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CVE-2022-23594

Estado: ModificadaMedia (5.5)—

Tensorflow is an Open Source Machine Learning Framework. The TFG dialect of TensorFlow (MLIR) makes several assumptions about the incoming `GraphDef` before converting it to the MLIR-based dialect. If an attacker changes the `SavedModel` format on disk to invalidate these assumptions and the `GraphDef` is then converted to MLIR-based IR then they can cause a crash in the Python interpreter. Under certain scenarios, heap OOB read/writes are possible. These issues have been discovered via fuzzing and it is possible that more weaknesses exist. We will patch them as they are discovered.

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)

Google — Tensorflow

CWE

Referencias

JSON original (NVD)

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{
  "id": "CVE-2022-23594",
  "cveTags": [],
  "metrics": {
    "ssvcV203": [
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        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "ssvcData": {
          "id": "CVE-2022-23594",
          "role": "CISA Coordinator",
          "options": [
            {
              "exploitation": "none"
            },
            {
              "automatable": "no"
            },
            {
              "technicalImpact": "total"
            }
          ],
          "version": "2.0.3",
          "timestamp": "2025-04-23T15:56:39.810788Z"
        }
      }
    ],
    "cvssMetricV2": [
      {
        "type": "Primary",
        "source": "nvd@nist.gov",
        "cvssData": {
          "version": "2.0",
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          "accessVector": "LOCAL",
          "vectorString": "AV:L/AC:L/Au:N/C:N/I:N/A:P",
          "authentication": "NONE",
          "integrityImpact": "NONE",
          "accessComplexity": "LOW",
          "availabilityImpact": "PARTIAL",
          "confidentialityImpact": "NONE"
        },
        "acInsufInfo": false,
        "impactScore": 2.9,
        "baseSeverity": "LOW",
        "obtainAllPrivilege": false,
        "exploitabilityScore": 3.9,
        "obtainUserPrivilege": false,
        "obtainOtherPrivilege": false,
        "userInteractionRequired": false
      }
    ],
    "cvssMetricV31": [
      {
        "type": "Secondary",
        "source": "security-advisories@github.com",
        "cvssData": {
          "scope": "CHANGED",
          "version": "3.1",
          "baseScore": 8.8,
          "attackVector": "LOCAL",
          "baseSeverity": "HIGH",
          "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H",
          "integrityImpact": "HIGH",
          "userInteraction": "NONE",
          "attackComplexity": "LOW",
          "availabilityImpact": "HIGH",
          "privilegesRequired": "LOW",
          "confidentialityImpact": "HIGH"
        },
        "impactScore": 6,
        "exploitabilityScore": 2
      },
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        "type": "Primary",
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        "cvssData": {
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          "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
          "integrityImpact": "NONE",
          "userInteraction": "NONE",
          "attackComplexity": "LOW",
          "availabilityImpact": "HIGH",
          "privilegesRequired": "LOW",
          "confidentialityImpact": "NONE"
        },
        "impactScore": 3.6,
        "exploitabilityScore": 1.8
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  "affected": [
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      "source": "security-advisories@github.com",
      "affectedData": [
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          "vendor": "tensorflow",
          "product": "tensorflow",
          "versions": [
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              "status": "affected",
              "version": ">= 2.7.0, < 2.8.0"
            }
          ]
        }
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    }
  ],
  "published": "2022-02-04T23:15:15.410",
  "references": [
    {
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9x52-887g-fhc2",
      "tags": [
        "Third Party Advisory"
      ],
      "source": "security-advisories@github.com"
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    {
      "url": "https://github.com/tensorflow/tensorflow/tree/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/core/ir/importexport",
      "tags": [
        "Third Party Advisory"
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    {
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9x52-887g-fhc2",
      "tags": [
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      "source": "af854a3a-2127-422b-91ae-364da2661108"
    },
    {
      "url": "https://github.com/tensorflow/tensorflow/tree/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/core/ir/importexport",
      "tags": [
        "Third Party Advisory"
      ],
      "source": "af854a3a-2127-422b-91ae-364da2661108"
    }
  ],
  "vulnStatus": "Modified",
  "weaknesses": [
    {
      "type": "Secondary",
      "source": "security-advisories@github.com",
      "description": [
        {
          "lang": "en",
          "value": "CWE-125"
        }
      ]
    },
    {
      "type": "Primary",
      "source": "nvd@nist.gov",
      "description": [
        {
          "lang": "en",
          "value": "CWE-125"
        },
        {
          "lang": "en",
          "value": "CWE-787"
        }
      ]
    }
  ],
  "descriptions": [
    {
      "lang": "en",
      "value": "Tensorflow is an Open Source Machine Learning Framework. The TFG dialect of TensorFlow (MLIR) makes several assumptions about the incoming `GraphDef` before converting it to the MLIR-based dialect. If an attacker changes the `SavedModel` format on disk to invalidate these assumptions and the `GraphDef` is then converted to MLIR-based IR then they can cause a crash in the Python interpreter. Under certain scenarios, heap OOB read/writes are possible. These issues have been discovered via fuzzing and it is possible that more weaknesses exist. We will patch them as they are discovered."
    },
    {
      "lang": "es",
      "value": "Tensorflow es un Marco de Aprendizaje Automático de Código Abierto. El dialecto TFG de TensorFlow (MLIR) hace varias suposiciones sobre el \"GraphDef\" entrante antes de convertirlo al dialecto basado en MLIR. Si un atacante cambia el formato del \"SavedModel\" en el disco para invalidar estas suposiciones y el \"GraphDef\" es entonces convertido al IR basado en MLIR, entonces pueden causar un bloqueo en el intérprete de Python. Bajo determinados escenarios, es posible la lectura/escritura de OOB en la pila. Estos problemas han sido detectados por medio de fuzzing y es posible que se presenten más debilidades. Los parchearemos a medida que son detectadas"
    }
  ],
  "lastModified": "2026-06-17T04:30:26.333",
  "configurations": [
    {
      "nodes": [
        {
          "negate": false,
          "cpeMatch": [
            {
              "criteria": "cpe:2.3:a:google:tensorflow:2.7.0:*:*:*:*:*:*:*",
              "vulnerable": true,
              "matchCriteriaId": "2EDFAAB8-799C-4259-9102-944D4760DA2C"
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          "operator": "OR"
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  "sourceIdentifier": "security-advisories@github.com"
}