{
  "GSD": {
    "alias": "CVE-2021-29566",
    "description": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can write outside the bounds of heap allocated arrays by passing invalid arguments to `tf.raw_ops.Dilation2DBackpropInput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/afd954e65f15aea4d438d0a219136fc4a63a573d/tensorflow/core/kernels/dilation_ops.cc#L321-L322) does not validate before writing to the output array. The values for `h_out` and `w_out` are guaranteed to be in range for `out_backprop` (as they are loop indices bounded by the size of the array). However, there are no similar guarantees relating `h_in_max`/`w_in_max` and `in_backprop`. 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.",
    "id": "GSD-2021-29566",
    "references": [
      "https://www.suse.com/security/cve/CVE-2021-29566.html",
      "https://security.archlinux.org/CVE-2021-29566"
    ]
  },
  "gsd": {
    "metadata": {
      "exploitCode": "unknown",
      "remediation": "unknown",
      "reportConfidence": "confirmed",
      "type": "vulnerability"
    },
    "osvSchema": {
      "aliases": [
        "CVE-2021-29566"
      ],
      "details": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can write outside the bounds of heap allocated arrays by passing invalid arguments to `tf.raw_ops.Dilation2DBackpropInput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/afd954e65f15aea4d438d0a219136fc4a63a573d/tensorflow/core/kernels/dilation_ops.cc#L321-L322) does not validate before writing to the output array. The values for `h_out` and `w_out` are guaranteed to be in range for `out_backprop` (as they are loop indices bounded by the size of the array). However, there are no similar guarantees relating `h_in_max`/`w_in_max` and `in_backprop`. 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.",
      "id": "GSD-2021-29566",
      "modified": "2023-12-13T01:23:36.690119Z",
      "schema_version": "1.4.0"
    }
  },
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        "ID": "CVE-2021-29566",
        "STATE": "PUBLIC",
        "TITLE": "Heap OOB access in `Dilation2DBackpropInput`"
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      "affects": {
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            "lang": "eng",
            "value": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can write outside the bounds of heap allocated arrays by passing invalid arguments to `tf.raw_ops.Dilation2DBackpropInput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/afd954e65f15aea4d438d0a219136fc4a63a573d/tensorflow/core/kernels/dilation_ops.cc#L321-L322) does not validate before writing to the output array. The values for `h_out` and `w_out` are guaranteed to be in range for `out_backprop` (as they are loop indices bounded by the size of the array). However, there are no similar guarantees relating `h_in_max`/`w_in_max` and `in_backprop`. 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."
          }
        ]
      },
      "impact": {
        "cvss": {
          "attackComplexity": "HIGH",
          "attackVector": "LOCAL",
          "availabilityImpact": "LOW",
          "baseScore": 2.5,
          "baseSeverity": "LOW",
          "confidentialityImpact": "NONE",
          "integrityImpact": "NONE",
          "privilegesRequired": "LOW",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L",
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        "problemtype_data": [
          {
            "description": [
              {
                "lang": "eng",
                "value": "CWE-787: Out-of-bounds Write"
              }
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          {
            "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pvrc-hg3f-58r6",
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            "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pvrc-hg3f-58r6"
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          {
            "name": "https://github.com/tensorflow/tensorflow/commit/3f6fe4dfef6f57e768260b48166c27d148f3015f",
            "refsource": "MISC",
            "url": "https://github.com/tensorflow/tensorflow/commit/3f6fe4dfef6f57e768260b48166c27d148f3015f"
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      "source": {
        "advisory": "GHSA-pvrc-hg3f-58r6",
        "discovery": "UNKNOWN"
      }
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      "advisories": [
        {
          "affected_range": "\u003c2.1.4||\u003e=2.2.0,\u003c2.2.3||\u003e=2.3.0,\u003c2.3.3||\u003e=2.4.0,\u003c2.4.2",
          "affected_versions": "All versions before 2.1.4, all versions starting from 2.2.0 before 2.2.3, all versions starting from 2.3.0 before 2.3.3, all versions starting from 2.4.0 before 2.4.2",
          "cvss_v2": "AV:L/AC:L/Au:N/C:P/I:P/A:P",
          "cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
          "cwe_ids": [
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            "CWE-787",
            "CWE-937"
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          "date": "2021-05-21",
