Vulnerability in Elastic Elasticsearch
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 · last modified .
CVSS v3 metric
CVSS v3 base score 8.8 (High). Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H.
EPSS exploit prediction
EPSS: 0.006 (46.8th percentile), scored .
Very low probability of exploitation in the next 30 days; routine patching cadence is appropriate. 47th percentile — 46.8% of CVEs in the catalogue have a lower EPSS than this one. How to read EPSS.
EPSS over last 30 days · oldest: 0.003 · newest: 0.006 · change: +0.003
Affected products
- Elastic Elasticsearch — versions 8.19.0, 9.4.0, 9.5.0
Weakness classification (CWE)
References
Frequently asked questions
- What is CVE-2026-72642?
- CVE-2026-72642 is a high-severity vulnerability in Elastic Elasticsearch, classified under CWE-823. CVSS score: 8.8/10. Published 2026-08-13.
- How severe is CVE-2026-72642?
- High severity. CVSS v3 base score is 8.8 out of 10.