security are disabled and the _aliases, _shrink, or _split endpoints are used . If the elasticsearch.yml file has xpack.security.dls_fls.enabled set to false, certain permission checks are skipped when users perform one of the actions mentioned above, to make existing data available under a new index/alias name. This could result in an attacker gaining additional permissions against a restricted index.

Kibana versions before 6.6.1 contain an arbitrary code execution flaw in the security audit logger. If a Kibana instance has the setting xpack.security.audit.enabled set to true, an attacker could send a request that will attempt to execute javascript code. This could possibly lead to an attacker executing arbitrary commands with permissions of the Kibana process on the host system.

Kibana versions before 5.6.15 and 6.6.1 contain an arbitrary code execution flaw in the Timelion visualizer. An attacker with access to the Timelion application could send a request that will attempt to execute javascript code. This could possibly lead to an attacker executing arbitrary commands with permissions of the Kibana process on the host system.

Kibana versions before 5.6.15 and 6.6.1 had a cross-site scripting (XSS) vulnerability that could allow an attacker to obtain sensitive information from or perform destructive actions on behalf of other Kibana users.

Elasticsearch Security versions 6.5.0 and 6.5.1 contain an XXE flaw in Machine Learning's find_file_structure API. If a policy allowing external network access has been added to Elasticsearch's Java Security Manager then an attacker could send a specially crafted request capable of leaking content of local files on the Elasticsearch node. This could allow a user to access information that they should not have access to.

Kibana versions before 6.4.3 and 5.6.13 contain an arbitrary file inclusion flaw in the Console plugin. An attacker with access to the Kibana Console API could send a request that will attempt to execute javascript code. This could possibly lead to an attacker executing arbitrary commands with permissions of the Kibana process on the host system.

Kibana versions 4.0 to 4.6, 5.0 to 5.6.12, and 6.0 to 6.4.2 contain an error in the way authorization credentials are used when generating PDF reports. If a report requests external resources plaintext credentials are included in the HTTP request that could be recovered by an external resource provider.

Elasticsearch Security versions 6.4.0 to 6.4.2 contain an error in the way request headers are applied to requests when using the Active Directory, LDAP, Native, or File realms. A request may receive headers intended for another request if the same username is being authenticated concurrently; when used with run as, this can result in the request running as the incorrect user. This could allow a user to access information that they should not have access to.

Elasticsearch Alerting and Monitoring in versions before 6.4.1 or 5.6.12 have an information disclosure issue when secrets are configured via the API. The Elasticsearch _cluster/settings API, when queried, could leak sensitive configuration information such as passwords, tokens, or usernames. This could allow an authenticated Elasticsearch user to improperly view these details.

Kibana versions 5.3.0 to 6.4.1 had a cross-site scripting (XSS) vulnerability via the source field formatter that could allow an attacker to obtain sensitive information from or perform destructive actions on behalf of other Kibana users.

In Elastic Cloud Enterprise (ECE) versions prior to 1.1.4 it was discovered that a user could scale out allocators on new hosts with an invalid roles token. An attacker with access to the previous runner ID and IP address of the coordinator-host could add a allocator to an existing ECE install to gain access to other clusters data.

Elastic Cloud Enterprise (ECE) versions prior to 1.1.4 contain an information exposure vulnerability. It was discovered that certain exception conditions would result in encryption keys, passwords, and other security sensitive headers being leaked to the allocator logs. An attacker with access to the logging cluster may obtain leaked credentials and perform authenticated actions using these credentials.

A sensitive data disclosure flaw was found in the Elasticsearch repository-azure (formerly elasticsearch-cloud-azure) plugin. When the repository-azure plugin is set to log at TRACE level Azure credentials can be inadvertently logged.

In Elasticsearch versions 6.0.0-beta1 to 6.2.4 a disclosure flaw was found in the _snapshot API. When the access_key and security_key parameters are set using the _snapshot API they can be exposed as plain text by users able to query the _snapshot API.

In Elastic Cloud Enterprise (ECE) versions prior to 1.1.4 a default master encryption key is used in the process of granting ZooKeeper access to Elasticsearch clusters. Unless explicitly overwritten, this master key is predictable across all ECE deployments. If an attacker can connect to ZooKeeper directly they would be able to access configuration information of other tenants if their cluster ID is known.

X-Pack Machine Learning versions before 6.2.4 and 5.6.9 had a cross-site scripting (XSS) vulnerability. If an attacker is able to inject data into an index that has a ML job running against it, then when another user views the results of the ML job it could allow the attacker to obtain sensitive information from or perform destructive actions on behalf of that other ML user.

