FKIE_CVE-2026-42271
Vulnerability from fkie_nvd - Published: 2026-05-08 04:16 - Updated: 2026-10-26 20:10
Severity
8.8 (High) - CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
8.8 (High) - CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
8.8 (High) - CVSS:3.1/
Summary
LiteLLM is a proxy server (AI Gateway) to call LLM APIs in OpenAI (or native) format. From version 1.74.2 to before version 1.83.7, two endpoints used to preview an MCP server before saving it — POST /mcp-rest/test/connection and POST /mcp-rest/test/tools/list — accepted a full server configuration in the request body, including the command, args, and env fields used by the stdio transport. When called with a stdio configuration, the endpoints attempted to connect, which spawned the supplied command as a subprocess on the proxy host with the privileges of the proxy process. The endpoints were gated only by a valid proxy API key, with no role check. Any authenticated user — including holders of low-privilege internal-user keys — could therefore run arbitrary commands on the host. This issue has been patched in version 1.83.7.
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| litellm | litellm | * | |
| redhat | openshift_ai | * | |
| redhat | openshift_ai | * | |
| redhat | openshift_ai | 3.4 |
{
"affected": [
{
"affectedData": [
{
"product": "litellm",
"vendor": "BerriAI",
"versions": [
{
"status": "affected",
"version": "\u003e= 1.74.2, \u003c 1.83.7"
}
]
}
],
"source": "security-advisories@github.com"
},
{
"affectedData": [
{
"collectionURL": "https://catalog.redhat.com/software/containers/",
"cpes": [
"cpe:/a:redhat:openshift_ai:2.25::el9"
],
"defaultStatus": "affected",
"packageName": "rhoai/odh-llama-stack-core-rhel9",
"product": "Red Hat OpenShift AI 2.25",
"vendor": "Red Hat",
"versions": [
{
"lessThan": "*",
"status": "unaffected",
"version": "1781826406",
"versionType": "rpm"
}
]
},
{
"collectionURL": "https://catalog.redhat.com/software/containers/",
"cpes": [
"cpe:/a:redhat:openshift_ai:3.3::el9"
],
"defaultStatus": "affected",
"packageName": "rhoai/odh-llama-stack-core-rhel9",
"product": "Red Hat OpenShift AI 3.3",
"vendor": "Red Hat",
"versions": [
{
"lessThan": "*",
"status": "unaffected",
"version": "1782310008",
"versionType": "rpm"
}
]
},
{
"collectionURL": "https://catalog.redhat.com/software/containers/",
"cpes": [
"cpe:/a:redhat:openshift_ai:3.4::el9"
],
"defaultStatus": "affected",
"packageName": "rhoai/odh-trustyai-garak-lls-provider-dsp-rhel9",
"product": "Red Hat OpenShift AI 3.4",
"vendor": "Red Hat",
"versions": [
{
"lessThan": "*",
"status": "unaffected",
"version": "1781622627",
"versionType": "rpm"
}
]
},
{
"collectionURL": "https://access.redhat.com/downloads/content/package-browser/",
"cpes": [
"cpe:/a:redhat:exploit_intelligence:0"
],
"defaultStatus": "unaffected",
"packageName": "exploit-intelligence-tech-preview/vulnerability-analysis-rhel9",
"product": "Exploit Intelligence",
"vendor": "Red Hat"
},
{
"collectionURL": "https://access.redhat.com/downloads/content/package-browser/",
"cpes": [
"cpe:/a:redhat:ansible_automation_platform:2"
],
"defaultStatus": "unaffected",
"packageName": "ansible-automation-platform-26/lightspeed-chatbot-rhel9",
"product": "Red Hat Ansible Automation Platform 2",
"vendor": "Red Hat"
},
{
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"cpes": [
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],
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"packageName": "ansible-automation-platform-27/lightspeed-chatbot-rhel9",
"product": "Red Hat Ansible Automation Platform 2",
"vendor": "Red Hat"
},
{
"collectionURL": "https://access.redhat.com/downloads/content/package-browser/",
"cpes": [
"cpe:/a:redhat:openshift_ai"
],
"defaultStatus": "unaffected",
"packageName": "rhoai/odh-mlflow-rhel9",
"product": "Red Hat OpenShift AI (RHOAI)",
"vendor": "Red Hat"
}
],
"source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c"
}
],
"cisaActionDue": "2026-06-22",
"cisaExploitAdd": "2026-06-08",
"cisaRequiredAction": "Apply mitigations per vendor instructions, follow applicable BOD 22-01 guidance for cloud services, or discontinue use of the product if mitigations are unavailable.",
