CVE-2026-72642
Received Received - Intake

Elasticsearch Native Inference Heap Corruption Vulnerability

Publication date: 2026-08-13

Last updated on: 2026-08-13

Assigner: Elastic

Description
The native inference process that Elasticsearch uses to evaluate uploaded machine learning models accepts a model operation that computes a memory address from an offset supplied inside the model, without validating that the offset stays within the bounds of the underlying storage. A user with the privileges required to upload and deploy a trained model can craft a model that reads and writes memory outside the intended allocation. The result is heap corruption that crashes the inference process, and, with sufficient control over the heap layout, could allow arbitrary code execution in the context of that process.

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Meta Information

Published
2026-08-13
Last Modified
2026-08-13
Generated
2026-08-14
AI Q&A
2026-08-13
EPSS Evaluated
N/A
NVD
CVE-2026-72642
EUVD
EUVD-2026-58287

Affected Vendors & Products

Showing 4 associated CPEs
Vendor Product Version / Range
elastic elasticsearch *
elastic elasticsearch From 8.19.0 (inc) to 8.19.19 (inc)
elastic elasticsearch From 9.4.0 (inc) to 9.4.4 (inc)
elastic elasticsearch From 9.5.0 (inc) to 9.5.1 (inc)

Helpful Resources

Exploitability

CWE
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KEV
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CWE ID Description
CWE-823 The product performs pointer arithmetic on a valid pointer, but it uses an offset that can point outside of the intended range of valid memory locations for the resulting pointer.

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Executive Summary

CVE-2026-72642 is a memory corruption vulnerability in Elasticsearch's machine learning inference process. It occurs when the system computes a memory address from an offset in a model without validating if the offset stays within the model's storage bounds. This allows users with model upload privileges to read and write memory outside the intended allocation, causing heap corruption, process crashes, and potentially arbitrary code execution.

Detection Guidance

Detecting this vulnerability requires checking Elasticsearch versions and machine learning node configurations. Use commands like 'curl -XGET http://localhost:9200' to verify version numbers. Inspect logs for heap corruption errors or inference process crashes. Ensure machine learning nodes are properly configured and monitor for unauthorized model uploads.

Impact Analysis

If exploited, this vulnerability could allow an attacker with sufficient privileges to execute arbitrary code on the Elasticsearch server, leading to data breaches, unauthorized access, or system compromise. It may also cause service disruptions due to process crashes. The impact depends on the attacker's goals and the server's configuration.

Compliance Impact

This vulnerability could lead to unauthorized data access or exfiltration, violating confidentiality requirements in GDPR and HIPAA. Organizations may face compliance violations, legal penalties, or reputational damage if exploited. Ensuring timely patching and implementing mitigations is critical to maintain compliance.

Mitigation Strategies

Immediately upgrade Elasticsearch to versions 8.19.20, 9.4.5, or 9.5.1. If upgrading is not possible, restrict model upload privileges to trusted administrators, avoid untrusted model sources, or disable machine learning features entirely if not required.

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