GSD-2021-41197

Vulnerability from gsd - Updated: 2023-12-13 01:23
Details
TensorFlow is an open source platform for machine learning. In affected versions TensorFlow allows tensor to have a large number of dimensions and each dimension can be as large as desired. However, the total number of elements in a tensor must fit within an `int64_t`. If an overflow occurs, `MultiplyWithoutOverflow` would return a negative result. In the majority of TensorFlow codebase this then results in a `CHECK`-failure. Newer constructs exist which return a `Status` instead of crashing the binary. This is similar to CVE-2021-29584. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
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Aliases
CVE-2021-41197
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{
  "GSD": {
    "alias": "CVE-2021-41197",
    "description": "TensorFlow is an open source platform for machine learning. In affected versions TensorFlow allows tensor to have a large number of dimensions and each dimension can be as large as desired. However, the total number of elements in a tensor must fit within an `int64_t`. If an overflow occurs, `MultiplyWithoutOverflow` would return a negative result. In the majority of TensorFlow codebase this then results in a `CHECK`-failure. Newer constructs exist which return a `Status` instead of crashing the binary. This is similar to CVE-2021-29584. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.",
    "id": "GSD-2021-41197",
    "references": [
      "https://www.suse.com/security/cve/CVE-2021-41197.html",
      "https://security.archlinux.org/CVE-2021-41197"
    ]
  },
  "gsd": {
    "metadata": {
      "exploitCode": "unknown",
      "remediation": "unknown",
      "reportConfidence": "confirmed",
      "type": "vulnerability"
    },
    "osvSchema": {
      "aliases": [
        "CVE-2021-41197"
      ],
      "details": "TensorFlow is an open source platform for machine learning. In affected versions TensorFlow allows tensor to have a large number of dimensions and each dimension can be as large as desired. However, the total number of elements in a tensor must fit within an `int64_t`. If an overflow occurs, `MultiplyWithoutOverflow` would return a negative result. In the majority of TensorFlow codebase this then results in a `CHECK`-failure. Newer constructs exist which return a `Status` instead of crashing the binary. This is similar to CVE-2021-29584. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.",
      "id": "GSD-2021-41197",
      "modified": "2023-12-13T01:23:27.613201Z",
      "schema_version": "1.4.0"
    }
  },
  "namespaces": {
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        "ID": "CVE-2021-41197",
        "STATE": "PUBLIC",
        "TITLE": "Crashes due to overflow and `CHECK`-fail in ops with large tensor shapes"
      },
      "affects": {
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            "value": "TensorFlow is an open source platform for machine learning. In affected versions TensorFlow allows tensor to have a large number of dimensions and each dimension can be as large as desired. However, the total number of elements in a tensor must fit within an `int64_t`. If an overflow occurs, `MultiplyWithoutOverflow` would return a negative result. In the majority of TensorFlow codebase this then results in a `CHECK`-failure. Newer constructs exist which return a `Status` instead of crashing the binary. This is similar to CVE-2021-29584. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range."
          }
        ]
      },
      "impact": {
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          "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"
        }
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                "value": "CWE-190: Integer Overflow or Wraparound"
              }
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          }
        ]
      },
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            "refsource": "MISC",
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          {
            "name": "https://github.com/tensorflow/tensorflow/issues/51908",
            "refsource": "MISC",
            "url": "https://github.com/tensorflow/tensorflow/issues/51908"
          },
          {
            "name": "https://github.com/tensorflow/tensorflow/commit/7c1692bd417eb4f9b33ead749a41166d6080af85",
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            "url": "https://github.com/tensorflow/tensorflow/commit/d81b1351da3e8c884ff836b64458d94e4a157c15"
          }
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      },
      "source": {
        "advisory": "GHSA-prcg-wp5q-rv7p",
        "discovery": "UNKNOWN"
      }
    },
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          "affected_range": "\u003e=2.6.0,\u003c2.6.1||\u003e=2.5.0,\u003c2.5.2||\u003c2.4.4",
          "affected_versions": "All versions starting from 2.6.0 before 2.6.1, all versions starting from 2.5.0 before 2.5.2, all versions before 2.4.4",
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            "CWE-190",
            "CWE-937"
          ],
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          "description": "TensorFlow is an open source platform for machine learning. In affected versions TensorFlow allows tensor to have a large number of dimensions and each dimension can be as large as desired. However, the total number of elements in a tensor must fit within an `int64_t`. If an overflow occurs, `MultiplyWithoutOverflow` would return a negative result. In the majority of TensorFlow codebase this then results in a `CHECK`-failure. Newer constructs exist which return a `Status` instead of crashing the binary. This is similar to CVE-2021-29584. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.",
          "fixed_versions": [
            "2.6.1",
            "2.4.4",
            "2.4.4"
          ],
          "identifier": "CVE-2021-41197",
          "identifiers": [
            "GHSA-prcg-wp5q-rv7p",
            "CVE-2021-41197"
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          "not_impacted": "All versions before 2.6.0, all versions starting from 2.6.1, all versions before 2.5.0, all versions starting from 2.4.4 before 2.5.2",
          "package_slug": "pypi/tensorflow-cpu",
          "pubdate": "2021-11-10",
          "solution": "Upgrade to versions 2.6.1, 2.4.4, 2.4.4 or above.",
          "title": "Integer Overflow or Wraparound",
          "urls": [
            "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-prcg-wp5q-rv7p",
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          "pubdate": "2021-11-10",
          "solution": "Upgrade to versions 2.6.1, 2.4.4, 2.4.4 or above.",
          "title": "Integer Overflow or Wraparound",
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          "pubdate": "2021-11-05",
          "solution": "Upgrade to versions 2.4.4, 2.5.2, 2.6.1 or above.",
          "title": "Integer Overflow or Wraparound",
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            "authentication": "NONE",
            "availabilityImpact": "PARTIAL",
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            "vectorString": "AV:L/AC:L/Au:N/C:N/I:N/A:P",
            "version": "2.0"
          },
          "exploitabilityScore": 3.9,
          "impactScore": 2.9,
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        },
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          "impactScore": 3.6
        }
      },
      "lastModifiedDate": "2021-11-09T14:30Z",
      "publishedDate": "2021-11-05T20:15Z"
    }
  }
}


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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.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
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  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.



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