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CVE-2026-12570

Estado: Pendiente de análisisMedia (5.5)—

A vulnerability in keras-team/keras versions <= 3.15.0 allows for a denial of service (DoS) attack when loading malicious .keras model files via the keras.models.load_model() function. The H5IOStore.__getitem__ method in keras/src/saving/saving_lib.py does not validate the shape or size of datasets, leading to unbounded memory allocation. A specially crafted .keras file can exploit this flaw to trigger an out-of-memory (OOM) condition, causing the process to be terminated (exit code 137). This issue bypasses the fix for CVE-2026-0897, which only addressed a similar vulnerability in KerasFileEditor. The attack vector includes poisoned models from public repositories or malicious model registries, posing a risk to machine learning pipelines that process untrusted models.

CVSS

Probabilidad de explotación (EPSS)

EPSS (Exploit Prediction Scoring System, de FIRST) estima la probabilidad de que una vulnerabilidad sea explotada en 30 días. Complementa a CVSS (impacto) y a CISA KEV (explotación confirmada).

Tecnologías afectadas (1)

⚠ Inferidas por IA a partir de la descripción — NVD aún no ha analizado esta CVE; no son CPE verificados.

Keras — KerasAI

CWE

Referencias

JSON original (NVD)

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{
  "id": "CVE-2026-12570",
  "cveTags": [],
  "metrics": {
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        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "ssvcData": {
          "id": "CVE-2026-12570",
          "role": "CISA Coordinator",
          "options": [
            {
              "exploitation": "poc"
            },
            {
              "automatable": "no"
            },
            {
              "technicalImpact": "partial"
            }
          ],
          "version": "2.0.3",
          "timestamp": "2026-08-10T17:37:17.637683Z"
        }
      }
    ],
    "cvssMetricV30": [
      {
        "type": "Secondary",
        "source": "security@huntr.dev",
        "cvssData": {
          "scope": "UNCHANGED",
          "version": "3.0",
          "baseScore": 5.5,
          "attackVector": "LOCAL",
          "baseSeverity": "MEDIUM",
          "vectorString": "CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H",
          "integrityImpact": "NONE",
          "userInteraction": "REQUIRED",
          "attackComplexity": "LOW",
          "availabilityImpact": "HIGH",
          "privilegesRequired": "NONE",
          "confidentialityImpact": "NONE"
        },
        "impactScore": 3.6,
        "exploitabilityScore": 1.8
      }
    ]
  },
  "affected": [
    {
      "source": "security@huntr.dev",
      "affectedData": [
        {
          "vendor": "keras-team",
          "product": "keras-team/keras",
          "versions": [
            {
              "status": "affected",
              "version": "unspecified",
              "lessThan": "3.12.3, 3.15.0",
              "versionType": "custom"
            }
          ]
        }
      ]
    }
  ],
  "published": "2026-08-10T07:16:44.370",
  "references": [
    {
      "url": "https://github.com/keras-team/keras/commit/4933ea4a5b3fcc24ceacdc276f5bb5dfbd06756c",
      "source": "security@huntr.dev"
    },
    {
      "url": "https://huntr.com/bounties/a064f475-780a-409a-82f7-678512f27ad8",
      "source": "security@huntr.dev"
    },
    {
      "url": "https://huntr.com/bounties/a064f475-780a-409a-82f7-678512f27ad8",
      "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0"
    }
  ],
  "vulnStatus": "Awaiting Analysis",
  "weaknesses": [
    {
      "type": "Secondary",
      "source": "security@huntr.dev",
      "description": [
        {
          "lang": "en",
          "value": "CWE-770"
        }
      ]
    }
  ],
  "descriptions": [
    {
      "lang": "en",
      "value": "A vulnerability in keras-team/keras versions <= 3.15.0 allows for a denial of service (DoS) attack when loading malicious .keras model files via the keras.models.load_model() function. The H5IOStore.__getitem__ method in keras/src/saving/saving_lib.py does not validate the shape or size of datasets, leading to unbounded memory allocation. A specially crafted .keras file can exploit this flaw to trigger an out-of-memory (OOM) condition, causing the process to be terminated (exit code 137). This issue bypasses the fix for CVE-2026-0897, which only addressed a similar vulnerability in KerasFileEditor. The attack vector includes poisoned models from public repositories or malicious model registries, posing a risk to machine learning pipelines that process untrusted models."
    }
  ],
  "lastModified": "2026-09-03T17:56:18.093",
  "sourceIdentifier": "security@huntr.dev"
}