CVE-2026-105753Medium· 6.5▾ SunlitvLLM 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, w…
▾ Sunlit zone — Low / medium · no exploitation signal
impact 35.8 · likelihood 0 · exploitation 0
Need a working PoC? Pro members can cast a request and our team develops one — it lands right here.
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 0.28.0.
Refer to the linked advisories for vendor-supplied fixes and affected version ranges.
Affected packages:
vllm < 0.28.0Patched in:
vllm 0.28.0Connected by shared product, vendor, weakness, or advisory.
CVE-2026-105754Medium· 6.5vLLM is an inference and serving engine for large language models
CVE-2026-94623High· 7.5vLLM through 0.29.0 contains a denial of service vulnerability in the NIXL connector's prefix caching implementation that fails to properly validate block counts across multi-prompt completion requests in prefill/decode disaggregated dep…
CVE-2026-93592High· 7.5vLLM versions before 0.28.0 fail to validate the lower bound of token IDs in the /v1/embeddings and /pooling endpoints, allowing unauthenticated attackers to crash the engine by submitting negative token IDs
CVE-2026-100654Medium· 6.5vLLM before 0.29.0 accepts user-controlled stop_token_ids on the OpenAI-compatible POST /v1/completions and POST /v1/chat/completions endpoints but validates only that the values are integers, not that each token id is within the model v…
CVE-2026-105760Medium· 5.3vLLM is an inference and serving engine for large language models
CVE-2026-105758Medium· 5.3vLLM is an inference and serving engine for large language models