Vulnerability-Lookup

CVE-2023-27579 (GCVE-0-2023-27579)

Vulnerability from cvelistv5 – Published: 2023-03-24 23:05 – Updated: 2025-02-19 20:45

Title

TensorFlow has Floating Point Exception in TFLite in conv kernel

Summary

TensorFlow is an end-to-end open source platform for machine learning. Constructing a tflite model with a paramater `filter_input_channel` of less than 1 gives a FPE. This issue has been patched in version 2.12. TensorFlow will also cherrypick the fix commit on TensorFlow 2.11.1.

Severity

7.5 (High)


                        
                          CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

SSVC

Exploitation: none Automatable: yes Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2025-02-19 20:44 UTC

CWE

CWE-697 - Incorrect Comparison

Assigner

GitHub_M CNA under the mitre root

CNA scorecard C 72/100 over 7771 records in the last 180 days details

References

2 references

URL	Tags
https://github.com/tensorflow/tensorflow/security…	x_refsource_CONFIRM
https://github.com/tensorflow/tensorflow/commit/3…	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version	CPE status
tensorflow	tensorflow	Affected: < 2.11.1	guessed

Show details on NVD website

JSON

To clipboard

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bit-tensorflow-2023-27579

Vulnerability from bitnami_vulndb

Published

2024-03-06 11:06

Modified

2026-09-08 08:34

Summary

TensorFlow has Floating Point Exception in TFLite in conv kernel

Details

TensorFlow is an end-to-end open source platform for machine learning. Constructing a tflite model with a paramater filter_input_channel of less than 1 gives a FPE. This issue has been patched in version 2.12. TensorFlow will also cherrypick the fix commit on TensorFlow 2.11.1.

JSON

To clipboard

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            {
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              "fixed": "2.12.0"
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          ],
          "type": "SEMVER"
        }
      ],
      "severity": [
        {
          "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
          "type": "CVSS_V3"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2023-27579"
  ],
  "database_specific": {
    "cpes": [
      "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*"
    ],
    "severity": "High"
  },
  "details": "TensorFlow is an end-to-end open source platform for machine learning. Constructing a tflite model with a paramater `filter_input_channel` of less than 1 gives a FPE. This issue has been patched in version 2.12. TensorFlow will also cherrypick the fix commit on TensorFlow 2.11.1.",
  "id": "BIT-tensorflow-2023-27579",
  "modified": "2026-09-08T08:34:36.952Z",
  "published": "2024-03-06T11:06:50.569Z",
  "references": [
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/34f8368c535253f5c9cb3a303297743b62442aaa"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5w96-866f-6rm8"
    },
    {
      "type": "WEB",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-27579"
    }
  ],
  "schema_version": "1.5.0",
  "summary": "TensorFlow has Floating Point Exception in TFLite in conv kernel"
}

FKIE_CVE-2023-27579

Vulnerability from fkie_nvd - Published: 2023-03-25 00:15 - Updated: 2026-06-17 05:45

Severity

7.5 (High) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
7.5 (High) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

Summary

References

URL	Tags
security-advisories@github.com	https://github.com/tensorflow/tensorflow/commit/34f8368c535253f5c9cb3a303297743b62442aaa	Patch
security-advisories@github.com	https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5w96-866f-6rm8	Patch, Vendor Advisory
af854a3a-2127-422b-91ae-364da2661108	https://github.com/tensorflow/tensorflow/commit/34f8368c535253f5c9cb3a303297743b62442aaa	Patch
af854a3a-2127-422b-91ae-364da2661108	https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5w96-866f-6rm8	Patch, Vendor Advisory