X-Pack Machine Learning versions before 6.2.4 and 5.6.9 had a cross-site scripting (XSS) vulnerability. Users with manage_ml permissions could create jobs containing malicious data as part of their configuration that could allow the attacker to obtain sensitive information from or perform destructive actions on behalf of other ML users viewing the results of the jobs.

X-Pack Security versions 6.2.0, 6.2.1, and 6.2.2 are vulnerable to a user impersonation attack via incorrect XML canonicalization and DOM traversal. An attacker might have been able to impersonate a legitimate user if the SAML Identity Provider allows for self registration with arbitrary identifiers and the attacker can register an account which an identifier that shares a suffix with a legitimate account. Both of those conditions must be true in order to exploit this flaw.

Kibana versions after 5.1.1 and before 5.6.7 and 6.1.3 had a cross-site scripting (XSS) vulnerability in the tag cloud visualization that could allow an attacker to obtain sensitive information from or perform destructive actions on behalf of other Kibana users.

Kibana versions after 6.1.0 and before 6.1.3 had a cross-site scripting (XSS) vulnerability in labs visualizations that could allow an attacker to obtain sensitive information from or perform destructive actions on behalf of other Kibana users.

The fix in Kibana for ESA-2017-23 was incomplete. With X-Pack security enabled, Kibana versions before 6.1.3 and 5.6.7 have an open redirect vulnerability on the login page that would enable an attacker to craft a link that redirects to an arbitrary website.

Kibana versions 5.1.1 to 6.1.2 and 5.6.6 had a cross-site scripting (XSS) vulnerability via the colored fields formatter that could allow an attacker to obtain sensitive information from or perform destructive actions on behalf of other Kibana users.

When logging warnings regarding deprecated settings, Logstash before 5.6.6 and 6.x before 6.1.2 could inadvertently log sensitive information.

Elasticsearch before 1.6.1 allows remote attackers to execute arbitrary code via unspecified vectors involving the transport protocol. NOTE: ZDI appears to claim that CVE-2015-3253 and CVE-2015-5377 are the same vulnerability

The Kibana fix for CVE-2017-8451 was found to be incomplete. With X-Pack installed, Kibana versions before 6.0.1 and 5.6.5 have an open redirect vulnerability on the login page that would enable an attacker to craft a link that redirects to an arbitrary website.

Kibana versions prior to 6.0.1 and 5.6.5 had a cross-site scripting (XSS) vulnerability via URL fields that could allow an attacker to obtain sensitive information from or perform destructive actions on behalf of other Kibana users.

An error was found in the permission model used by X-Pack Alerting 5.0.0 to 5.6.0 whereby users mapped to certain built-in roles could create a watch that results in that user gaining elevated privileges.

An error was found in the X-Pack Security 5.3.0 to 5.5.2 privilege enforcement. If a user has either 'delete' or 'index' permissions on an index in a cluster, they may be able to issue both delete and index requests against that index.

Kibana versions prior to 5.6.1 had a cross-site scripting (XSS) vulnerability in Timelion that could allow an attacker to obtain sensitive information from or perform destructive actions on behalf of other Kibana users.

An error was found in the X-Pack Security TLS trust manager for versions 5.0.0 to 5.5.1. If reloading the trust material fails the trust manager will be replaced with an instance that trusts all certificates. This could allow any node using any certificate to join a cluster. The proper behavior in this instance is for the TLS trust manager to deny all certificates.

Logstash 1.4.x before 1.4.5 and 1.5.x before 1.5.4 with Lumberjack output or the Logstash forwarder does not validate SSL/TLS certificates from the Logstash server, which might allow attackers to obtain sensitive information via a man-in-the-middle attack.

Elasticsearch X-Pack Security versions 5.0.0 to 5.4.3, when enabled, can result in the Elasticsearch _nodes API leaking sensitive configuration information, such as the paths and passphrases of SSL keys that were configured as part of an authentication realm. This could allow an authenticated Elasticsearch user to improperly view these details.

In Kibana X-Pack security versions prior to 5.4.3 if a Kibana user opens a crafted Kibana URL the result could be a redirect to an improperly initialized Kibana login screen. If the user enters credentials on this screen, the credentials will appear in the URL bar. The credentials could then be viewed by untrusted parties or logged into the Kibana access logs.

Logstash 1.5.x before 1.5.3 and 1.4.x before 1.4.4 allows remote attackers to read communications between Logstash Forwarder agent and Logstash server.

