CVE-2025-46570

LOW EPSS 16.1%
Published May 29, 20251y ago · Modified Jun 17, 20261w ago
2.6 CVSS 3.1
Low
Find Similar
Published May 29, 2025 1y ago
Last Modified Jun 17, 2026 1w ago

Description

vLLM is an inference and serving engine for large language models (LLMs). Prior to version 0.9.0, when a new prompt is processed, if the PageAttention mechanism finds a matching prefix chunk, the prefill process speeds up, which is reflected in the TTFT (Time to First Token). These timing differences caused by matching chunks are significant enough to be recognized and exploited. This issue has been patched in version 0.9.0.

CVSS Details

Base Score
2.6
Exploitability
1.2
Impact
1.4
Vector string
CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:L/I:N/A:N
Attack Vector Network
Attack Complexity High
Privileges Required Low
User Interaction Required
Scope Unchanged
Confidentiality Low
Integrity None
Availability None

Threat Intelligence

EPSS Exploit Probability
16.1% percentile
Exploit & Patch Status
No Known Exploit
Patch Available

Weaknesses 2

CWE-203
CWE-208

Affected Products 1

VendorProductVersionRange
vllmvllm* <0.9.0

References 3

  • github.com https://github.com/vllm-project/vllm/commit/77073c77bc2006eb80ea6d5128f076f5e6c6f54f
    Patch
  • github.com https://github.com/vllm-project/vllm/pull/17045
    Issue TrackingVendor Advisory
  • github.com https://github.com/vllm-project/vllm/security/advisories/GHSA-4qjh-9fv9-r85r
    Vendor Advisory

Remediation

  • github.com https://github.com/vllm-project/vllm/commit/77073c77bc2006eb80ea6d5128f076f5e6c6f54f
    Patch