gsd-2020-15265
Vulnerability from gsd
Modified
2023-12-13 01:21
Details
In Tensorflow before version 2.4.0, an attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dim_size only does a DCHECK to validate the argument and then uses it to access the corresponding element of an array. Since in normal builds, `DCHECK`-like macros are no-ops, this results in segfault and access out of bounds of the array. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.
Aliases
Aliases
CVE-2020-15265


To clipboard 

{
  "GSD": {
    "alias": "CVE-2020-15265",
    "description": "In Tensorflow before version 2.4.0, an attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dim_size only does a DCHECK to validate the argument and then uses it to access the corresponding element of an array. Since in normal builds, `DCHECK`-like macros are no-ops, this results in segfault and access out of bounds of the array. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.",
    "id": "GSD-2020-15265",
    "references": [
      "https://security.archlinux.org/CVE-2020-15265"
    ]
  },
  "gsd": {
    "metadata": {
      "exploitCode": "unknown",
      "remediation": "unknown",
      "reportConfidence": "confirmed",
      "type": "vulnerability"
    },
    "osvSchema": {
      "aliases": [
        "CVE-2020-15265"
      ],
      "details": "In Tensorflow before version 2.4.0, an attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dim_size only does a DCHECK to validate the argument and then uses it to access the corresponding element of an array. Since in normal builds, `DCHECK`-like macros are no-ops, this results in segfault and access out of bounds of the array. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.",
      "id": "GSD-2020-15265",
      "modified": "2023-12-13T01:21:43.261753Z",
      "schema_version": "1.4.0"
    }
  },
  "namespaces": {
    "cve.org": {
      "CVE_data_meta": {
        "ASSIGNER": "security-advisories@github.com",
        "ID": "CVE-2020-15265",
        "STATE": "PUBLIC",
        "TITLE": "Segfault in Tensorflow"
      },
      "affects": {
        "vendor": {
          "vendor_data": [
            {
              "product": {
                "product_data": [
                  {
                    "product_name": "tensorflow",
                    "version": {
                      "version_data": [
                        {
                          "version_value": "\u003c 2.4.0"
                        }
                      ]
                    }
                  }
                ]
              },
              "vendor_name": "tensorflow"
            }
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      "description": {
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          {
            "lang": "eng",
            "value": "In Tensorflow before version 2.4.0, an attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dim_size only does a DCHECK to validate the argument and then uses it to access the corresponding element of an array. Since in normal builds, `DCHECK`-like macros are no-ops, this results in segfault and access out of bounds of the array. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved."
          }
        ]
      },
      "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-125 Out-of-bounds Read"
              }
            ]
          }
        ]
      },
      "references": {
        "reference_data": [
          {
            "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rrfp-j2mp-hq9c",
            "refsource": "CONFIRM",
            "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rrfp-j2mp-hq9c"
          },
          {
            "name": "https://github.com/tensorflow/tensorflow/issues/42105",
            "refsource": "MISC",
            "url": "https://github.com/tensorflow/tensorflow/issues/42105"
          },
          {
            "name": "https://github.com/tensorflow/tensorflow/commit/eccb7ec454e6617738554a255d77f08e60ee0808",
            "refsource": "MISC",
            "url": "https://github.com/tensorflow/tensorflow/commit/eccb7ec454e6617738554a255d77f08e60ee0808"
          }
        ]
      },
      "source": {
        "advisory": "GHSA-rrfp-j2mp-hq9c",
        "discovery": "UNKNOWN"
      }
    },
    "gitlab.com": {
      "advisories": [
        {
          "affected_range": "\u003c2.4.0",
          "affected_versions": "All versions before 2.4.0",
          "cvss_v2": "AV:N/AC:L/Au:N/C:N/I:N/A:P",
          "cvss_v3": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
          "cwe_ids": [
            "CWE-1035",
            "CWE-125",
            "CWE-937"
          ],
          "date": "2020-11-03",
          "description": "In Tensorflow, an attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, `dim_size` only does a `DCHECK` to validate the argument and then uses it to access the corresponding element of an array. Since in normal builds, `DCHECK`-like macros are no-ops, this results in segfault and access out-of-bounds of the array.",
          "fixed_versions": [
            "2.4.0"
          ],
          "identifier": "CVE-2020-15265",
          "identifiers": [
            "CVE-2020-15265",
            "GHSA-rrfp-j2mp-hq9c"
          ],
          "not_impacted": "All versions starting from 2.4.0",
          "package_slug": "pypi/tensorflow-cpu",
          "pubdate": "2020-10-21",
          "solution": "Upgrade to version 2.4.0 or above.",
          "title": "Out-of-bounds Read",
          "urls": [
            "https://nvd.nist.gov/vuln/detail/CVE-2020-15265"
          ],
          "uuid": "e2ad6861-002e-442a-832b-71e3f40a5b9c"
        },
        {
          "affected_range": "\u003c2.4.0",
          "affected_versions": "All versions before 2.4.0",
          "cvss_v2": "AV:N/AC:L/Au:N/C:N/I:N/A:P",
          "cvss_v3": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
          "cwe_ids": [
            "CWE-1035",
            "CWE-125",
            "CWE-937"
          ],
          "date": "2020-11-03",
          "description": "In Tensorflow, an attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, `dim_size` only does a `DCHECK` to validate the argument and then uses it to access the corresponding element of an array. Since in normal builds, `DCHECK`-like macros are no-ops, this results in segfault and access out-of-bounds of the array.",
