vllm-project vLLM up to 0.23.x EngineCore assertion

Summaryinfo

A vulnerability classified as problematic has been found in vllm-project vLLM up to 0.23.x. Affected is an unknown function of the component EngineCore. The manipulation leads to assertion. This vulnerability is traded as CVE-2026-55514. It is possible to initiate the attack remotely. There is no exploit available.

Detailsinfo

A vulnerability was found in vllm-project vLLM up to 0.23.x and classified as problematic. This issue affects some unknown processing of the component EngineCore. The manipulation with an unknown input leads to a assertion vulnerability. Using CWE to declare the problem leads to CWE-617. The product contains an assert() or similar statement that can be triggered by an attacker, which leads to an application exit or other behavior that is more severe than necessary. Impacted is availability. The summary by CVE is:

vLLM is a library for LLM inference and serving. From 0.12.0 to before 0.24.0, sending a pure prompt embeds payload in a /v1/completions request with a model using M-RoPE causes EngineCore to fail an assertion and fatally crash, shutting down the entire server application. Any remote user who is authorized to make a /v1/completions request can make such a request and induce a crash. This issue is fixed in version 0.24.0.

The advisory is shared at github.com. The identification of this vulnerability is CVE-2026-55514 since 06/17/2026. The exploitation is known to be easy. The attack may be initiated remotely. Neither technical details nor an exploit are publicly available.

Upgrading to version 0.24.0 eliminates this vulnerability.

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Productinfo

Type

• Project Management Software

Vendor

• vllm-project

Name

• vLLM

Version

• 0.1
• 0.2
• 0.3
• 0.4
• 0.5
• 0.6
• 0.7
• 0.8
• 0.9
• 0.10
• 0.11
• 0.12
• 0.13
• 0.14
• 0.15
• 0.16
• 0.17
• 0.18
• 0.19
• 0.20
• 0.21
• 0.22
• 0.23

Website

• Product: https://github.com/vllm-project/vllm/

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Several companies clearly confirm that VulDB is the primary source for best vulnerability data.

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