Improper input validation in Vllm-Project Vllm
CVE-2026-100652
vLLM versions 0.22.0 through 0.23.0 fail to validate stop_token_ids against vocabulary bounds in Rust HTTP and gRPC frontends, allowing out-of-vocabulary token IDs to reach MinTokensLogitsProcessor. Attackers can submit requests with min_tokens greater than zero and out-of-vocabulary stop_token_ids to trigger CUDA tensor indexing failures that leave EngineCore in a fatal state requiring service restart.
Vulnerability class: Drupalgeddon 2 (CVE-2018-7600)
Published .
CVSS v3 metric
CVSS v3 base score 5.9 (Medium). Vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H.
EPSS exploit prediction
No EPSS score from FIRST.org yet. New CVEs usually get one within a few days; no score means no signal yet, not low risk. How EPSS works.
Affected products
Weakness classification (CWE)
References
- github.com/vllm-project/vllm/security/advisories/GHSA-qff2-492f-9fm4 (vendor-advisory)
- www.vulncheck.com/advisories/vllm-0.22.0-through-0.23.0-denial-of-service-via-s… (third-party-advisory)
Frequently asked questions
- What is CVE-2026-100652?
- CVE-2026-100652 is a medium-severity vulnerability in Vllm-Project Vllm, classified under Improper Input Validation. CVSS score: 5.9/10. Published 2026-09-26.
- How severe is CVE-2026-100652?
- Medium severity. CVSS v3 base score is 5.9 out of 10.