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CVE-2021-29571

Estado: ModificadaAlta (7.8)—

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/31bd5026304677faa8a0b77602c6154171b9aec1/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L116-L130) assumes that the last element of `boxes` input is 4, as required by [the op](https://www.tensorflow.org/api_docs/python/tf/raw_ops/DrawBoundingBoxesV2).

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Since this is not checked attackers passing values less than 4 can write outside of bounds of heap allocated objects and cause memory corruption. If the last dimension in `boxes` is less than 4, accesses similar to `tboxes(b, bb, 3)` will access data outside of bounds. Further during code execution there are also writes to these indices. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

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-2021-29571",
  "cveTags": [],
  "metrics": {
    "cvssMetricV2": [
      {
        "type": "Primary",
        "source": "nvd@nist.gov",
        "cvssData": {
          "version": "2.0",
          "baseScore": 4.6,
          "accessVector": "LOCAL",
          "vectorString": "AV:L/AC:L/Au:N/C:P/I:P/A:P",
          "authentication": "NONE",
          "integrityImpact": "PARTIAL",
          "accessComplexity": "LOW",
          "availabilityImpact": "PARTIAL",
          "confidentialityImpact": "PARTIAL"
        },
        "acInsufInfo": false,
        "impactScore": 6.4,
        "baseSeverity": "MEDIUM",
        "obtainAllPrivilege": false,
        "exploitabilityScore": 3.9,
        "obtainUserPrivilege": false,
        "obtainOtherPrivilege": false,
        "userInteractionRequired": false
      }
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    "cvssMetricV31": [
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        "type": "Secondary",
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        "cvssData": {
          "scope": "UNCHANGED",
          "version": "3.1",
          "baseScore": 4.5,
          "attackVector": "LOCAL",
          "baseSeverity": "MEDIUM",
          "vectorString": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:L/I:L/A:L",
          "integrityImpact": "LOW",
          "userInteraction": "NONE",
          "attackComplexity": "HIGH",
          "availabilityImpact": "LOW",
          "privilegesRequired": "LOW",
          "confidentialityImpact": "LOW"
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        "impactScore": 3.4,
        "exploitabilityScore": 1
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        "type": "Primary",
        "source": "nvd@nist.gov",
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          "scope": "UNCHANGED",
          "version": "3.1",
          "baseScore": 7.8,
          "attackVector": "LOCAL",
          "baseSeverity": "HIGH",
          "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
          "integrityImpact": "HIGH",
          "userInteraction": "NONE",
          "attackComplexity": "LOW",
          "availabilityImpact": "HIGH",
          "privilegesRequired": "LOW",
          "confidentialityImpact": "HIGH"
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        "impactScore": 5.9,
        "exploitabilityScore": 1.8
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  "affected": [
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      "affectedData": [
        {
          "vendor": "tensorflow",
          "product": "tensorflow",
          "versions": [
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              "status": "affected",
              "version": "< 2.1.4"
            },
            {
              "status": "affected",
              "version": ">= 2.2.0, < 2.2.3"
            },
            {
              "status": "affected",
              "version": ">= 2.3.0, < 2.3.3"
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            {
              "status": "affected",
              "version": ">= 2.4.0, < 2.4.2"
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  "published": "2021-05-14T20:15:13.877",
  "references": [
    {
      "url": "https://github.com/tensorflow/tensorflow/commit/79865b542f9ffdc9caeb255631f7c56f1d4b6517",
      "tags": [
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        "Third Party Advisory"
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      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-whr9-vfh2-7hm6",
      "tags": [
        "Exploit",
        "Patch",
        "Third Party Advisory"
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      "source": "security-advisories@github.com"
    },
    {
      "url": "https://github.com/tensorflow/tensorflow/commit/79865b542f9ffdc9caeb255631f7c56f1d4b6517",
      "tags": [
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        "Third Party Advisory"
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      "source": "af854a3a-2127-422b-91ae-364da2661108"
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    {
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      "tags": [
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        "Patch",
        "Third Party Advisory"
      ],
      "source": "af854a3a-2127-422b-91ae-364da2661108"
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  ],
  "vulnStatus": "Modified",
  "weaknesses": [
    {
      "type": "Secondary",
      "source": "security-advisories@github.com",
      "description": [
        {
          "lang": "en",
          "value": "CWE-787"
        }
      ]
    }
  ],
  "descriptions": [
    {
      "lang": "en",
      "value": "TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/31bd5026304677faa8a0b77602c6154171b9aec1/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L116-L130) assumes that the last element of `boxes` input is 4, as required by [the op](https://www.tensorflow.org/api_docs/python/tf/raw_ops/DrawBoundingBoxesV2). Since this is not checked attackers passing values less than 4 can write outside of bounds of heap allocated objects and cause memory corruption. If the last dimension in `boxes` is less than 4, accesses similar to `tboxes(b, bb, 3)` will access data outside of bounds. Further during code execution there are also writes to these indices. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range."
    },
    {
      "lang": "es",
      "value": "TensorFlow es una plataforma de código abierto de extremo a extremo para el aprendizaje automático.&#xa0;La implementación de \"tf.raw_ops.MaxPoolGradWithArgmax\" puede causar una lectura fuera de límites de los datos asignados a la pila si el atacante suministra entradas especialmente diseñadas.&#xa0;La implementación (https://github.com/tensorflow/tensorflow/blob/31bd5026304677faa8a0b77602c6154171b9aec1/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L116-L130) asume que el último elemento de la entrada \"boxes\" es 4, ya que por [la operación] (https://www.tensorflow.org/api_docs/python/tf/raw_ops/DrawBoundingBoxesV2).&#xa0;Dado que esto no es comprobado, los atacantes que pasan valores inferiores a 4 pueden escribir fuera de límites de los objetos asignados a la pila y causar corrupción de la memoria.&#xa0;Si la última dimensión en \"boxes\" es menor que 4, accesos similares a\" tboxes (b, bb, 3) \"accederán a los datos fuera de límites.&#xa0;Además, durante una ejecución del código, también son escritos estos índices.&#xa0;La corrección será incluida en TensorFlow versión 2.5.0.&#xa0;También seleccionaremos este commit en TensorFlow versión 2.4.2, TensorFlow versión 2.3.3, TensorFlow versión 2.2.3 y TensorFlow versión 2.1.4, ya que estos también están afectados y aún están en el rango admitido"
    }
  ],
  "lastModified": "2026-06-17T03:47:56.093",
  "configurations": [
    {
      "nodes": [
        {
          "negate": false,
          "cpeMatch": [
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