4.2
CVE-2025-46722
- EPSS 0.07%
- Veröffentlicht 29.05.2025 16:36:12
- Zuletzt bearbeitet 30.05.2025 16:31:03
- Quelle security-advisories@github.com
- CVE-Watchlists
- Unerledigt
vLLM is an inference and serving engine for large language models (LLMs). In versions starting from 0.7.0 to before 0.9.0, in the file vllm/multimodal/hasher.py, the MultiModalHasher class has a security and data integrity issue in its image hashing method. Currently, it serializes PIL.Image.Image objects using only obj.tobytes(), which returns only the raw pixel data, without including metadata such as the image’s shape (width, height, mode). As a result, two images of different sizes (e.g., 30x100 and 100x30) with the same pixel byte sequence could generate the same hash value. This may lead to hash collisions, incorrect cache hits, and even data leakage or security risks. This issue has been patched in version 0.9.0.
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Produkt
vllm
Version
>= 0.7.0, < 0.9.0
Status
affected
| Typ | Quelle | Score | Percentile |
|---|---|---|---|
| EPSS | FIRST.org | 0.07% | 0.21 |
| Quelle | Base Score | Exploit Score | Impact Score | Vector String |
|---|---|---|---|---|
| security-advisories@github.com | 4.2 | 1.6 | 2.5 |
CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:L/I:N/A:L
|
CWE-1023 Incomplete Comparison with Missing Factors
The product performs a comparison between entities that must consider multiple factors or characteristics of each entity, but the comparison does not include one or more of these factors.
CWE-1288 Improper Validation of Consistency within Input
The product receives a complex input with multiple elements or fields that must be consistent with each other, but it does not validate or incorrectly validates that the input is actually consistent.