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HIGH Received

CVE-2026-72642

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.

Published 13 Aug 2026, 20:17 UTC Last modified 13 Aug 2026, 20:17 UTC
01

Attack profile

The conditions required to exploit this vulnerability and its potential impact.

Attack vector Network
Attack complexity Low
Privileges required Low
User interaction None
Scope Unchanged
Confidentiality High
Integrity High
Availability High
Exploitability2.8
Impact5.9
02

Affected products

Product applicability statements supplied with the NVD record.

NVD has not published structured affected-product data for this record.
03

Weakness classification

CWE categories help security teams group the underlying software weakness.

04

Source references

External advisories, patches and technical reports attached to this CVE record.