Description

Memory Allocation with Excessive Size Value (CWE-789) in Elasticsearch can lead to denial of service via Excessive Allocation (CAPEC-130). An authenticated user holding only read privileges on a single index can submit one small, specially crafted search request that causes an excessively large memory allocation, exhausting the JVM heap and terminating the affected node.

Executive Summary

Technical Details

Mitigations

References

Additional Metadata

{
  "score": "6.5",
  "pubDate": "2026-08-13T20:17:24.927Z",
  "pubdate": "2026-08-13T20:17:24.927Z",
  "executiveSummary": "A memory allocation vulnerability categorized under CWE-789 (Memory Allocation with Excessive Size Value) exists in Elasticsearch, leading to a denial of service via excessive allocation, mapped to CAPEC-130. This vulnerability allows an authenticated attacker to trigger uncontrolled memory exhaustion within the Java Virtual Machine (JVM) heap, resulting in the abnormal termination of the affected Elasticsearch node.\nThe flaw impacts Elasticsearch installations handling search requests without proper input size validation or bounds checking on memory allocation parameters. The risk implication is severe, as it directly impacts cluster availability and operational stability, potentially leading to cascading failures across the distributed environment.\nExploitation requirements dictate that the attacker must hold authentication credentials, specifically possessing only read privileges on a single index. Despite these restricted privileges, the attacker can successfully leverage the vulnerability by interacting with standard query interfaces.\nThe attack is executed by submitting a single, small, and specially crafted search request designed to coerce the query processing engine into allocating an excessively large memory buffer. This bypasses typical resource constraints and instantly consumes available heap space, crashing the JVM process without requiring complex payloads or high-level administrative privileges.",
  "technicalDetails": "The root cause of the vulnerability stems from inadequate validation and sanitization of size or allocation parameters derived from incoming search queries within the Elasticsearch query parsing and execution pipeline. When the vulnerable component processes a maliciously crafted payload, it calculates or accepts an excessively large memory size value without enforcing upper-bound safety thresholds.\nThe vulnerability resides within the memory allocation routines handling specific search operations inside the Elasticsearch search execution subsystem. Because the input request appears small and structurally valid, it evades preliminary payload filters and reaches the internal data structures where JVM heap memory is dynamically requested.\nThe exploitation method leverages CAPEC-130 (Excessive Allocation), where an authenticated user with low-level access (specifically read privileges restricted to a single index) interacts with the cluster via standard query APIs. The attack flow initiates when the client transmits the malicious search request over the network protocol used by Elasticsearch. Upon receipt, the parsing engine interprets the crafted parameters and issues a massive memory allocation request to the JVM.\nThe payload behavior forces the underlying Java runtime to reserve a disproportionately huge block of memory, instantly depleting the available heap space. This triggers an immediate OutOfMemoryError (OOM) condition within the JVM. Due to the severity of heap exhaustion in Java-based enterprise search engines, the Java runtime environment or the cluster orchestration layer terminates the affected Elasticsearch node to prevent systemic corruption.\nThe post-exploitation impact is strictly focused on denial of service and cluster disruption. While the vulnerability does not directly facilitate remote code execution, privilege escalation, or unauthorized data exfiltration, the termination of a node can degrade cluster health, cause shard unassignment, disrupt ongoing read and write operations, and potentially trigger split-brain or cascading node failures depending on cluster topology and replica configurations."
}