FKIE_CVE-2026-28797
Vulnerability from fkie_nvd - Published: 2026-04-03 22:16 - Updated: 2026-07-24 22:10
Severity
Summary
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine. In versions 0.24.0 and prior, a Server-Side Template Injection (SSTI) vulnerability exists in RAGFlow's Agent workflow Text Processing (StringTransform) and Message components. These components use Python's jinja2.Template (unsandboxed) to render user-supplied templates, allowing any authenticated user to execute arbitrary operating system commands on the server. At time of publication, there are no publicly available patches.
References
| URL | Tags | ||
|---|---|---|---|
| security-advisories@github.com | https://github.com/infiniflow/ragflow/security/advisories/GHSA-vvwj-fvwh-4whx | Exploit, Mitigation, Vendor Advisory |
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| infiniflow | ragflow | * |
{
"affected": [
{
"affectedData": [
{
"product": "ragflow",
"vendor": "infiniflow",
"versions": [
{
"status": "affected",
"version": "\u003c= 0.24.0"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:infiniflow:ragflow:*:*:*:*:*:*:*:*",
"matchCriteriaId": "C4B649E9-6336-4DAB-A111-5D0503CA4A5C",
"versionEndIncluding": "0.24.0",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine. In versions 0.24.0 and prior, a Server-Side Template Injection (SSTI) vulnerability exists in RAGFlow\u0027s Agent workflow Text Processing (StringTransform) and Message components. These components use Python\u0027s jinja2.Template (unsandboxed) to render user-supplied templates, allowing any authenticated user to execute arbitrary operating system commands on the server. At time of publication, there are no publicly available patches."
},
{
"lang": "es",
"value": "RAGFlow es un motor RAG (Generaci\u00f3n Aumentada por Recuperaci\u00f3n) de c\u00f3digo abierto. En las versiones 0.24.0 y anteriores, existe una vulnerabilidad de Inyecci\u00f3n de Plantillas del Lado del Servidor (SSTI) en los componentes de Procesamiento de Texto (StringTransform) y Mensaje del flujo de trabajo del Agente de RAGFlow. Estos componentes utilizan jinja2.Template de Python (sin sandboxing) para renderizar plantillas proporcionadas por el usuario, permitiendo a cualquier usuario autenticado ejecutar comandos arbitrarios del sistema operativo en el servidor. En el momento de la publicaci\u00f3n, no hay parches disponibles p\u00fablicamente."
}
],
"id": "CVE-2026-28797",
"lastModified": "2026-07-24T22:10:00.140",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 8.8,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"exploitabilityScore": 2.8,
"impactScore": 5.9,
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"type": "Secondary"
}
],
"cvssMetricV40": [
{
"cvssData": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "LOW",
"attackRequirements": "NONE",
"attackVector": "NETWORK",
"availabilityRequirement": "NOT_DEFINED",
"baseScore": 8.7,
"baseSeverity": "HIGH",
"confidentialityRequirement": "NOT_DEFINED",
"exploitMaturity": "NOT_DEFINED",
"integrityRequirement": "NOT_DEFINED",
"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": "NONE",
"subIntegrityImpact": "NONE",
"userInteraction": "NONE",
"valueDensity": "NOT_DEFINED",
"vectorString": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
"version": "4.0",
"vulnAvailabilityImpact": "HIGH",
"vulnConfidentialityImpact": "HIGH",
"vulnIntegrityImpact": "HIGH",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"source": "security-advisories@github.com",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-28797",
"options": [
{
"exploitation": "poc"
},
{
"automatable": "no"
},
{
"technicalImpact": "total"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-04-06T18:56:48.455858Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-04-03T22:16:26.320",
"references": [
{
"source": "security-advisories@github.com",
"tags": [
"Exploit",
"Mitigation",
"Vendor Advisory"
],
"url": "https://github.com/infiniflow/ragflow/security/advisories/GHSA-vvwj-fvwh-4whx"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Analyzed",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-20"
},
{
"lang": "en",
"value": "CWE-78"
},
{
"lang": "en",
"value": "CWE-94"
},
{
"lang": "en",
"value": "CWE-1336"
}
],
"source": "security-advisories@github.com",
"type": "Secondary"
}
]
}
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Nomenclature
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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.
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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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