gsd-2021-29550
Vulnerability from gsd
Modified
2023-12-13 01:23
Details
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.FractionalAvgPool`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L85-L89) computes a divisor quantity by dividing two user controlled values. The user controls the values of `input_size[i]` and `pooling_ratio_[i]` (via the `value.shape()` and `pooling_ratio` arguments). If the value in `input_size[i]` is smaller than the `pooling_ratio_[i]`, then the floor operation results in `output_size[i]` being 0. The `DCHECK_GT` line is a no-op outside of debug mode, so in released versions of TF this does not trigger. Later, these computed values are used as arguments(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L96-L99) to `GeneratePoolingSequence`(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_pool_common.cc#L100-L108). There, the first computation is a division in a modulo operation. Since `output_length` can be 0, this results in runtime crashing. 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.
Aliases
Aliases
CVE-2021-29550


To clipboard 

{
  "GSD": {
    "alias": "CVE-2021-29550",
    "description": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.FractionalAvgPool`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L85-L89) computes a divisor quantity by dividing two user controlled values. The user controls the values of `input_size[i]` and `pooling_ratio_[i]` (via the `value.shape()` and `pooling_ratio` arguments). If the value in `input_size[i]` is smaller than the `pooling_ratio_[i]`, then the floor operation results in `output_size[i]` being 0. The `DCHECK_GT` line is a no-op outside of debug mode, so in released versions of TF this does not trigger. Later, these computed values are used as arguments(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L96-L99) to `GeneratePoolingSequence`(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_pool_common.cc#L100-L108). There, the first computation is a division in a modulo operation. Since `output_length` can be 0, this results in runtime crashing. 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-2021-29550",
    "references": [
      "https://www.suse.com/security/cve/CVE-2021-29550.html",
      "https://security.archlinux.org/CVE-2021-29550"
    ]
  },
  "gsd": {
    "metadata": {
      "exploitCode": "unknown",
      "remediation": "unknown",
      "reportConfidence": "confirmed",
      "type": "vulnerability"
    },
    "osvSchema": {
      "aliases": [
        "CVE-2021-29550"
      ],
      "details": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.FractionalAvgPool`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L85-L89) computes a divisor quantity by dividing two user controlled values. The user controls the values of `input_size[i]` and `pooling_ratio_[i]` (via the `value.shape()` and `pooling_ratio` arguments). If the value in `input_size[i]` is smaller than the `pooling_ratio_[i]`, then the floor operation results in `output_size[i]` being 0. The `DCHECK_GT` line is a no-op outside of debug mode, so in released versions of TF this does not trigger. Later, these computed values are used as arguments(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L96-L99) to `GeneratePoolingSequence`(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_pool_common.cc#L100-L108). There, the first computation is a division in a modulo operation. Since `output_length` can be 0, this results in runtime crashing. 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-2021-29550",
      "modified": "2023-12-13T01:23:36.864451Z",
      "schema_version": "1.4.0"
    }
  },
  "namespaces": {
    "cve.org": {
      "CVE_data_meta": {
        "ASSIGNER": "security-advisories@github.com",
        "ID": "CVE-2021-29550",
        "STATE": "PUBLIC",
        "TITLE": "Division by 0 in `FractionalAvgPool`"
      },
      "affects": {
        "vendor": {
          "vendor_data": [
            {
              "product": {
                "product_data": [
                  {
                    "product_name": "tensorflow",
                    "version": {
                      "version_data": [
                        {
                          "version_value": "\u003c 2.1.4"
                        },
                        {
                          "version_value": "\u003e= 2.2.0, \u003c 2.2.3"
                        },
                        {
                          "version_value": "\u003e= 2.3.0, \u003c 2.3.3"
                        },
                        {
                          "version_value": "\u003e= 2.4.0, \u003c 2.4.2"
                        }
                      ]
                    }
                  }
                ]
              },
              "vendor_name": "tensorflow"
            }
          ]
        }
      },
      "data_format": "MITRE",
      "data_type": "CVE",
      "data_version": "4.0",
      "description": {
        "description_data": [
          {
            "lang": "eng",
            "value": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.FractionalAvgPool`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L85-L89) computes a divisor quantity by dividing two user controlled values. The user controls the values of `input_size[i]` and `pooling_ratio_[i]` (via the `value.shape()` and `pooling_ratio` arguments). If the value in `input_size[i]` is smaller than the `pooling_ratio_[i]`, then the floor operation results in `output_size[i]` being 0. The `DCHECK_GT` line is a no-op outside of debug mode, so in released versions of TF this does not trigger. Later, these computed values are used as arguments(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L96-L99) to `GeneratePoolingSequence`(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_pool_common.cc#L100-L108). There, the first computation is a division in a modulo operation. Since `output_length` can be 0, this results in runtime crashing. 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",
