Threat Intelligence Database

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 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).

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.

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.

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.