GSD-2022-23591

Vulnerability from gsd - Updated: 2023-12-13 01:19
Details
Tensorflow is an Open Source Machine Learning Framework. The `GraphDef` format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a `GraphDef` containing a fragment such as the following can be consumed when loading a `SavedModel`. This would result in a stack overflow during execution as resolving each `NodeDef` means resolving the function itself and its nodes. 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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Aliases
CVE-2022-23591
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{
  "GSD": {
    "alias": "CVE-2022-23591",
    "description": "Tensorflow is an Open Source Machine Learning Framework. The `GraphDef` format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a `GraphDef` containing a fragment such as the following can be consumed when loading a `SavedModel`. This would result in a stack overflow during execution as resolving each `NodeDef` means resolving the function itself and its nodes. 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-2022-23591",
    "references": [
      "https://www.suse.com/security/cve/CVE-2022-23591.html"
    ]
  },
  "gsd": {
    "metadata": {
      "exploitCode": "unknown",
      "remediation": "unknown",
      "reportConfidence": "confirmed",
      "type": "vulnerability"
    },
    "osvSchema": {
      "aliases": [
        "CVE-2022-23591"
      ],
      "details": "Tensorflow is an Open Source Machine Learning Framework. The `GraphDef` format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a `GraphDef` containing a fragment such as the following can be consumed when loading a `SavedModel`. This would result in a stack overflow during execution as resolving each `NodeDef` means resolving the function itself and its nodes. 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-2022-23591",
      "modified": "2023-12-13T01:19:35.142778Z",
      "schema_version": "1.4.0"
    }
  },
  "namespaces": {
    "cve.org": {
      "CVE_data_meta": {
        "ASSIGNER": "security-advisories@github.com",
        "ID": "CVE-2022-23591",
        "STATE": "PUBLIC",
        "TITLE": "Stack 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"
                        }
                      ]
                    }
                  }
                ]
              },
              "vendor_name": "tensorflow"
            }
          ]
        }
      },
      "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 `GraphDef` format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a `GraphDef` containing a fragment such as the following can be consumed when loading a `SavedModel`. This would result in a stack overflow during execution as resolving each `NodeDef` means resolving the function itself and its nodes. 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": 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"
        }
      },
      "problemtype": {
        "problemtype_data": [
          {
            "description": [
              {
                "lang": "eng",
                "value": "CWE-400: Uncontrolled Resource Consumption"
              }
            ]
          }
        ]
      },
      "references": {
        "reference_data": [
          {
            "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-247x-2f9f-5wp7",
            "refsource": "CONFIRM",
            "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-247x-2f9f-5wp7"
          },
          {
            "name": "https://github.com/tensorflow/tensorflow/commit/448a16182065bd08a202d9057dd8ca541e67996c",
            "refsource": "MISC",
            "url": "https://github.com/tensorflow/tensorflow/commit/448a16182065bd08a202d9057dd8ca541e67996c"
          }
        ]
      },
      "source": {
        "advisory": "GHSA-247x-2f9f-5wp7",
        "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: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-400",
            "CWE-937"
          ],
          "date": "2022-02-11",
          "description": "Tensorflow is an Open Source Machine Learning Framework. The `GraphDef` format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a `GraphDef` containing a fragment such as the following can be consumed when loading a `SavedModel`. This would result in a stack overflow during execution as resolving each `NodeDef` means resolving the function itself and its nodes. 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-2022-23591",
          "identifiers": [
            "GHSA-247x-2f9f-5wp7",
            "CVE-2022-23591"
          ],
          "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": "2022-02-09",
          "solution": "Upgrade to versions 2.5.3, 2.6.3, 2.7.1 or above.",
          "title": "Uncontrolled Resource Consumption",
          "urls": [
            "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-247x-2f9f-5wp7",
            "https://github.com/tensorflow/tensorflow/commit/448a16182065bd08a202d9057dd8ca541e67996c",
            "https://nvd.nist.gov/vuln/detail/CVE-2022-23591",
