GSD-2022-35996

Vulnerability from gsd - Updated: 2023-12-13 01:19
Details
TensorFlow is an open source platform for machine learning. If `Conv2D` is given empty `input` and the `filter` and `padding` sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 611d80db29dd7b0cfb755772c69d60ae5bca05f9. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
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Aliases
CVE-2022-35996
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{
  "GSD": {
    "alias": "CVE-2022-35996",
    "description": "TensorFlow is an open source platform for machine learning. If `Conv2D` is given empty `input` and the `filter` and `padding` sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 611d80db29dd7b0cfb755772c69d60ae5bca05f9. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.",
    "id": "GSD-2022-35996",
    "references": [
      "https://www.suse.com/security/cve/CVE-2022-35996.html"
    ]
  },
  "gsd": {
    "metadata": {
      "exploitCode": "unknown",
      "remediation": "unknown",
      "reportConfidence": "confirmed",
      "type": "vulnerability"
    },
    "osvSchema": {
      "aliases": [
        "CVE-2022-35996"
      ],
      "details": "TensorFlow is an open source platform for machine learning. If `Conv2D` is given empty `input` and the `filter` and `padding` sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 611d80db29dd7b0cfb755772c69d60ae5bca05f9. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.",
      "id": "GSD-2022-35996",
      "modified": "2023-12-13T01:19:33.526658Z",
      "schema_version": "1.4.0"
    }
  },
  "namespaces": {
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        "ASSIGNER": "security-advisories@github.com",
        "ID": "CVE-2022-35996",
        "STATE": "PUBLIC",
        "TITLE": "Floating point exception in `Conv2D` in TensorFlow"
      },
      "affects": {
        "vendor": {
          "vendor_data": [
            {
              "product": {
                "product_data": [
                  {
                    "product_name": "tensorflow",
                    "version": {
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      "description": {
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            "value": "TensorFlow is an open source platform for machine learning. If `Conv2D` is given empty `input` and the `filter` and `padding` sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 611d80db29dd7b0cfb755772c69d60ae5bca05f9. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue."
          }
        ]
      },
      "impact": {
        "cvss": {
          "attackComplexity": "HIGH",
          "attackVector": "NETWORK",
          "availabilityImpact": "HIGH",
          "baseScore": 5.9,
          "baseSeverity": "MEDIUM",
          "confidentialityImpact": "NONE",
          "integrityImpact": "NONE",
          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H",
          "version": "3.1"
        }
      },
      "problemtype": {
        "problemtype_data": [
          {
            "description": [
              {
                "lang": "eng",
                "value": "CWE-369: Divide By Zero"
              }
            ]
          }
        ]
      },
      "references": {
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          {
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          },
          {
            "name": "https://github.com/tensorflow/tensorflow/commit/611d80db29dd7b0cfb755772c69d60ae5bca05f9",
            "refsource": "MISC",
            "url": "https://github.com/tensorflow/tensorflow/commit/611d80db29dd7b0cfb755772c69d60ae5bca05f9"
          }
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      "source": {
        "advisory": "GHSA-q5jv-m6qw-5g37",
        "discovery": "UNKNOWN"
      }
    },
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        {
          "affected_range": "\u003c2.7.2||\u003e=2.8.0,\u003c2.8.1||\u003e=2.9.0,\u003c2.9.1",
          "affected_versions": "All versions before 2.7.2, all versions starting from 2.8.0 before 2.8.1, all versions starting from 2.9.0 before 2.9.1",
          "cwe_ids": [
            "CWE-1035",
            "CWE-369",
            "CWE-937"
          ],
          "date": "2022-09-16",
          "description": "TensorFlow is an open source platform for machine learning. If `Conv2D` is given empty `input` and the `filter` and `padding` sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 611d80db29dd7b0cfb755772c69d60ae5bca05f9. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.",
          "fixed_versions": [
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            "2.8.1",
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            "CVE-2022-35996"
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          "package_slug": "pypi/tensorflow-cpu",
          "pubdate": "2022-09-16",
          "solution": "Upgrade to versions 2.7.2, 2.8.1, 2.9.1 or above.",
          "title": "Divide By Zero",
          "urls": [
            "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q5jv-m6qw-5g37",
            "https://github.com/tensorflow/tensorflow/commit/611d80db29dd7b0cfb755772c69d60ae5bca05f9",
            "https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0",
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          "affected_versions": "All versions before 2.7.2, all versions starting from 2.8.0 before 2.8.1, all versions starting from 2.9.0 before 2.9.1",
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            "CWE-369",
            "CWE-937"
          ],
          "date": "2022-09-16",
          "description": "TensorFlow is an open source platform for machine learning. If `Conv2D` is given empty `input` and the `filter` and `padding` sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 611d80db29dd7b0cfb755772c69d60ae5bca05f9. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.",
          "fixed_versions": [
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            "2.8.1",
            "2.9.1"
          ],
          "identifier": "CVE-2022-35996",
          "identifiers": [
            "GHSA-q5jv-m6qw-5g37",
            "CVE-2022-35996"
          ],
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          "package_slug": "pypi/tensorflow-gpu",
          "pubdate": "2022-09-16",
          "solution": "Upgrade to versions 2.7.2, 2.8.1, 2.9.1 or above.",
          "title": "Divide By Zero",
          "urls": [
            "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q5jv-m6qw-5g37",
            "https://github.com/tensorflow/tensorflow/commit/611d80db29dd7b0cfb755772c69d60ae5bca05f9",
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          "description": "TensorFlow is an open source platform for machine learning. If `Conv2D` is given empty `input` and the `filter` and `padding` sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 611d80db29dd7b0cfb755772c69d60ae5bca05f9. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.",
          "fixed_versions": [
            "2.7.2",
            "2.8.1",
            "2.9.1"
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          "package_slug": "pypi/tensorflow",
          "pubdate": "2022-09-16",
          "solution": "Upgrade to versions 2.7.2, 2.8.1, 2.9.1 or above.",
          "title": "Divide By Zero",
          "urls": [
            "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q5jv-m6qw-5g37",
            "https://github.com/tensorflow/tensorflow/commit/611d80db29dd7b0cfb755772c69d60ae5bca05f9",
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    },
    "nvd.nist.gov": {
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            "attackVector": "NETWORK",
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            "baseScore": 7.5,
            "baseSeverity": "HIGH",
            "confidentialityImpact": "NONE",
            "integrityImpact": "NONE",
            "privilegesRequired": "NONE",
            "scope": "UNCHANGED",
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          "impactScore": 3.6
        }
      },
      "lastModifiedDate": "2022-09-20T14:49Z",
      "publishedDate": "2022-09-16T23:15Z"
    }
  }
}


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  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
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  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.



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