CVE-2026-93592High· 7.5▾ MidnightPoC availablevLLM 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. A single request with a nega…
▾ Midnight zone — Critical, or high with PoC / in-the-wild
impact 41.3 · likelihood 0.1 · exploitation 12
A public proof-of-concept already exists for this vulnerability — see Exploit availability below.
Stakeholder-Specific Vulnerability Categorization from CISA's ADP record at CVE.org: whether exploitation is observed, whether an attack can be automated, and how much of the system is at stake.
Exploit-prediction probability, daily snapshots since Sep 19.
Disclosure to exploitation, from the record and what we observed since indexing it.
Disclosed via NVD
Exploit / PoC code exists
0.4%
Last analysed / modified upstream
0.4% → 0.5%
vLLM 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. A single request with a negative token ID triggers a CUDA device-side assertion that poisons the GPU context, causing all subsequent requests to fail until the process restarts.
vllm < 0.28.0Upgrade past the affected range:
vllm 0.28.0Affected packages:
vllm < 0.28.0Patched in:
vllm 0.28.0Field changes observed since this record was first indexed.
Connected by shared product, vendor, weakness, or advisory.
CVE-2026-100650Medium· 6.5vLLM through 0.29.0 fetches and fully materializes remote or inline media before enforcing its documented media controls (the VLLM_MAX_AUDIO_CLIP_FILESIZE_MB compressed-audio size cap, default 25 MB, and the per-modality --limit-mm-per-p…
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-2026-69147Medium· 6.5vLLM is an inference and serving engine for large language models
CVE-2026-37237High· 7.5vLLM up to and including 0.17.0 allows remote attackers to cause a Denial of Service via memory exhaustion
CVE-2026-73556Medium· 5.3vLLM is an inference and serving engine for large language models
CVE-2026-48746Critical· 9.1vLLM is an inference and serving engine for large language models (LLMs)