MEDIUM · 5.3

CVE-2026-73558

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 b...

Vulnerability 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.

CVSS Score

5.3

MEDIUM

CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:N/A:N
Attack Vector
NETWORK
Attack Complexity
HIGH
Privileges Required
NONE
User Interaction
REQUIRED
Scope
UNCHANGED
Confidentiality
HIGH
Integrity
NONE
Availability
NONE

Related Weaknesses (CWE)

References

FAQ

What is CVE-2026-73558?

CVE-2026-73558 is a vulnerability with a CVSS score of 5.3 (MEDIUM). 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 b...

How severe is CVE-2026-73558?

CVE-2026-73558 has been rated MEDIUM with a CVSS base score of 5.3/10. Review the CVSS metrics above for detailed severity breakdown.

Is there a patch for CVE-2026-73558?

Check the references section above for vendor advisories and patch information. Review vendor security bulletins for remediation guidance.