GPU VulnDB

Database/AI/ML frameworks & serving

vLLM: forged multimodal uuid desynchronizes the processor cache and kills the serving instance

CVSS 7.1CVE-2026-114050AI/ML frameworks & servingcurated

Impact

vLLM trusts a client-supplied multimodal uuid as the cache identity and performs no consistency check on a hit, so a caller can make the P0 and P1 processor caches disagree about what a cached entry contains. The resulting token-placeholder mismatch is fatal: the whole serving process dies and stays down until something restarts it, taking every in-flight request and the model weights resident on the GPUs with it. On a GPU node this is expensive downtime rather than a simple crash - reloading a large model into HBM is minutes of unavailable accelerators, and a repeat request kills it again as soon as it is back. Any multimodal vLLM endpoint reachable by untrusted callers is a one-request denial of service against that node's GPUs.

Who can reach it

Anyone who can send an inference request to the vLLM OpenAI-compatible endpoint. The advisory describes the attacker as unauthenticated; the CVSS vector records PR:L, so treat it as reachable by any tenant or caller permitted to submit multimodal requests.

What to do

Upgrade to vLLM 0.31.0 or later and restart each serving replica; the model reload is the real cost, so stage it per replica behind the load balancer rather than all at once. Until patched, do not expose multimodal endpoints to untrusted callers, and make sure a supervisor restarts the engine automatically so a crash is minutes rather than hours.

References

Related entries

All AI/ML frameworks & serving entries

This entry is curated: imported from vendor advisories with machine assistance, not yet individually verified. Confirm against your vendor's advisory before acting, and report anything wrong.