vLLM using built-in hash() from Python 3.12 leads to predictable hash collisions in vLLM prefix cache (vllm-project vllm)

CVE-2025-25183
LOW 2.6

At a glance

Source
NVD
EPSS
EPSS 0.19 % · percentile 9 ()
State
PUBLISHED
Published
Updated
Assigner
GitHub_M
NVD status
Analyzed

Description

vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Maliciously constructed statements can lead to hash collisions, resulting in cache reuse, which can interfere with subsequent responses and cause unintended behavior. Prefix caching makes use of Python's built-in hash() function. As of Python 3.12, the behavior of hash(None) has changed to be a predictable constant value. This makes it more feasible that someone could try exploit hash collisions. The impact of a collision would be using cache that was generated using different content. Given knowledge of prompts in use and predictable hashing behavior, someone could intentionally populate the cache using a prompt known to collide with another prompt in use. This issue has been addressed in version 0.7.2 and all users are advised to upgrade. There are no known workarounds for this vulnerability.

Weaknesses (CWE)

  • CWE-354 — Improper Validation of Integrity Check Value

References

Scores

VersionScoreVectorScored by
CVSS 3.1LOW 2.6CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:L/A:NGitHub_M
CVSS 3.1LOW 2.6CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:L/A:NNVD · security-advisories@github.com (Secondary)

Advisories

European references

CERT-FR advisories

Affected configurations (NVD CPE)

Affected products

ProductVersions
vllm-project · vllmaffected < 0.7.2

Sources

SourceLicence
CVE List (CVEProject cvelistV5)CVE Program Terms of Use
EPSS (FIRST.org)FIRST — attribution requested
ENISA EUVDENISA — reproduction authorised, source acknowledged
CERT-FR (ANSSI)Licence Ouverte / Etalab 2.0
NVD (NIST) via fkie-cad/nvd-json-data-feedsPublic domain — this product uses data from the NVD API but is not endorsed or certified by the NVD