gsd-2021-37646
Vulnerability from gsd
Modified
2023-12-13 01:23
Details
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.StringNGrams` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/string_ngrams_op.cc#L184) calls `reserve` on a `tstring` with a value that sometimes can be negative if user supplies negative `ngram_widths`. The `reserve` method calls `TF_TString_Reserve` which has an `unsigned long` argument for the size of the buffer. Hence, the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit c283e542a3f422420cfdb332414543b62fc4e4a5. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Aliases
Aliases
CVE-2021-37646


To clipboard 

{
  "GSD": {
    "alias": "CVE-2021-37646",
    "description": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.StringNGrams` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/string_ngrams_op.cc#L184) calls `reserve` on a `tstring` with a value that sometimes can be negative if user supplies negative `ngram_widths`. The `reserve` method calls `TF_TString_Reserve` which has an `unsigned long` argument for the size of the buffer. Hence, the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit c283e542a3f422420cfdb332414543b62fc4e4a5. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.",
    "id": "GSD-2021-37646",
    "references": [
      "https://www.suse.com/security/cve/CVE-2021-37646.html",
      "https://security.archlinux.org/CVE-2021-37646"
    ]
  },
  "gsd": {
    "metadata": {
      "exploitCode": "unknown",
      "remediation": "unknown",
      "reportConfidence": "confirmed",
      "type": "vulnerability"
    },
    "osvSchema": {
      "aliases": [
        "CVE-2021-37646"
      ],
      "details": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.StringNGrams` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/string_ngrams_op.cc#L184) calls `reserve` on a `tstring` with a value that sometimes can be negative if user supplies negative `ngram_widths`. The `reserve` method calls `TF_TString_Reserve` which has an `unsigned long` argument for the size of the buffer. Hence, the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit c283e542a3f422420cfdb332414543b62fc4e4a5. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.",
      "id": "GSD-2021-37646",
      "modified": "2023-12-13T01:23:09.419654Z",
      "schema_version": "1.4.0"
    }
  },
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        "ID": "CVE-2021-37646",
        "STATE": "PUBLIC",
        "TITLE": "Bad alloc in `StringNGrams` caused by integer conversion in TensorFlow"
      },
      "affects": {
        "vendor": {
          "vendor_data": [
            {
              "product": {
                "product_data": [
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      "description": {
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          {
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            "value": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.StringNGrams` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/string_ngrams_op.cc#L184) calls `reserve` on a `tstring` with a value that sometimes can be negative if user supplies negative `ngram_widths`. The `reserve` method calls `TF_TString_Reserve` which has an `unsigned long` argument for the size of the buffer. Hence, the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit c283e542a3f422420cfdb332414543b62fc4e4a5. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range."
          }
        ]
      },
      "impact": {
        "cvss": {
          "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",
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                "value": "CWE-681: Incorrect Conversion between Numeric Types"
              }
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            "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h6jh-7gv5-28vg",
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          },
          {
            "name": "https://github.com/tensorflow/tensorflow/commit/c283e542a3f422420cfdb332414543b62fc4e4a5",
            "refsource": "MISC",
            "url": "https://github.com/tensorflow/tensorflow/commit/c283e542a3f422420cfdb332414543b62fc4e4a5"
          }
        ]
      },
      "source": {
        "advisory": "GHSA-h6jh-7gv5-28vg",
        "discovery": "UNKNOWN"
      }
    },
    "gitlab.com": {
      "advisories": [
        {
          "affected_range": "\u003c2.3.4||\u003e=2.4.0,\u003c2.4.3||==2.5.0",
          "affected_versions": "All versions before 2.3.4, all versions starting from 2.4.0 before 2.4.3, version 2.5.0",
          "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": [
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            "CWE-681",
            "CWE-937"
          ],
          "date": "2021-08-25",
          "description": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.StringNGrams` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The implementation calls `reserve` on a `tstring` with a value that sometimes can be negative if user supplies negative `ngram_widths`. The `reserve` method calls `TF_TString_Reserve` which has an `unsigned long` argument for the size of the buffer. Hence, the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit c283e542a3f422420cfdb332414543b62fc4e4a5. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.",
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            "2.4.3",
            "2.5.1"
          ],
          "identifier": "CVE-2021-37646",
          "identifiers": [
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            "CVE-2021-37646"
          ],
          "not_impacted": "All versions starting from 2.3.4 before 2.4.0, all versions starting from 2.4.3 before 2.5.0, all versions after 2.5.0",
          "package_slug": "pypi/tensorflow-cpu",
          "pubdate": "2021-08-25",
          "solution": "Upgrade to versions 2.3.4, 2.4.3, 2.5.1 or above.",
          "title": "Incorrect Conversion between Numeric Types",
          "urls": [
            "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h6jh-7gv5-28vg",
            "https://nvd.nist.gov/vuln/detail/CVE-2021-37646",
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          "uuid": "59e4bedf-761a-4523-847e-7f8a34d59a9f"
        },
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            "CWE-937"
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          "description": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.StringNGrams` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The implementation calls `reserve` on a `tstring` with a value that sometimes can be negative if user supplies negative `ngram_widths`. The `reserve` method calls `TF_TString_Reserve` which has an `unsigned long` argument for the size of the buffer. Hence, the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit c283e542a3f422420cfdb332414543b62fc4e4a5. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.",
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            "CVE-2021-37646"
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          "package_slug": "pypi/tensorflow-gpu",
          "pubdate": "2021-08-25",
          "solution": "Upgrade to versions 2.3.4, 2.4.3, 2.5.1 or above.",
          "title": "Incorrect Conversion between Numeric Types",
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          "date": "2021-08-18",
          "description": "TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.StringNGrams` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The implementation calls `reserve` on a `tstring` with a value that sometimes can be negative if user supplies negative `ngram_widths`. The `reserve` method calls `TF_TString_Reserve` which has an `unsigned long` argument for the size of the buffer. Hence, the implicit conversion transforms the negative value to a large integer.",
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            "2.4.3"
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          "identifier": "CVE-2021-37646",
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          "package_slug": "pypi/tensorflow",
          "pubdate": "2021-08-12",
          "solution": "Upgrade to versions 2.3.4, 2.4.3 or above.",
          "title": "Incorrect Conversion between Numeric Types",
          "urls": [
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          "uuid": "3ac32c12-3e5a-4dde-a85c-858f564abc68"
        }
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      },
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          "acInsufInfo": false,
          "cvssV2": {
            "accessComplexity": "LOW",
            "accessVector": "LOCAL",
            "authentication": "NONE",
            "availabilityImpact": "PARTIAL",
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            "vectorString": "AV:L/AC:L/Au:N/C:N/I:N/A:P",
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        },
        "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",
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          "exploitabilityScore": 1.8,
          "impactScore": 3.6
        }
      },
      "lastModifiedDate": "2021-08-18T15:39Z",
      "publishedDate": "2021-08-12T21:15Z"
    }
  }
}


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