gsd-2022-35966
Vulnerability from gsd
Modified
2023-12-13 01:19
Details
TensorFlow is an open source platform for machine learning. If `QuantizedAvgPool` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 7cdf9d4d2083b739ec81cfdace546b0c99f50622. 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.
Aliases
Aliases
CVE-2022-35966


To clipboard 

{
  "GSD": {
    "alias": "CVE-2022-35966",
    "description": "TensorFlow is an open source platform for machine learning. If `QuantizedAvgPool` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 7cdf9d4d2083b739ec81cfdace546b0c99f50622. 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-2022-35966",
    "references": [
      "https://www.suse.com/security/cve/CVE-2022-35966.html"
    ]
  },
  "gsd": {
    "metadata": {
      "exploitCode": "unknown",
      "remediation": "unknown",
      "reportConfidence": "confirmed",
      "type": "vulnerability"
    },
    "osvSchema": {
      "aliases": [
        "CVE-2022-35966"
      ],
      "details": "TensorFlow is an open source platform for machine learning. If `QuantizedAvgPool` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 7cdf9d4d2083b739ec81cfdace546b0c99f50622. 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-2022-35966",
      "modified": "2023-12-13T01:19:33.656674Z",
      "schema_version": "1.4.0"
    }
  },
  "namespaces": {
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        "ASSIGNER": "security-advisories@github.com",
        "ID": "CVE-2022-35966",
        "STATE": "PUBLIC",
        "TITLE": "Segfault in `QuantizedAvgPool` in TensorFlow"
      },
      "affects": {
        "vendor": {
          "vendor_data": [
            {
              "product": {
                "product_data": [
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                    "product_name": "tensorflow",
                    "version": {
                      "version_data": [
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                          "version_value": "\u003e= 2.8.0, \u003c 2.8.1"
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            "value": "TensorFlow is an open source platform for machine learning. If `QuantizedAvgPool` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 7cdf9d4d2083b739ec81cfdace546b0c99f50622. 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": [
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            "refsource": "MISC",
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        "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": [
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            "CWE-20",
            "CWE-937"
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          "description": "TensorFlow is an open source platform for machine learning. If `QuantizedAvgPool` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 7cdf9d4d2083b739ec81cfdace546b0c99f50622. 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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          "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": "Improper Input Validation",
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            "CWE-937"
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          "date": "2022-09-16",
          "description": "TensorFlow is an open source platform for machine learning. If `QuantizedAvgPool` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 7cdf9d4d2083b739ec81cfdace546b0c99f50622. 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",
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          ],
          "identifier": "CVE-2022-35966",
          "identifiers": [
            "GHSA-4w68-4x85-mjj9",
            "CVE-2022-35966"
          ],
          "not_impacted": "All versions starting from 2.7.2 before 2.8.0, all versions starting from 2.8.1 before 2.9.0, all versions starting from 2.9.1",
          "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": "Improper Input Validation",
          "urls": [
            "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4w68-4x85-mjj9",
            "https://github.com/tensorflow/tensorflow/commit/7cdf9d4d2083b739ec81cfdace546b0c99f50622",
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          "uuid": "35c517cc-d5a4-4c00-ad70-c175a84f9350"
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          "date": "2022-09-20",
          "description": "TensorFlow is an open source platform for machine learning. If `QuantizedAvgPool` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 7cdf9d4d2083b739ec81cfdace546b0c99f50622. 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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            "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": "Improper Input Validation",
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            "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4w68-4x85-mjj9",
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          "uuid": "ca0c6289-6050-475d-ac76-2f3f3ad42bf3"
        }
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    },
    "nvd.nist.gov": {
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      "impact": {
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            "baseSeverity": "HIGH",
            "confidentialityImpact": "NONE",
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            "privilegesRequired": "NONE",
            "scope": "UNCHANGED",
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          "impactScore": 3.6
        }
      },
      "lastModifiedDate": "2022-09-20T20:06Z",
      "publishedDate": "2022-09-16T21:15Z"
    }
  }
}


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