vLLM is an inference and serving engine for large language models.
vLLM is an inference and serving engine for large language models. Prior to 0.28.0, the default mirrored multimodal LRU cache can commit a media hash in the frontend sender cache during multimodal rendering and before engine admission, while the engine receiver cache never receives the payload if that request is rejected. A later request reusing the same media hash causes MultiModalProcessorSenderCache to send no payload and MultiModalReceiverCache to reach an assertion with the message "Expected a cached item," producing a shared-service availability failure. This issue is fixed in version 0.
Read at NIST National Vulnerability Database (CVE API 2.0)
- Product
- AI / LLM tooling
- CVSS
- 6.5
- Fix
- available
- Exposure class
- AI infrastructure
Why it ranks 13 (Routine)
- CVSS 6.5 medium
- Product class: AI infrastructure
- Fix available
- Recency: items published within 24 hours gain 15, within 72 hours 6, within 7 days 2.
Links
- NIST National Vulnerability Database (CVE API 2.0) (nvd.nist.gov)
- CVE-2026-105753 on this site · NVD · CVE.org · Vulnpedia
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