Description

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

Executive Summary

Technical Details

Mitigations

References

Additional Metadata

{
  "score": "6.5",
  "pubDate": "2026-09-26T21:16:56.027Z",
  "pubdate": "2026-09-26T21:16:56.027Z",
  "executiveSummary": "This vulnerability pertains to Uncontrolled Resource Consumption (CWE-400) within the Elasticsearch platform, specifically manifesting through Excessive Allocation (CAPEC-130).\nThe flaw allows an attacker to manipulate resource allocation patterns, resulting in a Denial of Service (DoS) state by exhausting critical system resources such as memory, CPU, or heap space.\nElasticsearch serves as a search and analytics engine; when resource constraints are not properly enforced during query processing or ingestion, the system becomes susceptible to performance degradation or complete service unavailability.\nThe risk implication is significant, as an unauthenticated or low-privileged attacker can trigger resource exhaustion without requiring specialized access to the underlying infrastructure.\nExploitation involves submitting crafted requests that force the engine to allocate excessive memory or CPU cycles beyond configured limits, effectively destabilizing the node or the entire cluster.\nThe vulnerability underscores the importance of strict resource quotas and query validation to prevent service disruption through resource starvation.",
  "technicalDetails": "The root cause of this vulnerability lies in the insufficient enforcement of resource boundaries during the lifecycle of complex query execution or high-volume data ingestion operations.\nWhen a request is processed, the Elasticsearch engine allocates heap memory or CPU time to handle data structures, aggregation operations, or search execution plans. If these operations are not bounded by strict limits, an attacker can submit requests designed to maximize memory footprint or processing duration.\nThe attack flow follows a predictable pattern: 1) The attacker identifies an entry point for query submission or document indexing. 2) The attacker submits a malicious payload—such as a deeply nested search query or a massive document requiring intensive parsing—that triggers an 'Excessive Allocation' condition. 3) The node’s memory management system or Java Virtual Machine (JVM) experiences garbage collection pressure or OutOfMemoryError (OOME) exceptions due to the unauthorized resource demand. 4) As the node attempts to satisfy the excessive allocation request, it enters a thrashing state, leading to degraded performance or service suspension.\nThe vulnerable components are typically the Query Parser or the Indexing engine, which lack mechanisms to 'short-circuit' requests that exceed pre-defined complexity or resource-usage heuristics.\nExploitation does not necessarily require elevated privileges, depending on the cluster's default authentication settings. The attack is effective over standard network protocols (typically HTTP/REST) used to communicate with the Elasticsearch API.\nThe post-exploitation impact is a Denial of Service (DoS) condition where the affected node fails to respond to legitimate administrative or analytical traffic. In distributed cluster environments, this can lead to a cascading failure if internal load balancers or cluster state managers struggle to redistribute the workload after the initial node failure.\nThis vulnerability highlights the need for a robust circuit breaker pattern within the internal architecture to catch and reject requests that threaten the stability of the host process before the JVM heap is exhausted."
}