HIGHVulnerability

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.

Properties

severity
HIGH
score
8.8
epss_score
0.00336
cve_id
CVE-2026-72642
vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
published_at
2026-08-13T20:17:24.673
last_modified
2026-09-01T14:15:50.140
epss_percentile
0.26305

Related Entities (4)

ENRICHED_BY (1)

[Source]FIRST EPSS

HAS_WEAKNESS (1)

[Weakness]Use of Out-of-range Pointer Offset

DESCRIBED_BY (1)

[Source]NVD

AFFECTS_PRODUCT (1)

[Product]

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CVE-2026-72642 — Ninja Signal Threat Intelligence | Ninja Signal