Impacted products

	Vendor	Product	Version
	google	tensorflow	*

JSON

To clipboard

{
  "affected": [
    {
      "affectedData": [
        {
          "product": "tensorflow",
          "vendor": "tensorflow",
          "versions": [
            {
              "status": "affected",
              "version": "\u003c 2.11.1"
            }
          ]
        }
      ],
      "source": "security-advisories@github.com"
    }
  ],
  "configurations": [
    {
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        {
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              "criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
              "matchCriteriaId": "FAC3DE54-93B4-4D6C-9648-B9D416B9770F",
              "versionEndExcluding": "2.12.0",
              "vulnerable": true
            }
          ],
          "negate": false,
          "operator": "OR"
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  "cveTags": [],
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      "lang": "en",
      "value": "TensorFlow is an end-to-end open source platform for machine learning. Constructing a tflite model with a paramater `filter_input_channel` of less than 1 gives a FPE. This issue has been patched in version 2.12. TensorFlow will also cherrypick the fix commit on TensorFlow 2.11.1.\n"
    }
  ],
  "id": "CVE-2023-27579",
  "lastModified": "2026-06-17T05:45:30.590",
  "metrics": {
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      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "HIGH",
          "baseScore": 7.5,
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          "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"
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        "impactScore": 3.6,
        "source": "security-advisories@github.com",
        "type": "Secondary"
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          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
          "version": "3.1"
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        "exploitabilityScore": 3.9,
        "impactScore": 3.6,
        "source": "nvd@nist.gov",
        "type": "Primary"
      }
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    "ssvcV203": [
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        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "ssvcData": {
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          "options": [
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              "exploitation": "none"
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              "automatable": "yes"
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            {
              "technicalImpact": "partial"
            }
          ],
          "role": "CISA Coordinator",
          "timestamp": "2025-02-19T20:44:58.148388Z",
          "version": "2.0.3"
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  "published": "2023-03-25T00:15:08.183",
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    },
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      "source": "af854a3a-2127-422b-91ae-364da2661108",
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GHSA-5W96-866F-6RM8

Vulnerability from github – Published: 2023-03-24 21:53 – Updated: 2023-03-30 22:23

Summary

TensorFlow has Floating Point Exception in TFLite in conv kernel

Details

Impact

Constructing a tflite model with a paramater filter_input_channel of less than 1 gives a FPE.

Patches

We have patched the issue in GitHub commit 34f8368c535253f5c9cb3a303297743b62442aaa.

The fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability was reported by Wang Xuan of Qihoo 360 AIVul Team.

Severity

7.5 (High)


                  
                    CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.11.1"
            }
          ],
          "type": "ECOSYSTEM"
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    },
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        "ecosystem": "PyPI",
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      },
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              "introduced": "0"
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            }
          ],
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        }
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            {
              "introduced": "0"
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          "type": "ECOSYSTEM"
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    }
  ],
  "aliases": [
    "CVE-2023-27579"
  ],
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    "cwe_ids": [
      "CWE-697"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2023-03-24T21:53:39Z",
    "nvd_published_at": "2023-03-25T00:15:00Z",
    "severity": "HIGH"
  },
  "details": "### Impact\nConstructing a tflite model with a paramater `filter_input_channel` of less than 1 gives a FPE.\n\n\n### Patches\nWe have patched the issue in GitHub commit [34f8368c535253f5c9cb3a303297743b62442aaa](https://github.com/tensorflow/tensorflow/commit/34f8368c535253f5c9cb3a303297743b62442aaa).\n\nThe fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.\n\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis vulnerability was reported by Wang Xuan of Qihoo 360 AIVul Team.\n",
  "id": "GHSA-5w96-866f-6rm8",
  "modified": "2023-03-30T22:23:36Z",
  "published": "2023-03-24T21:53:39Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5w96-866f-6rm8"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-27579"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/34f8368c535253f5c9cb3a303297743b62442aaa"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/tensorflow/tensorflow"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "TensorFlow has Floating Point Exception in TFLite in conv kernel"
}

GSD-2023-27579

Vulnerability from gsd - Updated: 2023-12-13 01:20

Details

Aliases

CVE-2023-27579

Aliases

CVE-2023-27579

JSON

To clipboard

{
  "GSD": {
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    "id": "GSD-2023-27579"
  },
  "gsd": {
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      "exploitCode": "unknown",
      "remediation": "unknown",
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    },
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      "modified": "2023-12-13T01:20:55.354446Z",
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            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
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          },
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        }
      },
      "lastModifiedDate": "2023-03-30T19:18Z",
      "publishedDate": "2023-03-25T00:15Z"
    }
  }
}

MSRC_CVE-2023-27579

Vulnerability from csaf_microsoft - Published: 2023-03-10 00:00 - Updated: 2024-06-30 07:00

Summary

TensorFlow has Floating Point Exception in TFLite in conv kernel

Scope

1 vulnerability in this advisory, including CVE-2023-27579.