          "version": "3.1"
        }
      },
      "problemtype": {
        "problemtype_data": [
          {
            "description": [
              {
                "lang": "eng",
                "value": "CWE-369: Divide By Zero"
              }
            ]
          }
        ]
      },
      "references": {
        "reference_data": [
          {
            "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f78g-q7r4-9wcv",
            "refsource": "CONFIRM",
            "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f78g-q7r4-9wcv"
          },
          {
            "name": "https://github.com/tensorflow/tensorflow/commit/548b5eaf23685d86f722233d8fbc21d0a4aecb96",
            "refsource": "MISC",
            "url": "https://github.com/tensorflow/tensorflow/commit/548b5eaf23685d86f722233d8fbc21d0a4aecb96"
          }
        ]
      },
      "source": {
        "advisory": "GHSA-f78g-q7r4-9wcv",
        "discovery": "UNKNOWN"
      }
    },
    "gitlab.com": {
      "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:N/I:N/A:P",
          "cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
          "cwe_ids": [
            "CWE-1035",
            "CWE-369",
            "CWE-937"
          ],
          "date": "2021-05-21",
          "description": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.FractionalAvgPool`. This is because the implementation computes a divisor quantity by dividing two user controlled values. The user controls the values of `input_sizei]` and `pooling_ratio_[i `pooling_ratio` arguments). If the value in `input_sizei `pooling_ratio_i]`, then the floor operation results in `output_size[i 0. The `DCHECK_GT` line is a no-op outside of debug mode, so in released versions of TF this does not trigger. Later, these computed values are used as arguments to `GeneratePoolingSequence`. There, the first computation is a division in a modulo operation. Since `output_length` can be 0, this results in runtime crashing. 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.",
          "fixed_versions": [
            "2.1.4",
            "2.2.3",
            "2.3.3",
            "2.4.2"
          ],
          "identifier": "CVE-2021-29550",
          "identifiers": [
            "GHSA-f78g-q7r4-9wcv",
            "CVE-2021-29550"
          ],
          "not_impacted": "All versions starting from 2.1.4 before 2.2.0, all versions starting from 2.2.3 before 2.3.0, all versions starting from 2.3.3 before 2.4.0, all versions starting from 2.4.2",
          "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": "Divide By Zero",
          "urls": [
            "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f78g-q7r4-9wcv",
            "https://nvd.nist.gov/vuln/detail/CVE-2021-29550",
            "https://github.com/tensorflow/tensorflow/commit/548b5eaf23685d86f722233d8fbc21d0a4aecb96",
            "https://github.com/advisories/GHSA-f78g-q7r4-9wcv"
          ],
          "uuid": "8e98d9d5-2c15-4c86-8cec-6421b0ce7d1c"
        },
        {
          "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:N/I:N/A:P",
          "cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
          "cwe_ids": [
            "CWE-1035",
            "CWE-369",
            "CWE-937"
          ],
          "date": "2021-05-21",
          "description": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.FractionalAvgPool`. This is because the implementation computes a divisor quantity by dividing two user controlled values. The user controls the values of `input_sizei]` and `pooling_ratio_[i `pooling_ratio` arguments). If the value in `input_sizei `pooling_ratio_i]`, then the floor operation results in `output_size[i 0. The `DCHECK_GT` line is a no-op outside of debug mode, so in released versions of TF this does not trigger. Later, these computed values are used as arguments to `GeneratePoolingSequence`. There, the first computation is a division in a modulo operation. Since `output_length` can be 0, this results in runtime crashing. 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.",
          "fixed_versions": [
            "2.1.4",
            "2.2.3",
            "2.3.3",
            "2.4.2"
          ],
          "identifier": "CVE-2021-29550",
          "identifiers": [
            "GHSA-f78g-q7r4-9wcv",
            "CVE-2021-29550"
          ],
          "not_impacted": "All versions starting from 2.1.4 before 2.2.0, all versions starting from 2.2.3 before 2.3.0, all versions starting from 2.3.3 before 2.4.0, all versions starting from 2.4.2",
          "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": "Divide By Zero",
          "urls": [
            "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f78g-q7r4-9wcv",
            "https://nvd.nist.gov/vuln/detail/CVE-2021-29550",
            "https://github.com/tensorflow/tensorflow/commit/548b5eaf23685d86f722233d8fbc21d0a4aecb96",
            "https://github.com/advisories/GHSA-f78g-q7r4-9wcv"
          ],
          "uuid": "dade0b49-9a9d-4bd9-8100-fc6619a4a0cd"
        },
        {
          "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",
          "cvss_v2": "AV:L/AC:L/Au:N/C:N/I:N/A:P",
          "cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
          "cwe_ids": [
            "CWE-1035",
            "CWE-369",
            "CWE-937"
          ],
          "date": "2021-07-27",
          "description": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.FractionalAvgPool`.",
          "fixed_versions": [
            "2.5.0"
          ],
          "identifier": "CVE-2021-29550",
          "identifiers": [