Kibana versions prior to 5.2.1 configured for SSL client access, file descriptors will fail to be cleaned up after certain requests and will accumulate over time until the process crashes.

With X-Pack installed, Kibana versions before 5.3.1 have an open redirect vulnerability on the login page that would enable an attacker to craft a link that redirects to an arbitrary website.

X-Pack 5.1.1 did not properly apply document and field level security to multi-search and multi-get requests so users without access to a document and/or field may have been able to access this information.

X-Pack Security 5.2.x would allow access to more fields than the user should have seen if the field level security rules used a mix of grant and exclude rules when merging multiple rules with field level security rules for the same index.

Kibana versions after and including 4.3 and before 4.6.2 are vulnerable to a cross-site scripting (XSS) attack.

Kibana versions before 4.6.3 and 5.0.1 have an open redirect vulnerability that would enable an attacker to craft a link in the Kibana domain that redirects to an arbitrary website.

With X-Pack installed, Kibana versions 5.0.0 and 5.0.1 were not properly authenticating requests to advanced settings and the short URL service, any authenticated user could make requests to those services regardless of their own permissions.

Logstash versions prior to 2.3.3, when using the Netflow Codec plugin, a remote attacker crafting malicious Netflow v5, Netflow v9 or IPFIX packets could perform a denial of service attack on the Logstash instance. The errors resulting from these crafted inputs are not handled by the codec and can cause the Logstash process to exit.

Logstash prior to version 2.1.2, the CSV output can be attacked via engineered input that will create malicious formulas in the CSV data.

Logstash prior to version 2.3.4, Elasticsearch Output plugin would log to file HTTP authorization headers which could contain sensitive information.

Kibana before 4.5.4 and 4.1.11 are vulnerable to an XSS attack that would allow an attacker to execute arbitrary JavaScript in users' browsers.

Kibana before 4.5.4 and 4.1.11 when a custom output is configured for logging in, cookies and authorization headers could be written to the log files. This information could be used to hijack sessions of other users when using Kibana behind some form of authentication such as Shield.

Kibana Reporting plugin version 2.4.0 is vulnerable to a CSRF vulnerability that could allow an attacker to generate superfluous reports whenever an authenticated Kibana user navigates to a specially-crafted page.

Kibana versions prior to 4.1.3 and 4.2.1 are vulnerable to a XSS attack.

Elastic X-Pack Security versions prior to 5.4.1 and 5.3.3 did not always correctly apply Document Level Security to index aliases. This bug could allow a user with restricted permissions to view data they should not have access to when performing certain operations against an index alias.

Starting in version 5.3.0, Kibana had a cross-site scripting (XSS) vulnerability in the Discover page that could allow an attacker to obtain sensitive information from or perform destructive actions on behalf of other Kibana users.

Kibana version 5.4.0 was affected by a Cross Site Scripting (XSS) bug in the Time Series Visual Builder. This bug could allow an attacker to obtain sensitive information from Kibana users.

Elastic X-Pack Security versions 5.0.0 to 5.4.0 contain a privilege escalation bug in the run_as functionality. This bug prevents transitioning into the specified user specified in a run_as request. If a role has been created using a template that contains the _user properties, the behavior of run_as will be incorrect. Additionally if the run_as user specified does not exist, the transition will not happen.

Cross-site request forgery (CSRF) vulnerability in Elasticsearch Kibana before 4.1.3 and 4.2.x before 4.2.1 allows remote attackers to hijack the authentication of unspecified victims via unknown vectors.

Directory traversal vulnerability in the file output plugin in Elasticsearch Logstash before 1.4.3 allows remote attackers to write to arbitrary files via vectors related to dynamic field references in the path option.

Cross-site scripting (XSS) vulnerability in Elasticsearch Kibana 4.x before 4.0.3 allows remote attackers to inject arbitrary web script or HTML via unspecified vectors.

The Groovy scripting engine in Elasticsearch before 1.3.8 and 1.4.x before 1.4.3 allows remote attackers to bypass the sandbox protection mechanism and execute arbitrary shell commands via a crafted script.

The default configuration in Elasticsearch before 1.2 enables dynamic scripting, which allows remote attackers to execute arbitrary MVEL expressions and Java code via the source parameter to _search. NOTE: this only violates the vendor's intended security policy if the user does not run Elasticsearch in its own independent virtual machine.

Elasticsearch Logstash 1.0.14 through 1.4.x before 1.4.2 allows remote attackers to execute arbitrary commands via a crafted event in (1) zabbix.rb or (2) nagios_nsca.rb in outputs/.