"cisaVulnerabilityName": "BerriAI LiteLLM Command Injection Vulnerability",
"configurations": [
{
"nodes": [
{
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{
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}
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{
"nodes": [
{
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}
],
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}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "LiteLLM is a proxy server (AI Gateway) to call LLM APIs in OpenAI (or native) format. From version 1.74.2 to before version 1.83.7, two endpoints used to preview an MCP server before saving it \u2014 POST /mcp-rest/test/connection and POST /mcp-rest/test/tools/list \u2014 accepted a full server configuration in the request body, including the command, args, and env fields used by the stdio transport. When called with a stdio configuration, the endpoints attempted to connect, which spawned the supplied command as a subprocess on the proxy host with the privileges of the proxy process. The endpoints were gated only by a valid proxy API key, with no role check. Any authenticated user \u2014 including holders of low-privilege internal-user keys \u2014 could therefore run arbitrary commands on the host. This issue has been patched in version 1.83.7."
},
{
"lang": "es",
"value": "LiteLLM es un servidor proxy (Pasarela de IA) para llamar a las API de LLM en formato OpenAI (o nativo). Desde la versi\u00f3n 1.74.2 hasta antes de la versi\u00f3n 1.83.7, dos puntos finales utilizados para previsualizar un servidor MCP antes de guardarlo - POST /mcp-rest/test/connection y POST /mcp-rest/test/tools/list - aceptaban una configuraci\u00f3n completa del servidor en el cuerpo de la solicitud, incluyendo los campos command, args y env utilizados por el transporte stdio. Cuando se invocaban con una configuraci\u00f3n stdio, los puntos finales intentaban conectarse, lo que generaba el comando proporcionado como un subproceso en el host proxy con los privilegios del proceso proxy. Los puntos finales estaban protegidos \u00fanicamente por una clave API de proxy v\u00e1lida, sin verificaci\u00f3n de rol. Cualquier usuario autenticado - incluyendo los titulares de claves de usuario interno de bajo privilegio - pod\u00eda, por lo tanto, ejecutar comandos arbitrarios en el host. Este problema ha sido parcheado en la versi\u00f3n 1.83.7."
}
],
"id": "CVE-2026-42271",
"lastModified": "2026-10-26T20:10:00.160",
"metrics": {
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"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
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"source": "nvd@nist.gov",
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"exploitMaturity": "NOT_DEFINED",
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"modifiedAttackComplexity": "NOT_DEFINED",
"modifiedAttackRequirements": "NOT_DEFINED",
"modifiedAttackVector": "NOT_DEFINED",
"modifiedPrivilegesRequired": "NOT_DEFINED",
"modifiedSubAvailabilityImpact": "NOT_DEFINED",
"modifiedSubConfidentialityImpact": "NOT_DEFINED",
"modifiedSubIntegrityImpact": "NOT_DEFINED",
"modifiedUserInteraction": "NOT_DEFINED",
"modifiedVulnAvailabilityImpact": "NOT_DEFINED",
"modifiedVulnConfidentialityImpact": "NOT_DEFINED",
"modifiedVulnIntegrityImpact": "NOT_DEFINED",
"privilegesRequired": "LOW",
"providerUrgency": "NOT_DEFINED",
"subAvailabilityImpact": "NONE",
"subConfidentialityImpact": "HIGH",
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"valueDensity": "NOT_DEFINED",
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"vulnerabilityResponseEffort": "NOT_DEFINED"
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"timestamp": "2026-05-08T00:00:00+00:00",
"version": "2.0.3"
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},
"published": "2026-05-08T04:16:21.820",
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}
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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
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
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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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