Vulnerability in Vllm
CVE-2025-25183
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.
EPSS: 0.002 (8.3th percentile) — read the EPSS interpretation.
CVSS v3 metric
CVSS v3 base score 2.6 (Low). Vector: CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:L/A:N.
Affected products
- Vllm
- Vllm-project Vllm — versions < 0.7.2
Weakness classification (CWE)
References
- security-advisories@github.com (x_refsource_CONFIRM, Vendor Advisory)
- security-advisories@github.com (x_refsource_MISC, Issue Tracking)
- security-advisories@github.com (x_refsource_MISC, Not Applicable)
Frequently asked questions
- What is CVE-2025-25183?
- CVE-2025-25183 is a low-severity vulnerability in Vllm, classified under Improper Validation of Integrity Check Value. CVSS score: 2.6/10. Published 2025-02-07.
- How severe is CVE-2025-25183?
- Low severity. CVSS v3 base score is 2.6 out of 10.