GSD-2022-23576

Vulnerability from gsd - Updated: 2023-12-13 01:19
Details
Tensorflow is an Open Source Machine Learning Framework. The implementation of `OpLevelCostEstimator::CalculateOutputSize` is vulnerable to an integer overflow if an attacker can create an operation which would involve tensors with large enough number of elements. We can have a large enough number of dimensions in `output_shape.dim()` or just a small number of dimensions being large enough to cause an overflow in the multiplication. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Aliases
Aliases

{
  "GSD": {
    "alias": "CVE-2022-23576",
    "description": "Tensorflow is an Open Source Machine Learning Framework. The implementation of `OpLevelCostEstimator::CalculateOutputSize` is vulnerable to an integer overflow if an attacker can create an operation which would involve tensors with large enough number of elements. We can have a large enough number of dimensions in `output_shape.dim()` or just a small number of dimensions being large enough to cause an overflow in the multiplication. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.",
    "id": "GSD-2022-23576",
    "references": [
      "https://www.suse.com/security/cve/CVE-2022-23576.html"
    ]
  },
  "gsd": {
    "metadata": {
      "exploitCode": "unknown",
      "remediation": "unknown",
      "reportConfidence": "confirmed",
      "type": "vulnerability"
    },
    "osvSchema": {
      "aliases": [
        "CVE-2022-23576"
      ],
      "details": "Tensorflow is an Open Source Machine Learning Framework. The implementation of `OpLevelCostEstimator::CalculateOutputSize` is vulnerable to an integer overflow if an attacker can create an operation which would involve tensors with large enough number of elements. We can have a large enough number of dimensions in `output_shape.dim()` or just a small number of dimensions being large enough to cause an overflow in the multiplication. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.",
      "id": "GSD-2022-23576",
      "modified": "2023-12-13T01:19:34.894860Z",
      "schema_version": "1.4.0"
    }
  },
  "namespaces": {
    "cve.org": {
      "CVE_data_meta": {
        "ASSIGNER": "security-advisories@github.com",
        "ID": "CVE-2022-23576",
        "STATE": "PUBLIC",
        "TITLE": "Integer overflow in Tensorflow"
      },
      "affects": {
        "vendor": {
          "vendor_data": [
            {
              "product": {
                "product_data": [
                  {
                    "product_name": "tensorflow",
                    "version": {
                      "version_data": [
                        {
                          "version_value": "\u003e= 2.7.0, \u003c 2.7.1"
                        },
                        {
                          "version_value": "\u003e= 2.6.0, \u003c 2.6.3"
                        },
                        {
                          "version_value": "\u003c 2.5.3"
                        }
                      ]
                    }
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                ]
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              "vendor_name": "tensorflow"
            }
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      "data_format": "MITRE",
      "data_type": "CVE",
      "data_version": "4.0",
      "description": {
        "description_data": [
          {
            "lang": "eng",
            "value": "Tensorflow is an Open Source Machine Learning Framework. The implementation of `OpLevelCostEstimator::CalculateOutputSize` is vulnerable to an integer overflow if an attacker can create an operation which would involve tensors with large enough number of elements. We can have a large enough number of dimensions in `output_shape.dim()` or just a small number of dimensions being large enough to cause an overflow in the multiplication. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range."
