Vulnerability-Lookup

CVE-2026-5817 (GCVE-0-2026-5817)

Vulnerability from cvelistv5 – Published: 2026-05-22 19:24 – Updated: 2026-05-27 03:55

Title

Docker Model Runner container-to-host code execution via unsandboxed trust_remote_code in Python inference backends

Summary

The vllm-metal inference backend in Docker Model Runner on macOS unconditionally sets trust_remote_code=True when loading model tokenizers, and runs without sandboxing. This causes transformers.AutoTokenizer.from_pretrained() to import and execute arbitrary Python files included in any model pulled from an OCI registry, resulting in arbitrary code execution on the Docker host as the Docker Desktop user when inference is triggered. Any container on the Docker network can trigger this by calling the model-runner.docker.internal API to pull a malicious model and request inference.

Severity

8.8 (High)


                        
                          CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H

8.2 (High)


                        
                          CVSS:3.1/AV:L/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:H

SSVC

Exploitation: none Automatable: no Technical Impact: total

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2026-05-26 00:00 UTC

CWE

CWE-829 - Inclusion of Functionality from Untrusted Control Sphere

Assigner

Docker mitre root

References

1 reference

URL	Tags
https://docs.docker.com/desktop/release-notes/#4680	release-notes

Impacted products

1 product

Vendor	Product	Version
Docker	Docker Desktop	Affected: 4.62.0 , < 4.68.0 (semver)

Credits

David Rochester (@davidrxchester) Nicholas Gould (@gouldnicholas)

Show details on NVD website

JSON

To clipboard

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BDU:2026-10963 (CVE-2026-5817)

Vulnerability from fstec – Published: 2026-08-03 – Updated: 2026-08-03 – View on bdu.fstec.ru Fixed

Title

Уязвимость компонента vllm-metal inference backend плагина для Docker Desktop Docker Model Runner, позволяющая нарушителю выполнить произвольный код

Summary

Уязвимость компонента vllm-metal inference backend плагина для Docker Desktop Docker Model Runner связана с включением функций из недостоверной контролируемой области. Эксплуатация уязвимости может позволить нарушителю выполнить произвольный код

Severity

7.2 (High) CVSS 2.0


                      
                        AV:L/AC:L/Au:N/C:C/I:C/A:C

8.6 (High) CVSS 3.1


                      
                        CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H

Class

Architecture vulnerability

Status

Confirmed by the vendor

Exploitation

Spoofing

Incidents

Being clarified

Remediation

Software update

CWE

CWE-829 - Включение функций из недостоверной контролируемой области

Aliases

CVE-2026-5817

References

1 reference

URL
https://docs.docker.com/desktop/release-notes/#4680

Impacted products

1 product from 1 vendor

Vendors

Docker Inc.

Products

Docker Model Runner

Versions

от 4.62.0 до 4.68.0 (Docker Model Runner)

