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CVE-2025-25183 – LLM vLLM Hash Collision Cache Manipulation

The following table lists the changes that have been made to the
CVE-2025-25183 vulnerability over time.

Vulnerability history details can be useful for understanding the evolution
of a vulnerability, and for identifying the most recent changes that may
impact the vulnerability’s severity, exploitability, or other characteristics.

  • New CVE Received
    by [email protected]

    Feb. 07, 2025

    Action Type Old Value New Value
    Added 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.
    Added CVSS V3.1 AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:L/A:N
    Added CWE CWE-354
    Added Reference https://github.com/python/cpython/commit/432117cd1f59c76d97da2eaff55a7d758301dbc7
    Added Reference https://github.com/vllm-project/vllm/pull/12621
    Added Reference https://github.com/vllm-project/vllm/security/advisories/GHSA-rm76-4mrf-v9r8
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