          }
        ]
      },
      "impact": {
        "cvss": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "HIGH",
          "baseScore": 6.5,
          "baseSeverity": "MEDIUM",
          "confidentialityImpact": "NONE",
          "integrityImpact": "NONE",
          "privilegesRequired": "LOW",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
          "version": "3.1"
        }
      },
      "problemtype": {
        "problemtype_data": [
          {
            "description": [
              {
                "lang": "eng",
                "value": "CWE-190: Integer Overflow or Wraparound"
              }
            ]
          }
        ]
      },
      "references": {
        "reference_data": [
          {
            "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wm93-f238-7v37",
            "refsource": "CONFIRM",
            "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wm93-f238-7v37"
          },
          {
            "name": "https://github.com/tensorflow/tensorflow/commit/b9bd6cfd1c50e6807846af9a86f9b83cafc9c8ae",
            "refsource": "MISC",
            "url": "https://github.com/tensorflow/tensorflow/commit/b9bd6cfd1c50e6807846af9a86f9b83cafc9c8ae"
          },
          {
            "name": "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L1598-L1617",
            "refsource": "MISC",
            "url": "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L1598-L1617"
          }
        ]
      },
      "source": {
        "advisory": "GHSA-wm93-f238-7v37",
        "discovery": "UNKNOWN"
      }
    },
    "gitlab.com": {
      "advisories": [
        {
          "affected_range": "\u003c2.5.3||\u003e=2.6.0,\u003c2.6.3||==2.7.0",
          "affected_versions": "All versions before 2.5.3, all versions starting from 2.6.0 before 2.6.3, version 2.7.0",
          "cvss_v2": "AV:N/AC:L/Au:S/C:N/I:N/A:P",
          "cvss_v3": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
          "cwe_ids": [
            "CWE-1035",
            "CWE-190",
            "CWE-937"
          ],
          "date": "2022-02-11",
          "description": "Tensorflow is an Open Source Machine Learning Framework. The implementation of `OpLevelCostEstimator::CalculateOutputSize` is vulnerable to an integer overflow if an attacker can create an operation which would involve tensors with large enough number of elements. We can have a large enough number of dimensions in `output_shape.dim` or just a small number of dimensions being large enough to cause an overflow in the multiplication. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.",
          "fixed_versions": [
            "2.5.3",
            "2.6.3",
            "2.7.1"
          ],
          "identifier": "CVE-2022-23576",
          "identifiers": [
            "GHSA-wm93-f238-7v37",
            "CVE-2022-23576"
          ],
          "not_impacted": "All versions starting from 2.5.3 before 2.6.0, all versions starting from 2.6.3 before 2.7.0, all versions after 2.7.0",
          "package_slug": "pypi/tensorflow-cpu",
          "pubdate": "2022-02-10",
          "solution": "Upgrade to versions 2.5.3, 2.6.3, 2.7.1 or above.",
          "title": "Integer Overflow or Wraparound",
          "urls": [
            "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wm93-f238-7v37",
            "https://github.com/tensorflow/tensorflow/commit/b9bd6cfd1c50e6807846af9a86f9b83cafc9c8ae",
            "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L1598-L1617",
            "https://nvd.nist.gov/vuln/detail/CVE-2022-23576",
            "https://github.com/advisories/GHSA-wm93-f238-7v37"
          ],
          "uuid": "a0bbf1b4-ee73-465c-b1ae-5b1359771450"
        },
        {
          "affected_range": "\u003c2.5.3||\u003e=2.6.0,\u003c2.6.3||==2.7.0",
          "affected_versions": "All versions before 2.5.3, all versions starting from 2.6.0 before 2.6.3, version 2.7.0",
          "cvss_v2": "AV:N/AC:L/Au:S/C:N/I:N/A:P",
          "cvss_v3": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
          "cwe_ids": [
            "CWE-1035",
            "CWE-190",
            "CWE-937"
          ],
          "date": "2022-02-11",
          "description": "Tensorflow is an Open Source Machine Learning Framework. The implementation of `OpLevelCostEstimator::CalculateOutputSize` is vulnerable to an integer overflow if an attacker can create an operation which would involve tensors with large enough number of elements. We can have a large enough number of dimensions in `output_shape.dim` or just a small number of dimensions being large enough to cause an overflow in the multiplication. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.",
          "fixed_versions": [
            "2.5.3",
            "2.6.3",
            "2.7.1"
          ],
          "identifier": "CVE-2022-23576",
          "identifiers": [
            "GHSA-wm93-f238-7v37",
            "CVE-2022-23576"
          ],
          "not_impacted": "All versions starting from 2.5.3 before 2.6.0, all versions starting from 2.6.3 before 2.7.0, all versions after 2.7.0",
          "package_slug": "pypi/tensorflow-gpu",
          "pubdate": "2022-02-10",
          "solution": "Upgrade to versions 2.5.3, 2.6.3, 2.7.1 or above.",
          "title": "Integer Overflow or Wraparound",
          "urls": [
            "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wm93-f238-7v37",
            "https://github.com/tensorflow/tensorflow/commit/b9bd6cfd1c50e6807846af9a86f9b83cafc9c8ae",
            "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L1598-L1617",
            "https://nvd.nist.gov/vuln/detail/CVE-2022-23576",