          "fixed_versions": [
            "2.4.0"
          ],
          "identifier": "CVE-2020-15265",
          "identifiers": [
            "CVE-2020-15265",
            "GHSA-rrfp-j2mp-hq9c"
          ],
          "not_impacted": "All versions starting from 2.4.0",
          "package_slug": "pypi/tensorflow-gpu",
          "pubdate": "2020-10-21",
          "solution": "Upgrade to version 2.4.0 or above.",
          "title": "Out-of-bounds Read",
          "urls": [
            "https://nvd.nist.gov/vuln/detail/CVE-2020-15265"
          ],
          "uuid": "cb900810-4503-4004-88fb-cda6a4e51bba"
        },
        {
          "affected_range": "\u003c2.4.0",
          "affected_versions": "All versions before 2.4.0",
          "cvss_v2": "AV:N/AC:L/Au:N/C:N/I:N/A:P",
          "cvss_v3": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
          "cwe_ids": [
            "CWE-1035",
            "CWE-125",
            "CWE-937"
          ],
          "date": "2021-08-17",
          "description": "In Tensorflow, an attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`.` This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, `dim_size` only does a `DCHECK` to validate the argument and then uses it to access the corresponding element of an array. Since in normal builds, `DCHECK`-like macros are no-ops, this results in segfault and access out-of-bounds of the array.",
          "fixed_versions": [
            "2.4.0"
          ],
          "identifier": "CVE-2020-15265",
          "identifiers": [
            "CVE-2020-15265",
            "GHSA-rrfp-j2mp-hq9c"
          ],
          "not_impacted": "All versions starting from 2.4.0",
          "package_slug": "pypi/tensorflow",
          "pubdate": "2020-10-21",
          "solution": "Upgrade to version 2.4.0 or above.",
          "title": "Out-of-bounds Read",
          "urls": [
            "https://nvd.nist.gov/vuln/detail/CVE-2020-15265"
          ],
          "uuid": "39082c03-8860-43cb-a715-375470501bb3"
        }
      ]
    },
    "nvd.nist.gov": {
      "configurations": {
        "CVE_data_version": "4.0",
        "nodes": [
          {
            "children": [],
            "cpe_match": [
              {
                "cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:-:*:*:*",
                "cpe_name": [],
                "versionEndExcluding": "2.4.0",
                "vulnerable": true
              }
            ],
            "operator": "OR"
          }
        ]
      },
      "cve": {
        "CVE_data_meta": {
          "ASSIGNER": "security-advisories@github.com",
          "ID": "CVE-2020-15265"
        },
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        "data_type": "CVE",
        "data_version": "4.0",
        "description": {
          "description_data": [
            {
              "lang": "en",
              "value": "In Tensorflow before version 2.4.0, an attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dim_size only does a DCHECK to validate the argument and then uses it to access the corresponding element of an array. Since in normal builds, `DCHECK`-like macros are no-ops, this results in segfault and access out of bounds of the array. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved."
            }
          ]
        },
        "problemtype": {
          "problemtype_data": [
            {
              "description": [
                {
                  "lang": "en",
                  "value": "CWE-125"
                }
              ]
            }
          ]
        },
        "references": {
          "reference_data": [
            {
              "name": "https://github.com/tensorflow/tensorflow/commit/eccb7ec454e6617738554a255d77f08e60ee0808",
              "refsource": "MISC",
              "tags": [
                "Patch",
                "Third Party Advisory"
              ],
              "url": "https://github.com/tensorflow/tensorflow/commit/eccb7ec454e6617738554a255d77f08e60ee0808"
            },
            {
              "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rrfp-j2mp-hq9c",
              "refsource": "CONFIRM",
              "tags": [
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                "Patch",
                "Third Party Advisory"
              ],
              "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rrfp-j2mp-hq9c"
            },
            {
              "name": "https://github.com/tensorflow/tensorflow/issues/42105",
              "refsource": "MISC",
              "tags": [
                "Patch",
                "Third Party Advisory"
              ],
              "url": "https://github.com/tensorflow/tensorflow/issues/42105"
            }
          ]
        }
      },
      "impact": {
        "baseMetricV2": {
          "acInsufInfo": false,
          "cvssV2": {
            "accessComplexity": "LOW",
            "accessVector": "NETWORK",
            "authentication": "NONE",
            "availabilityImpact": "PARTIAL",
            "baseScore": 5.0,
            "confidentialityImpact": "NONE",
            "integrityImpact": "NONE",
            "vectorString": "AV:N/AC:L/Au:N/C:N/I:N/A:P",
            "version": "2.0"
          },
          "exploitabilityScore": 10.0,
          "impactScore": 2.9,
          "obtainAllPrivilege": false,
          "obtainOtherPrivilege": false,
          "obtainUserPrivilege": false,
          "severity": "MEDIUM",
          "userInteractionRequired": false
        },
        "baseMetricV3": {
          "cvssV3": {
            "attackComplexity": "LOW",
            "attackVector": "NETWORK",
            "availabilityImpact": "HIGH",
            "baseScore": 7.5,
            "baseSeverity": "HIGH",
            "confidentialityImpact": "NONE",
            "integrityImpact": "NONE",
            "privilegesRequired": "NONE",
            "scope": "UNCHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
            "version": "3.1"
          },
          "exploitabilityScore": 3.9,
          "impactScore": 3.6
        }
      },
      "lastModifiedDate": "2021-08-17T13:21Z",
      "publishedDate": "2020-10-21T21:15Z"
    }
  }
}


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