          "description": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can write outside the bounds of heap allocated arrays by passing invalid arguments to `tf.raw_ops.Dilation2DBackpropInput`. This is because the implementation does not validate before writing to the output array. The values for `h_out` and `w_out` are guaranteed to be in range for `out_backprop` (as they are loop indices bounded by the size of the array). However, there are no similar guarantees relating `h_in_max`/`w_in_max` and `in_backprop`. 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.",
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            "2.1.4",
            "2.2.3",
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          "identifier": "CVE-2021-29566",
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          "package_slug": "pypi/tensorflow-cpu",
          "pubdate": "2021-05-21",
          "solution": "Upgrade to versions 2.1.4, 2.2.3, 2.3.3, 2.4.2 or above.",
          "title": "Out-of-bounds Write",
          "urls": [
            "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pvrc-hg3f-58r6",
            "https://nvd.nist.gov/vuln/detail/CVE-2021-29566",
            "https://github.com/tensorflow/tensorflow/commit/3f6fe4dfef6f57e768260b48166c27d148f3015f",
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          "affected_versions": "All versions before 2.1.4, all versions starting from 2.2.0 before 2.2.3, all versions starting from 2.3.0 before 2.3.3, all versions starting from 2.4.0 before 2.4.2",
          "cvss_v2": "AV:L/AC:L/Au:N/C:P/I:P/A:P",
          "cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
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            "CWE-937"
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          "date": "2021-05-21",
          "description": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can write outside the bounds of heap allocated arrays by passing invalid arguments to `tf.raw_ops.Dilation2DBackpropInput`. This is because the implementation does not validate before writing to the output array. The values for `h_out` and `w_out` are guaranteed to be in range for `out_backprop` (as they are loop indices bounded by the size of the array). However, there are no similar guarantees relating `h_in_max`/`w_in_max` and `in_backprop`. 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.",
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            "2.2.3",
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          "package_slug": "pypi/tensorflow-gpu",
          "pubdate": "2021-05-21",
          "solution": "Upgrade to versions 2.1.4, 2.2.3, 2.3.3, 2.4.2 or above.",
          "title": "Out-of-bounds Write",
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          "affected_range": "\u003c=2.1.4||\u003e=2.2.0,\u003c=2.2.3||\u003e=2.3.0,\u003c=2.3.3||\u003e=2.4.0,\u003c=2.4.2",
          "affected_versions": "All versions up to 2.1.4, all versions starting from 2.2.0 up to 2.2.3, all versions starting from 2.3.0 up to 2.3.3, all versions starting from 2.4.0 up to 2.4.2",
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          "cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
          "cwe_ids": [
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            "CWE-787",
            "CWE-937"
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          "date": "2021-07-26",
          "description": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can write outside the bounds of heap allocated arrays by passing invalid arguments to `tf.raw_ops.Dilation2DBackpropInput`. This is because the implementation does not validate before writing to the output array. The values for `h_out` and `w_out` are guaranteed to be in range for `out_backprop` (as they are loop indices bounded by the size of the array). However, there are no similar guarantees relating `h_in_max`/`w_in_max` and `in_backprop`.",
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          "identifier": "CVE-2021-29566",
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          "package_slug": "pypi/tensorflow",
          "pubdate": "2021-05-14",
          "solution": "Upgrade to version 2.5.0 or above.",
          "title": "Out-of-bounds Write",
          "urls": [
            "https://nvd.nist.gov/vuln/detail/CVE-2021-29566"
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              "value": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can write outside the bounds of heap allocated arrays by passing invalid arguments to `tf.raw_ops.Dilation2DBackpropInput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/afd954e65f15aea4d438d0a219136fc4a63a573d/tensorflow/core/kernels/dilation_ops.cc#L321-L322) does not validate before writing to the output array. The values for `h_out` and `w_out` are guaranteed to be in range for `out_backprop` (as they are loop indices bounded by the size of the array). However, there are no similar guarantees relating `h_in_max`/`w_in_max` and `in_backprop`. 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."
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            "accessVector": "LOCAL",
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      },
      "lastModifiedDate": "2021-07-26T16:20Z",
      "publishedDate": "2021-05-14T20:15Z"
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}