GSD-2021-37661

Vulnerability from gsd - Updated: 2023-12-13 01:23
Details
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. 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

{
  "GSD": {
    "alias": "CVE-2021-37661",
    "description": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. 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-2021-37661",
    "references": [
      "https://www.suse.com/security/cve/CVE-2021-37661.html",
      "https://security.archlinux.org/CVE-2021-37661"
    ]
  },
  "gsd": {
    "metadata": {
      "exploitCode": "unknown",
      "remediation": "unknown",
      "reportConfidence": "confirmed",
      "type": "vulnerability"
    },
    "osvSchema": {
      "aliases": [
        "CVE-2021-37661"
      ],
      "details": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. 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-2021-37661",
      "modified": "2023-12-13T01:23:09.746777Z",
      "schema_version": "1.4.0"
    }
  },
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        "ID": "CVE-2021-37661",
        "STATE": "PUBLIC",
        "TITLE": "Crash caused by integer conversion to unsigned in TensorFlow"
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      "affects": {
        "vendor": {
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              "product": {
                "product_data": [
                  {
                    "product_name": "tensorflow",
                    "version": {
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      "description": {
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            "lang": "eng",
            "value": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. 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",
          "version": "3.1"
        }
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      "problemtype": {
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                "value": "CWE-681: Incorrect Conversion between Numeric Types"
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        ]
      },
      "references": {
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          {
            "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gf88-j2mg-cc82",
            "refsource": "CONFIRM",
            "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gf88-j2mg-cc82"
          },
          {
            "name": "https://github.com/tensorflow/tensorflow/commit/8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992",
            "refsource": "MISC",
            "url": "https://github.com/tensorflow/tensorflow/commit/8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992"
          }
        ]
      },
      "source": {
        "advisory": "GHSA-gf88-j2mg-cc82",
        "discovery": "UNKNOWN"
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        {
          "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 an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The implementation does not validate that `num_streams` only contains non-negative numbers. In turn, this results in using this value to allocate memory However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. 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.",
          "fixed_versions": [
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            "2.4.3",
            "2.5.1"
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          "identifier": "CVE-2021-37661",
          "identifiers": [
            "GHSA-gf88-j2mg-cc82",
            "CVE-2021-37661"
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          "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-gf88-j2mg-cc82",
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          "description": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The implementation does not validate that `num_streams` only contains non-negative numbers. In turn, this results in using this value to allocate memory However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. 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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          "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",
          "urls": [
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          "date": "2021-08-18",
          "description": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The implementation does not validate that `num_streams` only contains non-negative numbers. In turn, this results in using this value to allocate memory. However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library.",
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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": "de9afdaf-8ee9-4dfd-a774-ac3bb1e3f724"
        }
      ]
    },
    "nvd.nist.gov": {
      "configurations": {
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        "nodes": [
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                "cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
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              "value": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. 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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          "acInsufInfo": false,
          "cvssV2": {
            "accessComplexity": "LOW",
            "accessVector": "LOCAL",
            "authentication": "NONE",
            "availabilityImpact": "PARTIAL",
            "baseScore": 2.1,
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            "vectorString": "AV:L/AC:L/Au:N/C:N/I:N/A:P",
            "version": "2.0"
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          "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",
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          "exploitabilityScore": 1.8,
          "impactScore": 3.6
        }
      },
      "lastModifiedDate": "2021-08-18T21:09Z",
      "publishedDate": "2021-08-12T21:15Z"
    }
  }
}


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  • Confirmed: The vulnerability has been validated from an analyst's perspective.
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