Product types

Application software

Mitigations

Использование рекомендаций: https://docs.docker.com/desktop/release-notes/#4680

JSON

To clipboard

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  "\u041d\u0430\u0438\u043c\u0435\u043d\u043e\u0432\u0430\u043d\u0438\u0435 \u041e\u0421 \u0438 \u0442\u0438\u043f \u0430\u043f\u043f\u0430\u0440\u0430\u0442\u043d\u043e\u0439 \u043f\u043b\u0430\u0442\u0444\u043e\u0440\u043c\u044b": null,
  "\u041d\u0430\u0438\u043c\u0435\u043d\u043e\u0432\u0430\u043d\u0438\u0435 \u0443\u044f\u0437\u0432\u0438\u043c\u043e\u0441\u0442\u0438": "\u0423\u044f\u0437\u0432\u0438\u043c\u043e\u0441\u0442\u044c \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442\u0430 vllm-metal inference backend \u043f\u043b\u0430\u0433\u0438\u043d\u0430 \u0434\u043b\u044f Docker Desktop Docker Model Runner, \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u044e\u0449\u0430\u044f \u043d\u0430\u0440\u0443\u0448\u0438\u0442\u0435\u043b\u044e \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u043b\u044c\u043d\u044b\u0439 \u043a\u043e\u0434",
  "\u041d\u0430\u043b\u0438\u0447\u0438\u0435 \u044d\u043a\u0441\u043f\u043b\u043e\u0439\u0442\u0430": "\u0414\u0430\u043d\u043d\u044b\u0435 \u0443\u0442\u043e\u0447\u043d\u044f\u044e\u0442\u0441\u044f",
  "\u041e\u043f\u0438\u0441\u0430\u043d\u0438\u0435 \u043e\u0448\u0438\u0431\u043a\u0438 CWE": "\u0412\u043a\u043b\u044e\u0447\u0435\u043d\u0438\u0435 \u0444\u0443\u043d\u043a\u0446\u0438\u0439 \u0438\u0437 \u043d\u0435\u0434\u043e\u0441\u0442\u043e\u0432\u0435\u0440\u043d\u043e\u0439 \u043a\u043e\u043d\u0442\u0440\u043e\u043b\u0438\u0440\u0443\u0435\u043c\u043e\u0439 \u043e\u0431\u043b\u0430\u0441\u0442\u0438 (CWE-829)",
  "\u041e\u043f\u0438\u0441\u0430\u043d\u0438\u0435 \u0443\u044f\u0437\u0432\u0438\u043c\u043e\u0441\u0442\u0438": "\u0423\u044f\u0437\u0432\u0438\u043c\u043e\u0441\u0442\u044c \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442\u0430 vllm-metal inference backend \u043f\u043b\u0430\u0433\u0438\u043d\u0430 \u0434\u043b\u044f Docker Desktop Docker Model Runner \u0441\u0432\u044f\u0437\u0430\u043d\u0430 \u0441 \u0432\u043a\u043b\u044e\u0447\u0435\u043d\u0438\u0435\u043c \u0444\u0443\u043d\u043a\u0446\u0438\u0439 \u0438\u0437 \u043d\u0435\u0434\u043e\u0441\u0442\u043e\u0432\u0435\u0440\u043d\u043e\u0439 \u043a\u043e\u043d\u0442\u0440\u043e\u043b\u0438\u0440\u0443\u0435\u043c\u043e\u0439 \u043e\u0431\u043b\u0430\u0441\u0442\u0438. \u042d\u043a\u0441\u043f\u043b\u0443\u0430\u0442\u0430\u0446\u0438\u044f \u0443\u044f\u0437\u0432\u0438\u043c\u043e\u0441\u0442\u0438 \u043c\u043e\u0436\u0435\u0442 \u043f\u043e\u0437\u0432\u043e\u043b\u0438\u0442\u044c \u043d\u0430\u0440\u0443\u0448\u0438\u0442\u0435\u043b\u044e \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u043b\u044c\u043d\u044b\u0439 \u043a\u043e\u0434",
