FKIE_CVE-2026-31228

Vulnerability from fkie_nvd - Published: 2026-05-12 16:16 - Updated: 2026-10-19 22:10
Severity
9.8 (Critical) - CVSS:3.1/AV:N/AC:L/PR:N/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
Summary
The Adversarial Robustness Toolbox (ART) thru 1.20.1 contains a remote code execution vulnerability in its Kubeflow component. The robustness evaluation function for PyTorch models uses the unsafe eval() function to dynamically evaluate user-supplied strings for the LossFn and Optimizer parameters without any sanitization or security restrictions. An attacker can exploit this by providing a specially crafted string that contains arbitrary Python code, which will be executed when eval() is called, leading to complete compromise of the system running the ART evaluation.
References
cve@mitre.orghttps://github.com/Trusted-AI/adversarial-robustness-toolbox
cve@mitre.orghttps://www.notion.so/CVE-2026-31228-35d1e1393188817f9ab0dc4b1651dfe9
0b0ca135-0b70-47e7-9f44-1890c2a1c46chttps://access.redhat.com/security/cve/CVE-2026-31228
0b0ca135-0b70-47e7-9f44-1890c2a1c46chttps://bugzilla.redhat.com/show_bug.cgi?id=2476522
0b0ca135-0b70-47e7-9f44-1890c2a1c46chttps://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-31228.json
Impacted products
Vendor Product Version
To clipboard 

{
  "affected": [
    {
      "affectedData": [
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          "product": "n/a",
          "vendor": "n/a",
          "versions": [
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      "source": "cve@mitre.org"
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          "defaultStatus": "unaffected",
          "packageName": "rhoai/odh-kserve-agent-rhel9",
          "product": "Red Hat OpenShift AI (RHOAI)",
          "vendor": "Red Hat"
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          "product": "Red Hat OpenShift AI (RHOAI)",
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          "defaultStatus": "unaffected",
          "packageName": "rhoai/odh-kserve-router-rhel9",
          "product": "Red Hat OpenShift AI (RHOAI)",
          "vendor": "Red Hat"
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          "packageName": "rhoai/odh-kserve-storage-initializer-rhel9",
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      "source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c"
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  ],
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "The Adversarial Robustness Toolbox (ART) thru 1.20.1 contains a remote code execution vulnerability in its Kubeflow component. The robustness evaluation function for PyTorch models uses the unsafe eval() function to dynamically evaluate user-supplied strings for the LossFn and Optimizer parameters without any sanitization or security restrictions. An attacker can exploit this by providing a specially crafted string that contains arbitrary Python code, which will be executed when eval() is called, leading to complete compromise of the system running the ART evaluation."
    },
    {
      "lang": "es",
      "value": "La Adversarial Robustness Toolbox (ART) hasta la versi\u00f3n 1.20.1 contiene una vulnerabilidad de ejecuci\u00f3n remota de c\u00f3digo en su componente Kubeflow. La funci\u00f3n de evaluaci\u00f3n de robustez para modelos PyTorch utiliza la funci\u00f3n insegura eval() para evaluar din\u00e1micamente cadenas proporcionadas por el usuario para los par\u00e1metros LossFn y Optimizer sin ninguna sanitizaci\u00f3n o restricciones de seguridad. Un atacante puede explotar esto al proporcionar una cadena especialmente dise\u00f1ada que contiene c\u00f3digo Python arbitrario, el cual se ejecutar\u00e1 cuando se llame a eval(), lo que lleva a un compromiso completo del sistema que ejecuta la evaluaci\u00f3n de ART."
    }
  ],
  "id": "CVE-2026-31228",
  "lastModified": "2026-10-19T22:10:00.130",
  "metrics": {
    "cvssMetricV31": [
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        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "HIGH",
          "baseScore": 9.8,
          "baseSeverity": "CRITICAL",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "HIGH",
          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
          "version": "3.1"
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        "impactScore": 5.9,
        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "type": "Secondary"
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          "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"
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        "source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c",
        "type": "Secondary"
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    "ssvcV203": [
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        "ssvcData": {
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          "options": [
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              "exploitation": "none"
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            {
              "automatable": "yes"
            },
            {
              "technicalImpact": "total"
            }
          ],
          "role": "CISA Coordinator",
          "timestamp": "2026-05-13T14:09:43.765461Z",
          "version": "2.0.3"
        }
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  },
  "published": "2026-05-12T16:16:14.633",
  "references": [
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      "url": "https://github.com/Trusted-AI/adversarial-robustness-toolbox"
    },
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    },
    {
      "source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c",
      "url": "https://access.redhat.com/security/cve/CVE-2026-31228"
    },
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      "source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c",
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  "vulnStatus": "Awaiting Analysis",
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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

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Nomenclature

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  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.



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