FKIE_CVE-2026-31228

Vulnerability from fkie_nvd - Published: 2026-05-12 16:16 - Updated: 2026-07-15 02:19
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": [
        {
          "product": "n/a",
          "vendor": "n/a",
          "versions": [
            {
              "status": "affected",
              "version": "n/a"
            }
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      "source": "cve@mitre.org"
    },
    {
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          "cpes": [
            "cpe:/a:redhat:openshift_ai"
          ],
          "defaultStatus": "affected",
          "packageName": "rhoai/odh-kserve-agent-rhel9",
          "product": "Red Hat OpenShift AI (RHOAI)",
          "vendor": "Red Hat"
        },
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          "cpes": [
            "cpe:/a:redhat:openshift_ai"
          ],
          "defaultStatus": "affected",
          "packageName": "rhoai/odh-kserve-controller-rhel9",
          "product": "Red Hat OpenShift AI (RHOAI)",
          "vendor": "Red Hat"
        },
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          "cpes": [
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          "defaultStatus": "affected",
          "packageName": "rhoai/odh-kserve-router-rhel9",
          "product": "Red Hat OpenShift AI (RHOAI)",
          "vendor": "Red Hat"
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          ],
          "defaultStatus": "affected",
          "packageName": "rhoai/odh-kserve-storage-initializer-rhel9",
          "product": "Red Hat OpenShift AI (RHOAI)",
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        }
      ],
      "source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c"
    }
  ],
  "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."
    }
  ],
  "id": "CVE-2026-31228",
  "lastModified": "2026-07-15T02:19:46.373",
  "metrics": {
    "cvssMetricV31": [
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        "cvssData": {
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          "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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          "attackVector": "NETWORK",
          "availabilityImpact": "HIGH",
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          "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",
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    "ssvcV203": [
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        "ssvcData": {
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          "options": [
            {
              "exploitation": "none"
            },
            {
              "automatable": "yes"
            },
            {
              "technicalImpact": "total"
            }
          ],
          "role": "CISA Coordinator",
          "timestamp": "2026-05-13T14:09:43.765461Z",
          "version": "2.0.3"
        }
      }
    ]
  },
  "published": "2026-05-12T16:16:14.633",
  "references": [
    {
      "source": "cve@mitre.org",
      "url": "https://github.com/Trusted-AI/adversarial-robustness-toolbox"
    },
    {
      "source": "cve@mitre.org",
      "url": "https://www.notion.so/CVE-2026-31228-35d1e1393188817f9ab0dc4b1651dfe9"
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  "vulnStatus": "Awaiting Analysis",
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          "lang": "en",
          "value": "CWE-94"
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      "type": "Secondary"
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      "source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c",
      "type": "Secondary"
    }
  ]
}



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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

  • 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.
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  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
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  • 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.