CVE-2023-27579

7.5 (High)


                
                  CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

Fixed: 1 product Known affected: 1 product Known not affected: 1 product

https://learn.microsoft.com/en-us/azure/azure-linux/tutoria…

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PYSEC-2026-3111

Vulnerability from pysec - Published: 2026-07-13 14:19 - Updated: 2026-07-13 16:06

Details

Impact

Constructing a tflite model with a paramater filter_input_channel of less than 1 gives a FPE.

Patches

We have patched the issue in GitHub commit 34f8368c535253f5c9cb3a303297743b62442aaa.

The fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability was reported by Wang Xuan of Qihoo 360 AIVul Team.

Severity

7.5 (High)


                  
                    CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

Impacted products

Name	purl
tensorflow	pkg:pypi/tensorflow

Aliases

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow",
        "purl": "pkg:pypi/tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.11.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "0.12.0",
        "0.12.1",
        "1.0.0",
        "1.0.1",
        "1.1.0",
        "1.10.0",
        "1.10.1",
        "1.11.0",
        "1.12.0",
        "1.12.2",
        "1.12.3",
        "1.13.1",
        "1.13.2",
        "1.14.0",
        "1.15.0",
        "1.15.2",
        "1.15.3",
        "1.15.4",
        "1.15.5",
        "1.2.0",
        "1.2.1",
        "1.3.0",
        "1.4.0",
        "1.4.1",
        "1.5.0",
        "1.5.1",
        "1.6.0",
        "1.7.0",
        "1.7.1",
        "1.8.0",
        "1.9.0",
        "2.0.0",
        "2.0.1",
        "2.0.2",
        "2.0.3",
        "2.0.4",
        "2.1.0",
        "2.1.1",
        "2.1.2",
        "2.1.3",
        "2.1.4",
        "2.10.0",
        "2.10.0rc0",
        "2.10.0rc1",
        "2.10.0rc2",
        "2.10.0rc3",
        "2.10.1",
        "2.11.0",
        "2.11.0rc0",
        "2.11.0rc1",
        "2.11.0rc2",
        "2.2.0",
        "2.2.1",
        "2.2.2",
        "2.2.3",
        "2.3.0",
        "2.3.1",
        "2.3.2",
        "2.3.3",
        "2.3.4",
        "2.4.0",
        "2.4.1",
        "2.4.2",
        "2.4.3",
        "2.4.4",
        "2.5.0",
        "2.5.1",
        "2.5.2",
        "2.5.3",
        "2.6.0",
        "2.6.0rc0",
        "2.6.0rc1",
        "2.6.0rc2",
        "2.6.1",
        "2.6.2",
        "2.6.3",
        "2.6.4",
        "2.6.5",
        "2.7.0",
        "2.7.0rc0",
        "2.7.0rc1",
        "2.7.1",
        "2.7.2",
        "2.7.3",
        "2.7.4",
        "2.8.0",
        "2.8.0rc0",
        "2.8.0rc1",
        "2.8.1",
        "2.8.2",
        "2.8.3",
        "2.8.4",
        "2.9.0",
        "2.9.0rc0",
        "2.9.0rc1",
        "2.9.0rc2",
        "2.9.1",
        "2.9.2",
        "2.9.3"
      ]
    }
  ],
  "aliases": [
    "CVE-2023-27579",
    "GHSA-5w96-866f-6rm8"
  ],
  "details": "### Impact\nConstructing a tflite model with a paramater `filter_input_channel` of less than 1 gives a FPE.\n\n\n### Patches\nWe have patched the issue in GitHub commit [34f8368c535253f5c9cb3a303297743b62442aaa](https://github.com/tensorflow/tensorflow/commit/34f8368c535253f5c9cb3a303297743b62442aaa).\n\nThe fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.\n\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis vulnerability was reported by Wang Xuan of Qihoo 360 AIVul Team.\n",
  "id": "PYSEC-2026-3111",
  "modified": "2026-07-13T16:06:56.709139Z",
  "published": "2026-07-13T14:19:57.293092Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5w96-866f-6rm8"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-27579"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/34f8368c535253f5c9cb3a303297743b62442aaa"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/tensorflow/tensorflow"
    },
    {
      "type": "PACKAGE",
      "url": "https://pypi.org/project/tensorflow"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/advisories/GHSA-5w96-866f-6rm8"
    }
  ],
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "TensorFlow has Floating Point Exception in TFLite in conv kernel"
}