  "\u041f\u043e\u0441\u043b\u0435\u0434\u0441\u0442\u0432\u0438\u044f \u044d\u043a\u0441\u043f\u043b\u0443\u0430\u0442\u0430\u0446\u0438\u0438 \u0443\u044f\u0437\u0432\u0438\u043c\u043e\u0441\u0442\u0438": null,
  "\u041f\u0440\u043e\u0447\u0430\u044f \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u044f": null,
  "\u0421\u0432\u044f\u0437\u044c \u0441 \u0438\u043d\u0446\u0438\u0434\u0435\u043d\u0442\u0430\u043c\u0438 \u0418\u0411": "\u0414\u0430\u043d\u043d\u044b\u0435 \u0443\u0442\u043e\u0447\u043d\u044f\u044e\u0442\u0441\u044f",
  "\u0421\u043e\u0441\u0442\u043e\u044f\u043d\u0438\u0435 \u0443\u044f\u0437\u0432\u0438\u043c\u043e\u0441\u0442\u0438": "\u041e\u043f\u0443\u0431\u043b\u0438\u043a\u043e\u0432\u0430\u043d\u0430",
  "\u0421\u043f\u043e\u0441\u043e\u0431 \u0443\u0441\u0442\u0440\u0430\u043d\u0435\u043d\u0438\u044f": "\u041e\u0431\u043d\u043e\u0432\u043b\u0435\u043d\u0438\u0435 \u043f\u0440\u043e\u0433\u0440\u0430\u043c\u043c\u043d\u043e\u0433\u043e \u043e\u0431\u0435\u0441\u043f\u0435\u0447\u0435\u043d\u0438\u044f",
  "\u0421\u043f\u043e\u0441\u043e\u0431 \u044d\u043a\u0441\u043f\u043b\u0443\u0430\u0442\u0430\u0446\u0438\u0438": "\u041f\u043e\u0434\u043c\u0435\u043d\u0430 \u043f\u0440\u0438 \u0432\u0437\u0430\u0438\u043c\u043e\u0434\u0435\u0439\u0441\u0442\u0432\u0438\u0438",
  "\u0421\u0441\u044b\u043b\u043a\u0438 \u043d\u0430 \u0438\u0441\u0442\u043e\u0447\u043d\u0438\u043a\u0438": "https://docs.docker.com/desktop/release-notes/#4680",
  "\u0421\u0442\u0430\u0442\u0443\u0441 \u0443\u044f\u0437\u0432\u0438\u043c\u043e\u0441\u0442\u0438": "\u041f\u043e\u0434\u0442\u0432\u0435\u0440\u0436\u0434\u0435\u043d\u0430 \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u0435\u043c",
  "\u0422\u0438\u043f \u041f\u041e": "\u041f\u0440\u0438\u043a\u043b\u0430\u0434\u043d\u043e\u0435 \u041f\u041e \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u043e\u043d\u043d\u044b\u0445 \u0441\u0438\u0441\u0442\u0435\u043c",
  "\u0422\u0438\u043f \u043e\u0448\u0438\u0431\u043a\u0438 CWE": "CWE-829",
  "\u0423\u0440\u043e\u0432\u0435\u043d\u044c \u043e\u043f\u0430\u0441\u043d\u043e\u0441\u0442\u0438 \u0443\u044f\u0437\u0432\u0438\u043c\u043e\u0441\u0442\u0438": "\u0412\u044b\u0441\u043e\u043a\u0438\u0439 \u0443\u0440\u043e\u0432\u0435\u043d\u044c \u043e\u043f\u0430\u0441\u043d\u043e\u0441\u0442\u0438 (\u0431\u0430\u0437\u043e\u0432\u0430\u044f \u043e\u0446\u0435\u043d\u043a\u0430 CVSS 2.0 \u0441\u043e\u0441\u0442\u0430\u0432\u043b\u044f\u0435\u0442 7,2)\n\u0412\u044b\u0441\u043e\u043a\u0438\u0439 \u0443\u0440\u043e\u0432\u0435\u043d\u044c \u043e\u043f\u0430\u0441\u043d\u043e\u0441\u0442\u0438 (\u0431\u0430\u0437\u043e\u0432\u0430\u044f \u043e\u0446\u0435\u043d\u043a\u0430 CVSS 3.1 \u0441\u043e\u0441\u0442\u0430\u0432\u043b\u044f\u0435\u0442 8,6)"
}

