CVE-2026-72642
Medium
Elevated severity or exploit probability.
CVSS base
8.8
HIGH
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
EPSS — probability of exploitation (30 days)
0.3%
27.1th percentile
CISA KEV
Not listed
Weakness / dates
CWE-823
Published 2026-08-13 · modified 2026-09-01
CVSS breakdown
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
| Attack Vector | N | Network |
| Attack Complexity | L | Low |
| Privileges Required | L | Low |
| User Interaction | N | None |
| Scope | U | Unchanged |
| Confidentiality | H | High |
| Integrity | H | High |
| Availability | H | High |
Timeline
- 2026-08-13 — Published (NVD)
- 2026-09-01 — Last modified (NVD)
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.