CVE-2026-63144 in Elasticsearch
Summary
by MITRE • 07/22/2026
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.
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Analysis
by VulDB Data Team • 07/22/2026
Uncontrolled recursion represents a fundamental flaw in software design where a function or process calls itself without proper termination conditions, leading to infinite loops that consume system resources and ultimately cause system failure. This vulnerability class is categorized under CWE-674 and falls within the broader category of denial of service conditions that can be exploited by malicious actors to disrupt service availability. Elasticsearch, as a distributed search and analytics engine built on top of Apache Lucene, processes complex query requests through sophisticated evaluation mechanisms that must handle various data structures and logical operations. When a user with read-level index access submits a specially crafted search request, the query parser and evaluator within Elasticsearch can be manipulated to enter recursive processing loops that expand exponentially. The vulnerability manifests when the query contains nested structures or logical constructs that trigger internal recursion within the query evaluation engine's code paths.
The technical exploitation of this vulnerability involves crafting search requests that contain recursive patterns in their structure, such as deeply nested boolean queries, complex multi-level aggregations, or malformed filter conditions that cause the Elasticsearch engine to repeatedly process the same logical units. These crafted requests can be submitted by authenticated users who possess read permissions on specific indices, making the attack surface broader than initially apparent since access control mechanisms do not prevent this particular class of malformed input from being processed. The processing behavior within Elasticsearch's query evaluation component becomes unstable as it attempts to resolve these recursive structures, leading to stack overflow conditions or excessive memory consumption that eventually results in fatal errors. When these errors occur, they cause the affected Elasticsearch node to crash and terminate its process, which can be observed through system logs indicating out-of-memory exceptions or stack overflow errors.
The operational impact of this vulnerability extends significantly beyond simple service disruption, particularly in environments where Elasticsearch clusters are mission-critical components of larger applications or data platforms. In single-node deployments, the consequences are immediate and complete, as the termination of a single node results in total service unavailability until manual intervention occurs to restart the node or restore its functionality. Multi-node clusters experience more complex degradation patterns where affected nodes repeatedly crash and restart, creating a cascading effect that can destabilize the entire cluster's operation and lead to sustained availability issues. This behavior creates additional operational challenges for administrators who must monitor cluster health, identify affected nodes, and implement temporary workarounds while waiting for patches or configuration changes to resolve the underlying issue.
Organizations utilizing Elasticsearch systems should immediately implement mitigation strategies to address this vulnerability, including applying official security patches from the Elasticsearch project as soon as they become available. Configuration-level mitigations can involve implementing query timeout mechanisms, setting maximum recursion depth limits within the Elasticsearch configuration, and establishing resource constraints that prevent any single query from consuming excessive system resources. Network-level controls such as rate limiting and query complexity monitoring can provide additional protection layers by detecting and blocking suspicious request patterns before they reach the core processing components. The ATT&CK framework categorizes this vulnerability under the denial of service category with specific techniques related to resource exhaustion and system instability, making it a critical target for both defensive measures and incident response protocols. Regular security assessments and penetration testing should include evaluation of query processing components to identify similar recursion patterns that may not yet be known or patched within the Elasticsearch ecosystem.
The broader implications of uncontrolled recursion vulnerabilities extend beyond Elasticsearch to encompass all software systems that process complex data structures or implement recursive algorithms without proper safeguards. Industry standards such as CWE-674 provide essential guidance for developers and security professionals in understanding how to prevent these conditions through proper input validation, termination condition implementation, and resource monitoring. Organizations should establish comprehensive vulnerability management programs that include regular updates to all software components, implementation of automated monitoring systems for unusual resource consumption patterns, and development of incident response procedures specifically tailored to handle denial of service conditions caused by recursive processing issues. The vulnerability serves as a reminder of the critical importance of robust input validation and resource management in distributed systems where malicious or malformed inputs can trigger cascading failures that affect entire infrastructure components rather than isolated processes.