Package Instance

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{
    "url": "http://public2.vulnerablecode.io/api/packages/49120?format=api",
    "purl": "pkg:pypi/vllm@0.19.0",
    "type": "pypi",
    "namespace": "",
    "name": "vllm",
    "version": "0.19.0",
    "qualifiers": {},
    "subpath": "",
    "is_vulnerable": true,
    "next_non_vulnerable_version": "0.20.0",
    "latest_non_vulnerable_version": "0.20.0",
    "affected_by_vulnerabilities": [
        {
            "url": "http://public2.vulnerablecode.io/api/vulnerabilities/37334?format=api",
            "vulnerability_id": "VCID-jzjy-kj6h-4bas",
            "summary": "vLLM is an inference and serving engine for large language models (LLMs). From  to before 0.20.0, the extract_hidden_states speculative decoding proposer in vLLM returns a tensor with an incorrect shape after the first decode step, causing a RuntimeError that crashes the EngineCore process. The crash is triggered when any request in the batch uses sampling penalty parameters (repetition_penalty, frequency_penalty, or presence_penalty). A single request with a penalty parameter (e.g., \"repetition_penalty\": 1.1) is sufficient to crash the server. This vulnerability is fixed in 0.20.0.",
            "references": [
                {
                    "reference_url": "https://github.com/vllm-project/vllm/pull/38610",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [
                        {
                            "value": "6.5",
                            "scoring_system": "cvssv3.1",
                            "scoring_elements": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H"
                        }
                    ],
                    "url": "https://github.com/vllm-project/vllm/pull/38610"
                },
                {
                    "reference_url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-83vm-p52w-f9pw",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [
                        {
                            "value": "6.5",
                            "scoring_system": "cvssv3.1",
                            "scoring_elements": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H"
                        }
                    ],
                    "url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-83vm-p52w-f9pw"
                }
            ],
            "fixed_packages": [
                {
                    "url": "http://public2.vulnerablecode.io/api/packages/50315?format=api",
                    "purl": "pkg:pypi/vllm@0.20.0",
                    "is_vulnerable": false,
                    "affected_by_vulnerabilities": [],
                    "resource_url": "http://public2.vulnerablecode.io/packages/pkg:pypi/vllm@0.20.0"
                }
            ],
            "aliases": [
                "CVE-2026-44223",
                "GHSA-83vm-p52w-f9pw",
                "PYSEC-2026-145"
            ],
            "risk_score": null,
            "exploitability": null,
            "weighted_severity": null,
            "resource_url": "http://public2.vulnerablecode.io/vulnerabilities/VCID-jzjy-kj6h-4bas"
        }
    ],
    "fixing_vulnerabilities": [
        {
            "url": "http://public2.vulnerablecode.io/api/vulnerabilities/37260?format=api",
            "vulnerability_id": "VCID-za3a-c9m1-jqgz",
            "summary": "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.",
            "references": [
                {
                    "reference_url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-pq5c-rjhq-qp7p",
                    "reference_id": "",
                    "reference_type": "",
                    "scores": [
                        {
                            "value": "6.5",
                            "scoring_system": "cvssv3.1",
                            "scoring_elements": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H"
                        }
                    ],
                    "url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-pq5c-rjhq-qp7p"
                }
            ],
            "fixed_packages": [
                {
                    "url": "http://public2.vulnerablecode.io/api/packages/49120?format=api",
                    "purl": "pkg:pypi/vllm@0.19.0",
                    "is_vulnerable": true,
                    "affected_by_vulnerabilities": [
                        {
                            "vulnerability": "VCID-jzjy-kj6h-4bas"
                        }
                    ],
                    "resource_url": "http://public2.vulnerablecode.io/packages/pkg:pypi/vllm@0.19.0"
                }
            ],
            "aliases": [
                "CVE-2026-34755",
                "GHSA-pq5c-rjhq-qp7p",
                "PYSEC-2026-144"
            ],
            "risk_score": null,
            "exploitability": null,
            "weighted_severity": null,
            "resource_url": "http://public2.vulnerablecode.io/vulnerabilities/VCID-za3a-c9m1-jqgz"
        }
    ],
    "risk_score": null,
    "resource_url": "http://public2.vulnerablecode.io/packages/pkg:pypi/vllm@0.19.0"
}