FKIE_CVE-2026-46432
Vulnerability from fkie_nvd - Published: 2026-06-10 00:16 - Updated: 2026-07-23 09:10
Severity
Summary
LMDeploy is a toolkit for compressing, deploying, and serving large language models. In versions 0.12.3 and prior, LMDeploy is vulnerable to arbitrary code execution through hardcoded "trust_remote_code=True" in multiple HuggingFace model-loading call sites. At time of publication, there are no publicly available patches.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"product": "lmdeploy",
"vendor": "InternLM",
"versions": [
{
"status": "affected",
"version": "\u003c= 0.12.3"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "LMDeploy is a toolkit for compressing, deploying, and serving large language models. In versions 0.12.3 and prior, LMDeploy is vulnerable to arbitrary code execution through hardcoded \"trust_remote_code=True\" in multiple HuggingFace model-loading call sites. At time of publication, there are no publicly available patches."
},
{
"lang": "es",
"value": "LMDeploy es un conjunto de herramientas para comprimir, desplegar y servir grandes modelos de lenguaje. En las versiones 0.12.3 y anteriores, LMDeploy es vulnerable a la ejecuci\u00f3n de c\u00f3digo arbitrario mediante el valor \u0027hardcoded\u0027 \u0027trust_remote_code=True\u0027 en m\u00faltiples sitios de llamada de carga de modelos de HuggingFace. En el momento de la publicaci\u00f3n, no hay parches disponibles p\u00fablicamente."
}
],
"id": "CVE-2026-46432",
"lastModified": "2026-07-23T09:10:00.113",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "LOCAL",
"availabilityImpact": "HIGH",
"baseScore": 7.8,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"exploitabilityScore": 1.8,
"impactScore": 5.9,
"source": "security-advisories@github.com",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-46432",
"options": [
{
"exploitation": "poc"
},
{
"automatable": "no"
},
{
"technicalImpact": "total"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-06-10T00:00:00+00:00",
"version": "2.0.3"
}
}
]
},
"published": "2026-06-10T00:16:53.557",
"references": [
{
"source": "security-advisories@github.com",
"url": "https://github.com/InternLM/lmdeploy/security/advisories/GHSA-m549-qq94-fvhg"
},
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"url": "https://github.com/InternLM/lmdeploy/security/advisories/GHSA-m549-qq94-fvhg"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Deferred",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-94"
}
],
"source": "security-advisories@github.com",
"type": "Secondary"
}
]
}
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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.
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