CVE-2026-105758 (GCVE-0-2026-105758)
Vulnerability from cvelistv5 – Published: 2026-10-05 22:54 – Updated: 2026-10-05 22:54
VLAI
EPSS
VEX
Title
vLLM: Qwen2-VL / Qwen3-VL video samplers bound on request-controlled max_frames, which the num_frames ceiling does not reach
Summary
vLLM is an inference and serving engine for large language models. From 0.24.0 until 0.30.0, the Qwen2VLVideoBackend and Qwen3VLVideoBackend classes accept request-level values for the media_io_kwargs.video.max_frames and media_io_kwargs.video.fps fields without enforcing server-side ceilings. An unauthenticated caller can submit these values to the /tokenize endpoint, causing the sampler to decode every frame selected from attacker-controlled video input, consume disproportionate frontend memory, and potentially terminate the API process before scheduling or admission control. The Rust frontend is not affected because it rejects the media_io_kwargs field. This issue is fixed in version 0.30.0.
Severity
5.3 (Medium)
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://github.com/vllm-project/vllm/security/adv… | x_refsource_CONFIRM |
| https://github.com/vllm-project/vllm/pull/56729 | x_refsource_MISC |
| https://github.com/vllm-project/vllm/commit/ea723… | x_refsource_MISC |
| https://github.com/vllm-project/vllm/releases/tag… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| vllm-project | vllm |
Affected:
>= 0.24.0, < 0.30.0
|
guessed |
{
"containers": {
"cna": {
"affected": [
{
"product": "vllm",
"vendor": "vllm-project",
"versions": [
{
"status": "affected",
"version": "\u003e= 0.24.0, \u003c 0.30.0"
}
]
}
],
"descriptions": [
{
"lang": "en",
"value": "vLLM is an inference and serving engine for large language models. From 0.24.0 until 0.30.0, the Qwen2VLVideoBackend and Qwen3VLVideoBackend classes accept request-level values for the media_io_kwargs.video.max_frames and media_io_kwargs.video.fps fields without enforcing server-side ceilings. An unauthenticated caller can submit these values to the /tokenize endpoint, causing the sampler to decode every frame selected from attacker-controlled video input, consume disproportionate frontend memory, and potentially terminate the API process before scheduling or admission control. The Rust frontend is not affected because it rejects the media_io_kwargs field. This issue is fixed in version 0.30.0."
}
],
"metrics": [
{
"cvssV3_1": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "LOW",
"baseScore": 5.3,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L",
"version": "3.1"
}
}
],
"problemTypes": [
{
"descriptions": [
{
"cweId": "CWE-770",
"description": "CWE-770: Allocation of Resources Without Limits or Throttling",
"lang": "en",
"type": "CWE"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2026-10-05T22:54:53.846Z",
"orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
"shortName": "GitHub_M"
},
"references": [
{
"name": "https://github.com/vllm-project/vllm/security/advisories/GHSA-x6mc-67gf-chw4",
"tags": [
"x_refsource_CONFIRM"
],
"url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-x6mc-67gf-chw4"
},
{
"name": "https://github.com/vllm-project/vllm/pull/56729",
"tags": [
"x_refsource_MISC"
],
"url": "https://github.com/vllm-project/vllm/pull/56729"
},
{
"name": "https://github.com/vllm-project/vllm/commit/ea723c81c3ea26425cb69503a5d5e90822a04a45",
"tags": [
"x_refsource_MISC"
],
"url": "https://github.com/vllm-project/vllm/commit/ea723c81c3ea26425cb69503a5d5e90822a04a45"
},
{
"name": "https://github.com/vllm-project/vllm/releases/tag/v0.30.0",
"tags": [
"x_refsource_MISC"
],
"url": "https://github.com/vllm-project/vllm/releases/tag/v0.30.0"
}
],
"source": {
"advisory": "GHSA-x6mc-67gf-chw4",
"discovery": "UNKNOWN"
},
"title": "vLLM: Qwen2-VL / Qwen3-VL video samplers bound on request-controlled max_frames, which the num_frames ceiling does not reach"
}
},
"cveMetadata": {
"assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
"assignerShortName": "GitHub_M",
"cveId": "CVE-2026-105758",
"datePublished": "2026-10-05T22:54:53.846Z",
"dateReserved": "2026-10-05T19:11:07.947Z",
"dateUpdated": "2026-10-05T22:54:53.846Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.2",
"vulnerability-lookup:meta": {
"epss": {
"cve": "CVE-2026-105758",
"date": "2026-10-06",
"epss": "0.00308",
"percentile": "0.21552"
},
"nvd": {
"cve": {
"affected": [
{
"affectedData": [
{
"product": "vllm",
"vendor": "vllm-project",
"versions": [
{
"status": "affected",
"version": "\u003e= 0.24.0, \u003c 0.30.0"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "vLLM is an inference and serving engine for large language models. From 0.24.0 until 0.30.0, the Qwen2VLVideoBackend and Qwen3VLVideoBackend classes accept request-level values for the media_io_kwargs.video.max_frames and media_io_kwargs.video.fps fields without enforcing server-side ceilings. An unauthenticated caller can submit these values to the /tokenize endpoint, causing the sampler to decode every frame selected from attacker-controlled video input, consume disproportionate frontend memory, and potentially terminate the API process before scheduling or admission control. The Rust frontend is not affected because it rejects the media_io_kwargs field. This issue is fixed in version 0.30.0."
}
],
"id": "CVE-2026-105758",
"lastModified": "2026-10-06T14:59:48.280",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "LOW",
"baseScore": 5.3,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 1.4,
"source": "security-advisories@github.com",
"type": "Secondary"
}
]
},
"published": "2026-10-05T23:17:02.610",
"references": [
{
"source": "security-advisories@github.com",
"url": "https://github.com/vllm-project/vllm/commit/ea723c81c3ea26425cb69503a5d5e90822a04a45"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/vllm-project/vllm/pull/56729"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/vllm-project/vllm/releases/tag/v0.30.0"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-x6mc-67gf-chw4"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Undergoing Analysis",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-770"
}
],
"source": "security-advisories@github.com",
"type": "Primary"
}
]
}
},
"redhat_vex": {
"aggregate_severity": "Moderate",
"current_release_date": "2026-10-06T00:11:39+00:00",
"cve": "CVE-2026-105758",
"id": "CVE-2026-105758",
"initial_release_date": "2026-10-05T22:54:53.846000+00:00",
"product_status:known_affected": "27",
"source": "Red Hat CSAF VEX",
"status": "final",
"title": "vllm: vllm: Denial of Service via unbounded video frame parameters",
"url": "https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-105758.json",
"version": "3"
}
}
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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