| ID |
CVE-2025-46560
|
| Sažetak |
vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Versions starting from 0.8.0 and prior to 0.8.5 are affected by a critical performance vulnerability in the input preprocessing logic of the multimodal tokenizer. The code dynamically replaces placeholder tokens (e.g., <|audio_|>, <|image_|>) with repeated tokens based on precomputed lengths. Due to inefficient list concatenation operations, the algorithm exhibits quadratic time complexity (O(n²)), allowing malicious actors to trigger resource exhaustion via specially crafted inputs. This issue has been patched in version 0.8.5. |
| Reference |
|
| CVSS |
| Base: | 6.5 |
| Impact: | 3.6 |
| Exploitability: | 2.8 |
|
| Pristup |
| Vektor | Složenost | Autentikacija |
| NETWORK |
LOW |
LOW |
|
| Impact |
| Povjerljivost | Cjelovitost | Dostupnost |
| NONE |
NONE |
HIGH |
|
| CVSS vektor |
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H |
| Zadnje važnije ažuriranje |
02-05-2025 - 13:53 |
| Objavljeno |
30-04-2025 - 01:15 |
