Vulnerability · Published Jul 6, 2026 · Assigned by GitHub_M

CVE-2026-54234vLLM: Remote DoS in vLLM via Invalid Recovered Token Reinjection

High 7.5

In plain English

A high-severity improper input validation in vllm from vllm-project. Proof-of-concept exploit code is public. The chance it is exploited in the next 30 days is estimated at 0.6% (higher than 50% of all known vulnerabilities). Fixed versions are available - upgrade the affected package.

Severity (CVSS 3.1)7.5High
Exploit odds (30 days)0.6%top 50.3% of all CVEs
Exploited in the wildNo reportsCISA SSVC: poc
Attack toolingNoneno public tooling known

Official description

vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Prior to 0.24.0, a frontend-legal multi-request speculative decoding workload can cause the rejection sampler to produce a recovered token equal to the model vocabulary size boundary value, which is then converted to negative one when the engine selects the next live token for a request and is written back into the drafter's input ids; that out-of-vocabulary value is later consumed by the model's embedding and attention path and crashes the engine worker with a GPU device-side assertion. The same triggering request sequence is reachable through the public gRPC Generate and Abort endpoints, so a remote client that can send generation requests can crash the shared engine worker, aborting concurrent requests and causing a service-wide denial of service for other clients of the deployment until the worker is restarted. This issue is fixed in version 0.24.0.

Affected packages & fixed versions

EcosystemPackageFixed inAdvisory
PyPIvllm0.24.0GHSA-8wr5-jm2h-8r4f
PyPIvllm0.24.0PYSEC-2026-3542

Affected products (as reported)

VendorProductVersions
vllm-project vllm < 0.24.0

Weakness: CWE-20, CWE-1284 · Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

References