gsd-2022-29212
Vulnerability from gsd
Modified
2023-12-13 01:19
Details
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, certain TFLite models that were created using TFLite model converter would crash when loaded in the TFLite interpreter. The culprit is that during quantization the scale of values could be greater than 1 but code was always assuming sub-unit scaling. Thus, since code was calling `QuantizeMultiplierSmallerThanOneExp`, the `TFLITE_CHECK_LT` assertion would trigger and abort the process. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
Aliases
Aliases
CVE-2022-29212


To clipboard 

{
  "GSD": {
    "alias": "CVE-2022-29212",
    "description": "TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, certain TFLite models that were created using TFLite model converter would crash when loaded in the TFLite interpreter. The culprit is that during quantization the scale of values could be greater than 1 but code was always assuming sub-unit scaling. Thus, since code was calling `QuantizeMultiplierSmallerThanOneExp`, the `TFLITE_CHECK_LT` assertion would trigger and abort the process. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.",
    "id": "GSD-2022-29212",
    "references": [
      "https://www.suse.com/security/cve/CVE-2022-29212.html"
    ]
  },
  "gsd": {
    "metadata": {
      "exploitCode": "unknown",
      "remediation": "unknown",
      "reportConfidence": "confirmed",
      "type": "vulnerability"
    },
    "osvSchema": {
      "aliases": [
        "CVE-2022-29212"
      ],
      "details": "TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, certain TFLite models that were created using TFLite model converter would crash when loaded in the TFLite interpreter. The culprit is that during quantization the scale of values could be greater than 1 but code was always assuming sub-unit scaling. Thus, since code was calling `QuantizeMultiplierSmallerThanOneExp`, the `TFLITE_CHECK_LT` assertion would trigger and abort the process. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.",
      "id": "GSD-2022-29212",
      "modified": "2023-12-13T01:19:42.469717Z",
      "schema_version": "1.4.0"
    }
  },
  "namespaces": {
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        "ID": "CVE-2022-29212",
        "STATE": "PUBLIC",
        "TITLE": "Core dump when loading TFLite models with quantization in TensorFlow"
      },
      "affects": {
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      "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",
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            "name": "https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4",
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      "source": {
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        "discovery": "UNKNOWN"
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        {
          "affected_range": "\u003c2.6.4||\u003e=2.7.0,\u003c2.7.2||\u003e=2.8.0,\u003c2.8.1",
          "affected_versions": "All versions before 2.6.4, all versions starting from 2.7.0 before 2.7.2, all versions starting from 2.8.0 before 2.8.1",
          "cwe_ids": [
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            "CWE-20",
            "CWE-937"
          ],
          "date": "2022-05-24",
          "description": "TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, certain TFLite models that were created using TFLite model converter would crash when loaded in the TFLite interpreter. The culprit is that during quantization the scale of values could be greater than 1 but code was always assuming sub-unit scaling. Thus, since code was calling `QuantizeMultiplierSmallerThanOneExp`, the `TFLITE_CHECK_LT` assertion would trigger and abort the process. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.",
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          "not_impacted": "All versions starting from 2.6.4 before 2.7.0, all versions starting from 2.7.2 before 2.8.0, all versions starting from 2.8.1",
          "package_slug": "pypi/tensorflow-cpu",
          "pubdate": "2022-05-24",
          "solution": "Upgrade to versions 2.6.4, 2.7.2, 2.8.1 or above.",
          "title": "Improper Input Validation",
          "urls": [
            "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8wwm-6264-x792",
            "https://nvd.nist.gov/vuln/detail/CVE-2022-29212",
            "https://github.com/tensorflow/tensorflow/issues/43661",
            "https://github.com/tensorflow/tensorflow/commit/a989426ee1346693cc015792f11d715f6944f2b8",
            "https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/lite/kernels/internal/quantization_util.cc#L114-L123",
            "https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4",
            "https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2",
            "https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1",
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            "https://github.com/advisories/GHSA-8wwm-6264-x792"
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        },
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            "CWE-20",
            "CWE-937"
          ],
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          "description": "TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, certain TFLite models that were created using TFLite model converter would crash when loaded in the TFLite interpreter. The culprit is that during quantization the scale of values could be greater than 1 but code was always assuming sub-unit scaling. Thus, since code was calling `QuantizeMultiplierSmallerThanOneExp`, the `TFLITE_CHECK_LT` assertion would trigger and abort the process. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.",
          "fixed_versions": [
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            "2.7.2",
            "2.8.1"
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          "identifier": "CVE-2022-29212",
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            "GHSA-8wwm-6264-x792",
            "CVE-2022-29212"
          ],
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          "package_slug": "pypi/tensorflow-gpu",
          "pubdate": "2022-05-24",
          "solution": "Upgrade to versions 2.6.4, 2.7.2, 2.8.1 or above.",
          "title": "Improper Input Validation",
          "urls": [
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            "https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2",
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          "uuid": "96274d26-a79f-4632-95b0-8645140eed0f"
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          "date": "2022-06-03",
          "description": "TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, certain TFLite models that were created using TFLite model converter would crash when loaded in the TFLite interpreter. The culprit is that during quantization the scale of values could be greater than 1 but code was always assuming sub-unit scaling. Thus, since code was calling `QuantizeMultiplierSmallerThanOneExp`, the `TFLITE_CHECK_LT` assertion would trigger and abort the process. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.",
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            "2.7.2",
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          "identifier": "CVE-2022-29212",
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            "GHSA-8wwm-6264-x792"
          ],
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          "package_slug": "pypi/tensorflow",
          "pubdate": "2022-05-21",
          "solution": "Upgrade to versions 2.6.4, 2.7.2, 2.8.1 or above.",
          "title": "Improper Input Validation",
          "urls": [
            "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8wwm-6264-x792",
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            "https://github.com/tensorflow/tensorflow/issues/43661",
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            "https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/lite/kernels/internal/quantization_util.cc#L114-L123",
            "https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4",
            "https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2",
            "https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1",
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          "uuid": "2fa662d5-d83c-4ae4-a55b-9e412e5403aa"
        }
      ]
    },
    "nvd.nist.gov": {
      "configurations": {
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            "cpe_match": [
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      "impact": {
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          "acInsufInfo": false,
          "cvssV2": {
            "accessComplexity": "LOW",
            "accessVector": "LOCAL",
            "authentication": "NONE",
            "availabilityImpact": "PARTIAL",
            "baseScore": 2.1,
            "confidentialityImpact": "NONE",
            "integrityImpact": "NONE",
            "vectorString": "AV:L/AC:L/Au:N/C:N/I:N/A:P",
            "version": "2.0"
          },
          "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",
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          "exploitabilityScore": 1.8,
          "impactScore": 3.6
        }
      },
      "lastModifiedDate": "2022-06-03T15:16Z",
      "publishedDate": "2022-05-21T00:15Z"
    }
  }
}


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  • Confirmed: The vulnerability is confirmed from an analyst perspective.
  • Exploited: This vulnerability was exploited and seen by the user reporting the sighting.
  • Patched: This vulnerability was successfully patched by the user reporting the sighting.
  • Not exploited: This vulnerability was not exploited or seen by the user reporting the sighting.
  • Not confirmed: The user expresses doubt about the veracity of the vulnerability.
  • Not patched: This vulnerability was not successfully patched by the user reporting the sighting.