Description
vLLM is an inference and serving engine for large language models. Prior to 0.27.0, an integer overflow in blockIdx.x * 2 * d in activation_kernels.cu can cause act_and_mul_kernel to consume another batched user's input, allowing a request processed in the same inference batch to receive a partial or complete copy of another user's inference result. This issue is fixed in version 0.27.0.
Published: 2026-08-13
Score: 5.3 Medium
EPSS: n/a
KEV: No
Impact: n/a
Action: n/a
AI Analysis

Impact

An integer overflow occurs in blockIdx.x * 2 * d within the activation_kernels.cu module of vLLM, leading the act_and_mul_kernel to read memory belonging to a different user’s batched request. This flaw allows a request processed in the same inference batch to obtain a partial or complete copy of another user’s inference output, resulting in confidentiality loss. The weakness is a classic integer overflow (CWE‑190).

Affected Systems

The vulnerability affects the vllm-project’s vLLM engine, specifically versions prior to 0.27.0. Users running 0.26.x or earlier are at risk; the issue is corrected in release v0.27.0.

Risk and Exploitability

The CVSS score of 5.3 indicates a moderate severity. EPSS is not available, and the vulnerability is not listed in CISA’s KEV catalog. Exposure requires that the attacker submit a request that shares an inference batch with a victim; no special privileges are needed beyond being able to submit a request. Consequently, the risk is primarily limited to environments where multiple users perform inference within the same batch, which is common in shared deployments.

Generated by OpenCVE AI on August 13, 2026 at 17:06 UTC.

Remediation

No vendor fix or workaround currently provided.

OpenCVE Recommended Actions

  • Upgrade vLLM to version 0.27.0 or later to eliminate the integer overflow bug.
  • Configure vLLM to isolate user requests, ensuring no two users share the same inference batch or use separate batch instances.
  • If upgrade cannot be performed immediately, restrict concurrent inference requests to a single user per batch to mitigate the risk of cross‑user data leakage.

Generated by OpenCVE AI on August 13, 2026 at 17:06 UTC.

Tracking

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Advisories

No advisories yet.

History

Thu, 13 Aug 2026 18:30:00 +0000

Type Values Removed Values Added
First Time appeared Vllm-project
Vllm-project vllm
Vendors & Products Vllm-project
Vllm-project vllm

Thu, 13 Aug 2026 15:15:00 +0000

Type Values Removed Values Added
Description vLLM is an inference and serving engine for large language models. Prior to 0.27.0, an integer overflow in blockIdx.x * 2 * d in activation_kernels.cu can cause act_and_mul_kernel to consume another batched user's input, allowing a request processed in the same inference batch to receive a partial or complete copy of another user's inference result. This issue is fixed in version 0.27.0.
Title vLLM: Cross-User Data Leak Vulnerability
Weaknesses CWE-190
References
Metrics cvssV3_1

{'score': 5.3, 'vector': 'CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:N/A:N'}


Subscriptions

Vllm-project Vllm
cve-icon MITRE

Status: PUBLISHED

Assigner: GitHub_M

Published:

Updated: 2026-08-13T15:38:40.181Z

Reserved: 2026-08-12T20:53:46.380Z

Link: CVE-2026-73558

cve-icon Vulnrichment

No data.

cve-icon NVD

Status : Received

Published: 2026-08-13T15:20:18.220

Modified: 2026-08-13T16:19:05.760

Link: CVE-2026-73558

cve-icon Redhat

No data.

cve-icon OpenCVE Enrichment

Updated: 2026-08-13T18:15:04Z

Weaknesses
  • CWE-190

    Integer Overflow or Wraparound