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Elasticsearch CVE-2026-72649

| EUVDEUVD-2026-69562 HIGH
Deserialization of Untrusted Data (CWE-502)
2026-09-01 elastic GHSA-5fhg-p2p3-wmjf
8.8
CVSS 3.1 · Vendor: elastic
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Severity by source

Vendor (elastic) PRIMARY
8.8 HIGH
AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
vuln.today AI
8.8 HIGH

Network-reachable ML API, low complexity once authenticated; PR:L reflects required ML model-deployment role, not arbitrary user access; full CIA from OS-level code execution.

3.1 AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
4.0 AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

Primary rating from Vendor (elastic).

CVSS VectorVendor: elastic

Attack Vector
Network
Attack Complexity
Low
Privileges Required
Low
User Interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

Lifecycle Timeline

2
Analysis Generated
Sep 01, 2026 - 19:53 vuln.today
CVE Published
Sep 01, 2026 - 19:20 cve.org
HIGH 8.8

DescriptionCVE.org

Deserialization of Untrusted Data (CWE-502) in the Elasticsearch machine learning component can lead to remote code execution via Object Injection (CAPEC-586). A specially crafted trained model artifact could cause attacker-controlled logic to execute with a materially broader system-call surface than intended. Exploitation requires an authenticated user with sufficient privileges to create and deploy trained models.

AnalysisAI

Remote code execution in Elasticsearch's machine learning component allows an authenticated user with ML model deployment privileges to execute arbitrary attacker-controlled logic on the Elasticsearch host node by supplying a crafted trained model artifact. The flaw stems from unsafe deserialization (CWE-502) of model artifact data during the ML inference loading process, granting the attacker a broader OS system-call surface than the ML subsystem is intended to expose. …

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Attack ChainAIDerived

Hypothetical attack flow derived from CVE metadata

Recon
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Exploit
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C2
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Execute
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Vulnerability AssessmentAI

Exploitation Exploitation requires a valid Elasticsearch session authenticated with the machine_learning_admin role, or a custom role granting the cluster:admin/xpack/ml/trained_models/put privilege (or equivalent trained-model write access). … Additional conditions and limiting factors are described in the full assessment.
Risk Assessment The CVSS 8.8 vector (AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H) correctly captures the network-accessible attack surface and full CIA impact, but PR:L warrants careful interpretation: exploitation requires not merely any authenticated Elasticsearch user, but one holding the machine_learning_admin role or an equivalent custom role with trained-model write permissions - a meaningfully narrowed attacker pool compared to generic PR:L. … Full risk analysis with EPSS, KEV, and SSVC signal comparison available after sign-in.
Exploit Scenario Full exploit scenario with step-by-step reproduction available after sign-in.
Remediation Upgrade to Elasticsearch 8.19.2, 9.4.5, or 9.5.1 as directed by ESA-2026-114 (https://discuss.elastic.co/t/elasticsearch-8-19-20-9-4-5-9-5-1-security-update-esa-2026-114/390087). … Detailed patch versions, workarounds, and compensating controls in full report.

Recommended ActionAI

Within 24 hours, identify all Elasticsearch instances in production and development environments and document their current versions. …

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Threat intelligence, references, and detailed analysis are available after sign-in.

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CVE-2026-72649 vulnerability details – vuln.today

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