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": "2026-09-26T21:16:56.277Z",
  "pubdate": "2026-09-26T21:16:56.277Z",
  "executiveSummary": "This vulnerability involves Uncontrolled Resource Consumption (CWE-400) within Elasticsearch, facilitating a Denial of Service (DoS) attack via Excessive Allocation (CAPEC-130).\nThe flaw stems from the application's failure to adequately bound or throttle resource requests, allowing an unauthenticated or authenticated attacker to trigger disproportionate memory or CPU allocation.\nThe primary impact is service instability or total system crash, resulting in a denial of service for legitimate users and operations.\nRisk implications are high for critical infrastructure, as availability is severely compromised.\nExploitation requires the ability to submit crafted requests that force the underlying execution engine to allocate excessive resources beyond established safety thresholds.\nThis vulnerability highlights a systemic failure in resource management and request sanitization within the affected Elasticsearch components.",
  "technicalDetails": "The core vulnerability is identified as CWE-400: Uncontrolled Resource Consumption. In the context of Elasticsearch, this manifests as an inability to properly constrain resource-intensive operations, leading to an exploit pattern defined by CAPEC-130: Excessive Allocation.\nWhen a request is processed by the Elasticsearch cluster, the engine may initiate heap-intensive operations or spawn multiple threads to handle complex queries, aggregations, or bulk indexing tasks. If the system does not enforce strict limits on the memory or CPU cycles consumed by a single request, an attacker can craft a payload designed to maximize resource footprint.\nThe attack flow typically initiates with an attacker identifying an endpoint capable of executing non-trivial resource operations, such as deep-paged searches, complex aggregations, or recursive scripts. By dispatching a high volume of these requests or a single, highly complex request, the attacker forces the JVM (Java Virtual Machine) to allocate heap space aggressively. This eventually triggers frequent Garbage Collection (GC) cycles, resulting in 'Stop-the-World' events that degrade system responsiveness.\nContinued excessive allocation eventually leads to an OutOfMemoryError (OOME), causing the node to become unresponsive or crash entirely. In a distributed environment, if the workload is distributed across multiple nodes, the attacker may trigger a cascading failure, impacting the availability of the entire cluster.\nThe vulnerability is deeply tied to the request handling lifecycle where input validation and resource budgeting are missing or insufficient. Because Elasticsearch relies on memory-mapped files and high-concurrency threading, the lack of per-request circuit breakers or concurrency limits facilitates the exploitation of underlying hardware and software constraints.\nPost-exploitation, the service remains unavailable until manual intervention or automated restart procedures are executed. No arbitrary code execution is inherently implied, but the degradation of security controls during an unstable state may introduce further attack vectors if monitoring systems fail to detect the exhaustion patterns in real-time."
}