            "CVE-2021-29550",
            "GHSA-f78g-q7r4-9wcv"
          ],
          "not_impacted": "All versions after 2.1.4 before 2.2.0, all versions after 2.2.3 before 2.3.0, all versions after 2.3.3 before 2.4.0, all versions after 2.4.2",
          "package_slug": "pypi/tensorflow",
          "pubdate": "2021-05-14",
          "solution": "Upgrade to version 2.5.0 or above.",
          "title": "Divide By Zero",
          "urls": [
            "https://nvd.nist.gov/vuln/detail/CVE-2021-29550"
          ],
          "uuid": "17e85ba6-525e-47ad-a6f0-0b4a5c7c03c4"
        }
      ]
    },
    "nvd.nist.gov": {
      "configurations": {
        "CVE_data_version": "4.0",
        "nodes": [
          {
            "children": [],
            "cpe_match": [
              {
                "cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
                "cpe_name": [],
                "versionEndExcluding": "2.1.4",
                "vulnerable": true
              },
              {
                "cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
                "cpe_name": [],
                "versionEndExcluding": "2.2.3",
                "versionStartIncluding": "2.2.0",
                "vulnerable": true
              },
              {
                "cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
                "cpe_name": [],
                "versionEndExcluding": "2.3.3",
                "versionStartIncluding": "2.3.0",
                "vulnerable": true
              },
              {
                "cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
                "cpe_name": [],
                "versionEndExcluding": "2.4.2",
                "versionStartIncluding": "2.4.0",
                "vulnerable": true
              }
            ],
            "operator": "OR"
          }
        ]
      },
      "cve": {
        "CVE_data_meta": {
          "ASSIGNER": "security-advisories@github.com",
          "ID": "CVE-2021-29550"
        },
        "data_format": "MITRE",
        "data_type": "CVE",
        "data_version": "4.0",
        "description": {
          "description_data": [
            {
              "lang": "en",
              "value": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.FractionalAvgPool`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L85-L89) computes a divisor quantity by dividing two user controlled values. The user controls the values of `input_size[i]` and `pooling_ratio_[i]` (via the `value.shape()` and `pooling_ratio` arguments). If the value in `input_size[i]` is smaller than the `pooling_ratio_[i]`, then the floor operation results in `output_size[i]` being 0. The `DCHECK_GT` line is a no-op outside of debug mode, so in released versions of TF this does not trigger. Later, these computed values are used as arguments(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L96-L99) to `GeneratePoolingSequence`(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_pool_common.cc#L100-L108). There, the first computation is a division in a modulo operation. Since `output_length` can be 0, this results in runtime crashing. 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."
            }
          ]
        },
        "problemtype": {
          "problemtype_data": [
            {
              "description": [
                {
                  "lang": "en",
                  "value": "CWE-369"
                }
              ]
            }
          ]
        },
        "references": {
          "reference_data": [
            {
              "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f78g-q7r4-9wcv",
              "refsource": "CONFIRM",
              "tags": [
                "Exploit",
                "Patch",
                "Third Party Advisory"
              ],
              "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f78g-q7r4-9wcv"
            },
            {
              "name": "https://github.com/tensorflow/tensorflow/commit/548b5eaf23685d86f722233d8fbc21d0a4aecb96",
              "refsource": "MISC",
              "tags": [
                "Patch",
                "Third Party Advisory"
              ],
              "url": "https://github.com/tensorflow/tensorflow/commit/548b5eaf23685d86f722233d8fbc21d0a4aecb96"
            }
          ]
        }
      },
      "impact": {
        "baseMetricV2": {
          "acInsufInfo": false,
          "cvssV2": {
            "accessComplexity": "LOW",
            "accessVector": "LOCAL",
            "authentication": "NONE",
            "availabilityImpact": "PARTIAL",
            "baseScore": 2.1,
            "confidentialityImpact": "NONE",
            "integrityImpact": "NONE",
            "vectorString": "AV:L/AC:L/Au:N/C:N/I:N/A:P",
            "version": "2.0"
          },
          "exploitabilityScore": 3.9,
          "impactScore": 2.9,
          "obtainAllPrivilege": false,
          "obtainOtherPrivilege": false,
          "obtainUserPrivilege": false,
          "severity": "LOW",
          "userInteractionRequired": false
        },
        "baseMetricV3": {
          "cvssV3": {
            "attackComplexity": "LOW",
            "attackVector": "LOCAL",
            "availabilityImpact": "HIGH",
            "baseScore": 5.5,
            "baseSeverity": "MEDIUM",
            "confidentialityImpact": "NONE",
            "integrityImpact": "NONE",
            "privilegesRequired": "LOW",
            "scope": "UNCHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
            "version": "3.1"
          },
          "exploitabilityScore": 1.8,
          "impactScore": 3.6
        }
      },
      "lastModifiedDate": "2021-07-27T17:19Z",
      "publishedDate": "2021-05-14T20:15Z"
    }
  }
}


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