CERTFR-2026-AVI-0620

Vulnerability from certfr_avis - Published: 2026-05-20 - Updated: 2026-05-20

De multiples vulnérabilités ont été découvertes dans Docker. Elles permettent à un attaquant de provoquer une exécution de code arbitraire à distance.

Solutions

Se référer au bulletin de sécurité de l'éditeur pour l'obtention des correctifs (cf. section Documentation).

Impacted products

	Vendor	Product	Description
	Docker	Docker Desktop	Docker Desktop versions antérieures à 4.71.0

References

Title

Publication Time

EUVD-2026-72081

European Vulnerability Database identifier assigned by ENISA

Reserved

2026-10-03 10:52

Assigner

ENISA

Alias of

a CVE record, shown under related vulnerabilities. This identifier carries no description, severity or references of its own: they belong to that CVE.

JSON

To clipboard

{
  "assigner": "ENISA",
  "date_reserved": "2026-10-03T10:52:28.508015+00:00",
  "id": "EUVD-2026-72081"
}

FKIE_CVE-2026-5817

Vulnerability from fkie_nvd - Published: 2026-05-22 20:16 - Updated: 2026-07-23 11:10

Severity

8.2 (High) - CVSS:3.1/AV:L/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:H
8.6 (High) - CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H

Summary

References

	URL	Tags
	security@docker.com	https://docs.docker.com/desktop/release-notes/#4680	Release Notes

Impacted products

	Vendor	Product	Version
	docker	docker_desktop	*
	apple	macos	-

JSON

To clipboard

{
  "affected": [
    {
      "affectedData": [
        {
          "defaultStatus": "unaffected",
          "platforms": [
            "MacOS"
          ],
          "product": "Docker Desktop",
          "vendor": "Docker",
          "versions": [
            {
              "lessThan": "4.68.0",
              "status": "affected",
              "version": "4.62.0",
              "versionType": "semver"
            }
          ]
        }
      ],
      "source": "security@docker.com"
    }
  ],
  "configurations": [
    {
      "nodes": [
        {
          "cpeMatch": [
            {
              "criteria": "cpe:2.3:a:docker:docker_desktop:*:*:*:*:*:*:*:*",
              "matchCriteriaId": "D13BBDD8-AB90-414E-A29B-75FA2125E68F",
              "versionEndExcluding": "4.68.0",
              "versionStartIncluding": "4.62.0",
              "vulnerable": true
            }
          ],
          "negate": false,
          "operator": "OR"
        },
        {
          "cpeMatch": [
            {
              "criteria": "cpe:2.3:o:apple:macos:-:*:*:*:*:*:*:*",
              "matchCriteriaId": "387021A0-AF36-463C-A605-32EA7DAC172E",
              "vulnerable": false
            }
          ],
          "negate": false,
          "operator": "OR"
        }
      ],
      "operator": "AND"
    }
  ],
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "The vllm-metal inference backend in Docker Model Runner on macOS unconditionally sets trust_remote_code=True when loading model tokenizers, and runs without sandboxing. This causes transformers.AutoTokenizer.from_pretrained() to import and execute arbitrary Python files included in any model pulled from an OCI registry, resulting in arbitrary code execution on the Docker host as the Docker Desktop user when inference is triggered.\n\nAny container on the Docker network can trigger this by calling the model-runner.docker.internal API to pull a malicious model and request inference."
    },
    {
      "lang": "es",
      "value": "El backend de inferencia vllm-metal en Docker Model Runner en macOS establece incondicionalmente trust_remote_code=True al cargar tokenizadores de modelos, y se ejecuta sin sandboxing. Esto provoca que transformers.AutoTokenizer.from_pretrained() importe y ejecute archivos Python arbitrarios incluidos en cualquier modelo extra\u00eddo de un registro OCI, lo que resulta en ejecuci\u00f3n de c\u00f3digo arbitrario en el host de Docker como el usuario de Docker Desktop cuando se activa la inferencia.\n\nCualquier contenedor en la red de Docker puede activar esto llamando a la API model-runner.docker.internal para extraer un modelo malicioso y solicitar inferencia."
    }
  ],
  "id": "CVE-2026-5817",
  "lastModified": "2026-07-23T11:10:00.120",
  "metrics": {
    "cvssMetricV31": [
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "LOCAL",
          "availabilityImpact": "HIGH",
          "baseScore": 8.2,
          "baseSeverity": "HIGH",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "HIGH",
          "privilegesRequired": "LOW",
          "scope": "CHANGED",
          "userInteraction": "REQUIRED",
          "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:H",
          "version": "3.1"
        },
        "exploitabilityScore": 1.5,
        "impactScore": 6.0,
        "source": "security@docker.com",
        "type": "Secondary"
      },
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "LOCAL",
          "availabilityImpact": "HIGH",
          "baseScore": 8.6,
          "baseSeverity": "HIGH",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "HIGH",
          "privilegesRequired": "NONE",
          "scope": "CHANGED",
          "userInteraction": "REQUIRED",
          "vectorString": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H",
          "version": "3.1"
        },
        "exploitabilityScore": 1.8,
        "impactScore": 6.0,
        "source": "nvd@nist.gov",
        "type": "Primary"
      }
    ],
    "cvssMetricV40": [
      {
        "cvssData": {
          "Automatable": "NOT_DEFINED",
          "Recovery": "NOT_DEFINED",
          "Safety": "NOT_DEFINED",
          "attackComplexity": "LOW",
          "attackRequirements": "PRESENT",
          "attackVector": "LOCAL",
          "availabilityRequirement": "NOT_DEFINED",
          "baseScore": 8.8,
          "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": "HIGH",
          "subConfidentialityImpact": "HIGH",
          "subIntegrityImpact": "HIGH",
          "userInteraction": "NONE",
          "valueDensity": "NOT_DEFINED",
          "vectorString": "CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H/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@docker.com",
        "type": "Secondary"
      }
    ],
    "ssvcV203": [
      {
        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "ssvcData": {
          "id": "CVE-2026-5817",
          "options": [
            {
              "exploitation": "none"
            },
            {
              "automatable": "no"
            },
            {
              "technicalImpact": "total"
            }
          ],
          "role": "CISA Coordinator",
          "timestamp": "2026-05-26T00:00:00+00:00",
          "version": "2.0.3"
        }
      }
    ]
  },
  "published": "2026-05-22T20:16:35.120",
  "references": [
    {
      "source": "security@docker.com",
      "tags": [
        "Release Notes"
      ],
      "url": "https://docs.docker.com/desktop/release-notes/#4680"
    }
  ],
  "sourceIdentifier": "security@docker.com",
  "vulnStatus": "Analyzed",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-829"
        }
      ],
      "source": "security@docker.com",
      "type": "Secondary"
    }
  ]
}