PYSEC-2026-3279

Vulnerability from pysec - Published: 2026-07-13 14:19 - Updated: 2026-07-13 16:06

Details

Impact

Constructing a tflite model with a paramater filter_input_channel of less than 1 gives a FPE.

Patches

We have patched the issue in GitHub commit 34f8368c535253f5c9cb3a303297743b62442aaa.

The fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability was reported by Wang Xuan of Qihoo 360 AIVul Team.

Severity

7.5 (High)


                  
                    CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

Impacted products

Name	purl
tensorflow-cpu	pkg:pypi/tensorflow-cpu

Aliases

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu",
        "purl": "pkg:pypi/tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.11.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "1.15.0",
        "2.1.0",
        "2.1.1",
        "2.1.2",
        "2.1.3",
        "2.1.4",
        "2.10.0",
        "2.10.0rc0",
        "2.10.0rc1",
        "2.10.0rc2",
        "2.10.0rc3",
        "2.10.1",
        "2.11.0",
        "2.11.0rc0",
        "2.11.0rc1",
        "2.11.0rc2",
        "2.2.0",
        "2.2.1",
        "2.2.2",
        "2.2.3",
        "2.3.0",
        "2.3.1",
        "2.3.2",
        "2.3.3",
        "2.3.4",
        "2.4.0",
        "2.4.1",
        "2.4.2",
        "2.4.3",
        "2.4.4",
        "2.5.0",
        "2.5.1",
        "2.5.2",
        "2.5.3",
        "2.6.0",
        "2.6.1",
        "2.6.2",
        "2.6.3",
        "2.6.4",
        "2.6.5",
        "2.7.0",
        "2.7.1",
        "2.7.2",
        "2.7.3",
        "2.7.4",
        "2.8.0",
        "2.8.1",
        "2.8.2",
        "2.8.3",
        "2.8.4",
        "2.9.0",
        "2.9.0rc0",
        "2.9.0rc1",
        "2.9.0rc2",
        "2.9.1",
        "2.9.2",
        "2.9.3"
      ]
    }
  ],
  "aliases": [
    "CVE-2023-27579",
    "GHSA-5w96-866f-6rm8"
  ],
  "details": "### Impact\nConstructing a tflite model with a paramater `filter_input_channel` of less than 1 gives a FPE.\n\n\n### Patches\nWe have patched the issue in GitHub commit [34f8368c535253f5c9cb3a303297743b62442aaa](https://github.com/tensorflow/tensorflow/commit/34f8368c535253f5c9cb3a303297743b62442aaa).\n\nThe fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.\n\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis vulnerability was reported by Wang Xuan of Qihoo 360 AIVul Team.\n",
  "id": "PYSEC-2026-3279",
  "modified": "2026-07-13T16:06:25.701362Z",
  "published": "2026-07-13T14:19:57.401217Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5w96-866f-6rm8"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-27579"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/34f8368c535253f5c9cb3a303297743b62442aaa"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/tensorflow/tensorflow"
    },
    {
      "type": "PACKAGE",
      "url": "https://pypi.org/project/tensorflow-cpu"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/advisories/GHSA-5w96-866f-6rm8"
    }
  ],
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "TensorFlow has Floating Point Exception in TFLite in conv kernel"
}

PYSEC-2026-954

Vulnerability from pysec - Published: 2026-07-07 10:17 - Updated: 2026-07-07 11:31

Details

Impact

Constructing a tflite model with a paramater filter_input_channel of less than 1 gives a FPE.

