CVE-2026-63263 in Elasticsearch
Summary
by MITRE • 07/22/2026
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.
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Analysis
by VulDB Data Team • 07/22/2026
Elasticsearch presents a critical vulnerability categorized under CWE-400, which describes uncontrolled resource consumption that can result in denial of service conditions. This specific weakness manifests through exponential data expansion as outlined in CAPEC-197, where an authenticated user can exploit a flaw in the ES|QL engine to initiate queries that consume excessive computational resources. The vulnerability specifically targets the query evaluation process within Elasticsearch's distributed search capabilities, creating a scenario where legitimate operations become impossible due to resource exhaustion.
The technical flaw exploits the ES|QL engine's handling of certain query patterns that trigger exponential growth in CPU consumption during processing. When an authenticated user submits a crafted query, the system's query worker threads experience disproportionate resource allocation, with computational overhead increasing at an exponential rate relative to input complexity. This behavior occurs because the query evaluation algorithm does not properly implement bounds checking or resource limiting mechanisms for specific data structures or pattern matching operations within the ES|QL execution engine.
The operational impact of this vulnerability extends beyond simple performance degradation to complete service unavailability. Once the resource exhaustion occurs, the affected Elasticsearch node becomes incapable of processing additional ES|QL queries until a full system restart is performed, creating significant downtime and service disruption for applications relying on the search platform. The persistence of resource exhaustion beyond query completion means that even after an individual malicious query finishes executing, the system remains vulnerable to further exploitation through repeated requests.
This vulnerability directly maps to several ATT&CK tactics including privilege escalation and denial of service, as attackers can leverage authenticated access to exhaust system resources and disrupt legitimate operations. Organizations using Elasticsearch should implement immediate mitigations including query timeout configurations, resource limits for query workers, and monitoring systems to detect unusual CPU consumption patterns. Additionally, regular updates to Elasticsearch versions that address this specific resource management flaw are essential for maintaining system integrity and preventing exploitation attempts.
The root cause of this vulnerability stems from inadequate input validation and resource management within the ES|QL engine's query processing pipeline, highlighting the importance of implementing proper bounds checking and computational resource limits in distributed search systems. System administrators should consider implementing rate limiting mechanisms and query complexity controls to prevent exploitation while maintaining service availability for legitimate users.