GHSA-CGQP-WW2V-6RJH

Vulnerability from github – Published: 2026-05-26 13:30 – Updated: 2026-05-26 13:30

Details

Any container on the Docker network can trigger this by calling the model-runner.docker.internal API to pull a malicious model and request inference.

Severity

8.2 (High)


                  
                    CVSS:3.1/AV:L/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:H

8.8 (High)


                  
                    CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H

Show details on source website

JSON

To clipboard

{
  "affected": [],
  "aliases": [
    "CVE-2026-5817"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-829"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-05-22T20:16:35Z",
    "severity": "HIGH"
  },
  "details": "The vllm-metal inference backend in Docker Model Runner on macOS unconditionally sets trust_remote_code=True when loading model tokenizers, and runs without sandboxing. This causes transformers.AutoTokenizer.from_pretrained() to import and execute arbitrary Python files included in any model pulled from an OCI registry, resulting in arbitrary code execution on the Docker host as the Docker Desktop user when inference is triggered.\n\nAny container on the Docker network can trigger this by calling the model-runner.docker.internal API to pull a malicious model and request inference.",
  "id": "GHSA-cgqp-ww2v-6rjh",
  "modified": "2026-05-26T13:30:21Z",
  "published": "2026-05-26T13:30:21Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-5817"
    },
    {
      "type": "WEB",
      "url": "https://docs.docker.com/desktop/release-notes/#4680"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H/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",
      "type": "CVSS_V4"
    }
  ]
}

WID-SEC-W-2026-1662

Vulnerability from csaf_certbund - Published: 2026-05-25 22:00 - Updated: 2026-05-25 22:00

Summary

Docker Desktop Model Runner: Mehrere Schwachstellen ermöglichen Codeausführung

Severity

Hoch

Scope

2 vulnerabilities in this advisory, including CVE-2026-5817.

CVE-2026-5817

Known affected: 1 product

Open the full advisory

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.

Detection rules are retrieved from Rulezet.

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.

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.

Action not permitted

CVE-2026-5817 (GCVE-0-2026-5817)

BDU:2026-10963 (CVE-2026-5817)

CERTFR-2026-AVI-0620

Solutions

EUVD-2026-72081

FKIE_CVE-2026-5817

GHSA-CGQP-WW2V-6RJH

WID-SEC-W-2026-1662

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Related by attack behaviour