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.
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.
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.
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.
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 Insertion of sensitive information in log file