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| purl | pkg:pypi/vllm@0.9.2 |
| Vulnerability | Summary | Fixed by |
|---|---|---|
|
VCID-nctw-rz8h-f3af
Aliases: CVE-2026-22773 GHSA-grg2-63fw-f2qr PYSEC-2026-143 |
vLLM is an inference and serving engine for large language models (LLMs). In versions from 0.6.4 to before 0.12.0, users can crash the vLLM engine serving multimodal models that use the Idefics3 vision model implementation by sending a specially crafted 1x1 pixel image. This causes a tensor dimension mismatch that results in an unhandled runtime error, leading to complete server termination. This issue has been patched in version 0.12.0. |
Affected by 1 other vulnerability. |
|
VCID-za3a-c9m1-jqgz
Aliases: CVE-2026-34755 GHSA-pq5c-rjhq-qp7p PYSEC-2026-144 |
vLLM is an inference and serving engine for large language models (LLMs). From 0.7.0 to before 0.19.0, the VideoMediaIO.load_base64() method at vllm/multimodal/media/video.py splits video/jpeg data URLs by comma to extract individual JPEG frames, but does not enforce a frame count limit. The num_frames parameter (default: 32), which is enforced by the load_bytes() code path, is completely bypassed in the video/jpeg base64 path. An attacker can send a single API request containing thousands of comma-separated base64-encoded JPEG frames, causing the server to decode all frames into memory and crash with OOM. This vulnerability is fixed in 0.19.0. |
Affected by 1 other vulnerability. |
| Vulnerability | Summary | Aliases |
|---|---|---|
| This package is not known to fix vulnerabilities. | ||
| Date | Actor | Action | Vulnerability | Source | VulnerableCode Version |
|---|---|---|---|---|---|
| 2026-06-02T04:24:27.956967+00:00 | Pypa Importer | Affected by | VCID-za3a-c9m1-jqgz | https://github.com/pypa/advisory-database/blob/main/vulns/vllm/PYSEC-2026-144.yaml | 38.6.0 |
| 2026-06-02T04:23:39.323835+00:00 | Pypa Importer | Affected by | VCID-nctw-rz8h-f3af | https://github.com/pypa/advisory-database/blob/main/vulns/vllm/PYSEC-2026-143.yaml | 38.6.0 |