Patches

We have patched the issue in GitHub commit 34f8368c535253f5c9cb3a303297743b62442aaa.

The fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability was reported by Wang Xuan of Qihoo 360 AIVul Team.

Severity

7.5 (High)


                  
                    CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

Impacted products

Name	purl
tensorflow-gpu	pkg:pypi/tensorflow-gpu

Aliases

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu",
        "purl": "pkg:pypi/tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.11.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "0.12.0",
        "0.12.1",
        "1.0.0",
        "1.0.1",
        "1.1.0",
        "1.10.0",
        "1.10.1",
        "1.11.0",
        "1.12.0",
        "1.12.2",
        "1.12.3",
        "1.13.1",
        "1.13.2",
        "1.14.0",
        "1.15.0",
        "1.15.2",
        "1.15.3",
        "1.15.4",
        "1.15.5",
        "1.2.0",
        "1.2.1",
        "1.3.0",
        "1.4.0",
        "1.4.1",
        "1.5.0",
        "1.5.1",
        "1.6.0",
        "1.7.0",
        "1.7.1",
        "1.8.0",
        "1.9.0",
        "2.0.0",
        "2.0.1",
        "2.0.2",
        "2.0.3",
        "2.0.4",
        "2.1.0",
        "2.1.1",
        "2.1.2",
        "2.1.3",
        "2.1.4",
        "2.10.0",
        "2.10.0rc0",
        "2.10.0rc1",
        "2.10.0rc2",
        "2.10.0rc3",
        "2.10.1",
        "2.11.0",
        "2.11.0rc0",
        "2.11.0rc1",
        "2.11.0rc2",
        "2.2.0",
        "2.2.1",
        "2.2.2",
        "2.2.3",
        "2.3.0",
        "2.3.1",
        "2.3.2",
        "2.3.3",
        "2.3.4",
        "2.4.0",
        "2.4.1",
        "2.4.2",
        "2.4.3",
        "2.4.4",
        "2.5.0",
        "2.5.1",
        "2.5.2",
        "2.5.3",
        "2.6.0",
        "2.6.1",
        "2.6.2",
        "2.6.3",
        "2.6.4",
        "2.6.5",
        "2.7.0",
        "2.7.0rc0",
        "2.7.0rc1",
        "2.7.1",
        "2.7.2",
        "2.7.3",
        "2.7.4",
        "2.8.0",
        "2.8.0rc0",
        "2.8.0rc1",
        "2.8.1",
        "2.8.2",
        "2.8.3",
        "2.8.4",
        "2.9.0",
        "2.9.0rc0",
        "2.9.0rc1",
        "2.9.0rc2",
        "2.9.1",
        "2.9.2",
        "2.9.3"
      ]
    }
  ],
  "aliases": [
    "CVE-2023-27579",
    "GHSA-5w96-866f-6rm8"
  ],
  "details": "### Impact\nConstructing a tflite model with a paramater `filter_input_channel` of less than 1 gives a FPE.\n\n\n### Patches\nWe have patched the issue in GitHub commit [34f8368c535253f5c9cb3a303297743b62442aaa](https://github.com/tensorflow/tensorflow/commit/34f8368c535253f5c9cb3a303297743b62442aaa).\n\nThe fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.\n\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis vulnerability was reported by Wang Xuan of Qihoo 360 AIVul Team.\n",
  "id": "PYSEC-2026-954",
  "modified": "2026-07-07T11:31:11.602451Z",
  "published": "2026-07-07T10:17:28.763356Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5w96-866f-6rm8"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-27579"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/34f8368c535253f5c9cb3a303297743b62442aaa"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/tensorflow/tensorflow"
    },
    {
      "type": "PACKAGE",
      "url": "https://pypi.org/project/tensorflow-gpu"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/advisories/GHSA-5w96-866f-6rm8"
    }
  ],
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "TensorFlow has Floating Point Exception in TFLite in conv kernel"
}

Sightings

Author	Source	Type	Date	Other

Nomenclature

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.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
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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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
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CVE-2023-27579 (GCVE-0-2023-27579)

Vulnerability from bitnami_vulndb

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