HighVulnerabilityLLM-specific

CVE-2026-90553: vLLM remote code execution in LlavaOnevision2 processor loader

Source: NVD(opens in a new tab)
Identifier: CVE-2026-90553
Published: September 12, 2026
Record updated: October 9, 2026

Known exploitation: Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
EPSS: 0.3%

Summary

vLLM before 0.28.0 contains a remote code execution flaw in the LlavaOnevision2 processor loader. The loader ignores the trust_remote_code parameter when it loads remote processor classes, so an attacker who crafts a malicious model with arbitrary code in processing_llava_onevision2.py can run that code with vLLM process authority, even when trust_remote_code is set to False.

Mitigation

The source does not state a fix yet. Check the original advisory for updates.

Details

Scores and exploitation

CVSS score: 7.8(high)
CVSS vector: CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
Attack vector: local
Attack complexity: low
Privileges required: none
User interaction: required
EPSS: 0.3%Estimated probability that this CVE is exploited in the next 30 days, from the FIRST Exploit Prediction Scoring System. Read on November 4, 2026.
Disclosure date: September 12, 2026

Weaknesses and techniques

Weakness (CWE): CWE-94
Attack pattern (CAPEC): CAPEC-242
AI threat technique (MITRE ATLAS): AML.T0010

Classification

Attack type: Supply chain
Attack sophistication: Moderate
AI component targeted: Inference
Impact: Confidentiality,
Integrity,
Availability
Labels: security

How this record was produced

Summaries, mitigations and labels on this page are generated automatically from the source. The linked source is authoritative. The source gives this advisory a description and no title, so the title above is a headline generated from the source text.

Original source: https://nvd.nist.gov/vuln/detail/CVE-2026-90553

First tracked: September 12, 2026 at 02:07 PM ET, from NVD/CVE Database

Classifier: claude-haiku-5-5, prompt v4

Classifier confidence: 95% (self-assessed)

Topics

Inference infrastructure

Summary

Mitigation

Topics

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