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          ],
          "uuid": "f087b602-fc7f-4e8a-8f80-cf3b16dc3e24"
        },
        {
          "affected_range": "\u003c=2.5.2||\u003e=2.6.0,\u003c=2.6.2||==2.7.0",
          "affected_versions": "All versions up to 2.5.2, all versions starting from 2.6.0 up to 2.6.2, version 2.7.0",
          "cvss_v2": "AV:N/AC:L/Au:S/C:N/I:N/A:P",
          "cvss_v3": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
          "cwe_ids": [
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            "CWE-190",
            "CWE-937"
          ],
          "date": "2022-02-10",
          "description": "Tensorflow is an Open Source Machine Learning Framework. The implementation of `OpLevelCostEstimator::CalculateOutputSize` is vulnerable to an integer overflow if an attacker can create an operation which would involve tensors with large enough number of elements. We can have a large enough number of dimensions in `output_shape.dim()` or just a small number of dimensions being large enough to cause an overflow in the multiplication. The fix will be included in TensorFlow We will also cherrypick this commit on TensorFlow, TensorFlow, and TensorFlow, as these are also affected and still in supported range.",
          "fixed_versions": [
            "2.5.3",
            "2.6.3",
            "2.7.1"
          ],
          "identifier": "CVE-2022-23576",
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            "CVE-2022-23576",
            "GHSA-wm93-f238-7v37"
          ],
          "not_impacted": "All versions after 2.5.2 before 2.6.0, all versions after 2.6.2 before 2.7.0, all versions after 2.7.0",
          "package_slug": "pypi/tensorflow",
          "pubdate": "2022-02-04",
          "solution": "Upgrade to versions 2.5.3, 2.6.3, 2.7.1 or above.",
          "title": "Integer Overflow or Wraparound",
          "urls": [
            "https://nvd.nist.gov/vuln/detail/CVE-2022-23576",
            "https://github.com/tensorflow/tensorflow/commit/b9bd6cfd1c50e6807846af9a86f9b83cafc9c8ae",
            "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L1598-L1617",
            "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wm93-f238-7v37"
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                "cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
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        "description": {
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              "value": "Tensorflow is an Open Source Machine Learning Framework. The implementation of `OpLevelCostEstimator::CalculateOutputSize` is vulnerable to an integer overflow if an attacker can create an operation which would involve tensors with large enough number of elements. We can have a large enough number of dimensions in `output_shape.dim()` or just a small number of dimensions being large enough to cause an overflow in the multiplication. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range."
            }
          ]
        },
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              "name": "https://github.com/tensorflow/tensorflow/commit/b9bd6cfd1c50e6807846af9a86f9b83cafc9c8ae",
              "refsource": "MISC",
              "tags": [
                "Patch",
                "Third Party Advisory"
              ],
              "url": "https://github.com/tensorflow/tensorflow/commit/b9bd6cfd1c50e6807846af9a86f9b83cafc9c8ae"
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              "name": "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L1598-L1617",
              "refsource": "MISC",
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              "url": "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L1598-L1617"
            },
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                "Third Party Advisory"
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              "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wm93-f238-7v37"
            }
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      },
      "impact": {
        "baseMetricV2": {
          "acInsufInfo": false,
          "cvssV2": {
            "accessComplexity": "LOW",
            "accessVector": "NETWORK",
            "authentication": "SINGLE",
            "availabilityImpact": "PARTIAL",
            "baseScore": 4.0,
            "confidentialityImpact": "NONE",
            "integrityImpact": "NONE",
            "vectorString": "AV:N/AC:L/Au:S/C:N/I:N/A:P",
            "version": "2.0"
          },
          "exploitabilityScore": 8.0,
          "impactScore": 2.9,
          "obtainAllPrivilege": false,
          "obtainOtherPrivilege": false,
          "obtainUserPrivilege": false,
          "severity": "MEDIUM",
          "userInteractionRequired": false
        },
        "baseMetricV3": {
          "cvssV3": {
            "attackComplexity": "LOW",
            "attackVector": "NETWORK",
            "availabilityImpact": "HIGH",
            "baseScore": 6.5,
            "baseSeverity": "MEDIUM",
            "confidentialityImpact": "NONE",
            "integrityImpact": "NONE",
            "privilegesRequired": "LOW",
            "scope": "UNCHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
            "version": "3.1"
          },
          "exploitabilityScore": 2.8,
          "impactScore": 3.6
        }
      },
      "lastModifiedDate": "2022-02-10T15:10Z",
      "publishedDate": "2022-02-04T23:15Z"
    }
  }
}


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  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
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