            "https://github.com/advisories/GHSA-247x-2f9f-5wp7"
          ],
          "uuid": "0cd53f43-43d4-4d96-81c8-9d64298257f8"
        },
        {
          "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: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-400",
            "CWE-937"
          ],
          "date": "2022-02-11",
          "description": "Tensorflow is an Open Source Machine Learning Framework. The `GraphDef` format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a `GraphDef` containing a fragment such as the following can be consumed when loading a `SavedModel`. This would result in a stack overflow during execution as resolving each `NodeDef` means resolving the function itself and its nodes. 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-2022-23591",
          "identifiers": [
            "GHSA-247x-2f9f-5wp7",
            "CVE-2022-23591"
          ],
          "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": "2022-02-09",
          "solution": "Upgrade to versions 2.5.3, 2.6.3, 2.7.1 or above.",
          "title": "Uncontrolled Resource Consumption",
          "urls": [
            "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-247x-2f9f-5wp7",
            "https://github.com/tensorflow/tensorflow/commit/448a16182065bd08a202d9057dd8ca541e67996c",
            "https://nvd.nist.gov/vuln/detail/CVE-2022-23591",
            "https://github.com/advisories/GHSA-247x-2f9f-5wp7"
          ],
          "uuid": "e51ca943-7a77-481d-8c39-5a60d1d715ac"
        },
        {
          "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: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-674",
            "CWE-937"
          ],
          "date": "2023-06-27",
          "description": "Tensorflow is an Open Source Machine Learning Framework. The `GraphDef` format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a `GraphDef` containing a fragment such as the following can be consumed when loading a `SavedModel`. This would result in a stack overflow during execution as resolving each `NodeDef` means resolving the function itself and its nodes. 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-2022-23591",
          "identifiers": [
            "CVE-2022-23591",
            "GHSA-247x-2f9f-5wp7"
          ],
          "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": "Uncontrolled Resource Consumption",
          "urls": [
            "https://nvd.nist.gov/vuln/detail/CVE-2022-23591",
            "https://github.com/tensorflow/tensorflow/commit/448a16182065bd08a202d9057dd8ca541e67996c",
            "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-247x-2f9f-5wp7"
          ],
          "uuid": "925e7449-0c75-4bbd-b65e-627ef09b124d"
        }
      ]
    },
    "nvd.nist.gov": {
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        "nodes": [
          {
            "children": [],
            "cpe_match": [
              {
                "cpe23Uri": "cpe:2.3:a:google:tensorflow:2.7.0:*:*:*:*:*:*:*",
                "cpe_name": [],
                "vulnerable": true
              },
              {
                "cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
                "cpe_name": [],
                "versionEndIncluding": "2.5.2",
                "vulnerable": true
              },
              {
                "cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
                "cpe_name": [],
                "versionEndIncluding": "2.6.2",
                "versionStartIncluding": "2.6.0",
                "vulnerable": true
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            "operator": "OR"
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          "ID": "CVE-2022-23591"
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        "description": {
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              "value": "Tensorflow is an Open Source Machine Learning Framework. The `GraphDef` format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a `GraphDef` containing a fragment such as the following can be consumed when loading a `SavedModel`. This would result in a stack overflow during execution as resolving each `NodeDef` means resolving the function itself and its nodes. 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/448a16182065bd08a202d9057dd8ca541e67996c",
              "refsource": "MISC",
              "tags": [
                "Patch",
                "Third Party Advisory"
              ],
              "url": "https://github.com/tensorflow/tensorflow/commit/448a16182065bd08a202d9057dd8ca541e67996c"
            },
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              "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-247x-2f9f-5wp7"
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      },
      "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": "2023-06-27T02:40Z",
      "publishedDate": "2022-02-04T23:15Z"
    }
  }
}


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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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