nvd-json-data-feeds/CVE-2021/CVE-2021-376xx/CVE-2021-37669.json

{
  "id": "CVE-2021-37669",
  "sourceIdentifier": "security-advisories@github.com",
  "published": "2021-08-12T23:15:07.597",
  "lastModified": "2021-08-19T14:27:46.797",
  "vulnStatus": "Analyzed",
  "descriptions": [
    {
      "lang": "en",
      "value": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause denial of service in applications serving models using `tf.raw_ops.NonMaxSuppressionV5` by triggering a division by 0. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/image/non_max_suppression_op.cc#L170-L271) uses a user controlled argument to resize a `std::vector`. However, as `std::vector::resize` takes the size argument as a `size_t` and `output_size` is an `int`, there is an implicit conversion to unsigned. If the attacker supplies a negative value, this conversion results in a crash. A similar issue occurs in `CombinedNonMaxSuppression`. We have patched the issue in GitHub commit 3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d and commit [b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range."
    },
    {
      "lang": "es",
      "value": "TensorFlow es una plataforma de c\u00f3digo abierto de extremo a extremo para el aprendizaje autom\u00e1tico. En las versiones afectadas, un atacante puede causar una denegaci\u00f3n de servicio en aplicaciones que sirven modelos que usan \"tf.raw_ops.NonMaxSuppressionV5\" al activar una divisi\u00f3n por 0. La [implementaci\u00f3n] (https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/ tensorflow / core / kernels / image / non_max_suppression_op.cc # L170-L271) usa un argumento controlado por el usuario para cambiar el tama\u00f1o de un \"std :: vector\". Sin embargo, como \"std :: vector :: resize\" toma el argumento de tama\u00f1o como un\" size_t\" y \"output_size\" es un\" int\", hay una conversi\u00f3n impl\u00edcita a unsigned. Si el atacante proporciona un valor negativo, esta conversi\u00f3n resulta en un bloqueo. Un problema similar ocurre en \"CombinedNonMaxSuppression\". Hemos solucionado el problema en GitHub, commit 3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d y commit [b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58. La correcci\u00f3n ser\u00e1 incluida en TensorFlow versi\u00f3n 2.6.0. Tambi\u00e9n seleccionaremos este commit en TensorFlow versi\u00f3n 2.5.1, TensorFlow versi\u00f3n 2.4.3 y TensorFlow versi\u00f3n 2.3.4, ya que estos tambi\u00e9n est\u00e1n afectados y a\u00fan se encuentran en el rango admitido."
    }
  ],
  "metrics": {
    "cvssMetricV31": [
      {
        "source": "nvd@nist.gov",
        "type": "Primary",
        "cvssData": {
          "version": "3.1",
          "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
          "attackVector": "LOCAL",
          "attackComplexity": "LOW",
          "privilegesRequired": "LOW",
          "userInteraction": "NONE",
          "scope": "UNCHANGED",
          "confidentialityImpact": "NONE",
          "integrityImpact": "NONE",
          "availabilityImpact": "HIGH",
          "baseScore": 5.5,
          "baseSeverity": "MEDIUM"
        },
        "exploitabilityScore": 1.8,
        "impactScore": 3.6
      },
      {
        "source": "security-advisories@github.com",
        "type": "Secondary",
        "cvssData": {
          "version": "3.1",
          "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
          "attackVector": "LOCAL",
          "attackComplexity": "LOW",
          "privilegesRequired": "LOW",
          "userInteraction": "NONE",
          "scope": "UNCHANGED",
          "confidentialityImpact": "NONE",
          "integrityImpact": "NONE",
          "availabilityImpact": "HIGH",
          "baseScore": 5.5,
          "baseSeverity": "MEDIUM"
        },
        "exploitabilityScore": 1.8,
        "impactScore": 3.6
      }
    ],
    "cvssMetricV2": [
      {
        "source": "nvd@nist.gov",
        "type": "Primary",
        "cvssData": {
          "version": "2.0",
          "vectorString": "AV:L/AC:L/Au:N/C:N/I:N/A:P",
          "accessVector": "LOCAL",
          "accessComplexity": "LOW",
          "authentication": "NONE",
          "confidentialityImpact": "NONE",
          "integrityImpact": "NONE",
          "availabilityImpact": "PARTIAL",
          "baseScore": 2.1
        },
        "baseSeverity": "LOW",
        "exploitabilityScore": 3.9,
        "impactScore": 2.9,
        "acInsufInfo": false,
        "obtainAllPrivilege": false,
        "obtainUserPrivilege": false,
        "obtainOtherPrivilege": false,
        "userInteractionRequired": false
      }
    ]
  },
  "weaknesses": [
    {
      "source": "security-advisories@github.com",
      "type": "Primary",
      "description": [
        {
          "lang": "en",
          "value": "CWE-681"
        }
      ]
    }
  ],
  "configurations": [
    {
      "nodes": [
        {
          "operator": "OR",
          "negate": false,
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  "references": [
    {
      "url": "https://github.com/tensorflow/tensorflow/commit/3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d",
      "source": "security-advisories@github.com",
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      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vmjw-c2vp-p33c",
      "source": "security-advisories@github.com",
      "tags": [
        "Third Party Advisory"
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}