github - ghsa-mxjj-953w-2c2v

ghsa-mxjj-953w-2c2v

Vulnerability from github

Published

2020-09-25 18:28

Modified

2024-10-30 21:17

Severity ?

7.4 (High) - CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:N
8.6 (High) - CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N

Summary

Data corruption in tensorflow-lite

Details

Impact

When determining the common dimension size of two tensors, TFLite uses a DCHECK which is no-op outside of debug compilation modes: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/internal/types.h#L437-L442

Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors.

Patches

We have patched the issue in 8ee24e7949a20 and will release patch releases for all versions between 1.15 and 2.3.

We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

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 has been reported by members of the Aivul Team from Qihoo 360.

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.15.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.0.0"
            },
            {
              "fixed": "2.0.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.1.0"
            },
            {
              "fixed": "2.1.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.2.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.3.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
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              "introduced": "0"
            },
            {
              "fixed": "1.15.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.0.0"
            },
            {
              "fixed": "2.0.3"
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          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
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        "name": "tensorflow-cpu"
      },
      "ranges": [
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          "events": [
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              "introduced": "2.1.0"
            },
            {
              "fixed": "2.1.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
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        "name": "tensorflow-cpu"
      },
      "ranges": [
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          "events": [
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            {
              "fixed": "2.2.1"
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          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.2.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.3.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.15.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.0.0"
            },
            {
              "fixed": "2.0.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.1.0"
            },
            {
              "fixed": "2.1.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.2.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.3.0"
      ]
    }
  ],
  "aliases": [
    "CVE-2020-15208"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125",
      "CWE-787"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2020-09-25T17:59:45Z",
    "nvd_published_at": "2020-09-25T19:15:00Z",
    "severity": "HIGH"
  },
  "details": "### Impact\nWhen determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes:\nhttps://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/internal/types.h#L437-L442\n\nSince the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors.\n\n### Patches\nWe have patched the issue in 8ee24e7949a20 and will release patch releases for all versions between 1.15 and 2.3.\n\nWe recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.\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 has been reported by members of the Aivul Team from Qihoo 360.",
  "id": "GHSA-mxjj-953w-2c2v",
  "modified": "2024-10-30T21:17:24Z",
  "published": "2020-09-25T18:28:44Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mxjj-953w-2c2v"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2020-15208"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/8ee24e7949a203d234489f9da2c5bf45a7d5157d"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-288.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-323.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-131.yaml"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/tensorflow/tensorflow"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:N",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Data corruption in tensorflow-lite"
}

pysec-2020-323

Vulnerability from pysec

Published

2020-09-25 19:15

Modified

2021-12-09 06:35

Details

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a DCHECK which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

Aliases

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu",
        "purl": "pkg:pypi/tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "8ee24e7949a203d234489f9da2c5bf45a7d5157d"
            }
          ],
          "repo": "https://github.com/tensorflow/tensorflow",
          "type": "GIT"
        },
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.15.4"
            },
            {
              "introduced": "2.0.0"
            },
            {
              "fixed": "2.0.3"
            },
            {
              "introduced": "2.1.0"
            },
            {
              "fixed": "2.1.2"
            },
            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.1"
            },
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "0.12.0",
        "0.12.1",
        "1.0.0",
        "1.0.1",
        "1.1.0",
        "1.10.0",
        "1.10.1",
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        "1.12.0",
        "1.12.2",
        "1.12.3",
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        "1.2.0",
        "1.2.1",
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        "1.4.0",
        "1.4.1",
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        "1.5.1",
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        "1.7.0",
        "1.7.1",
        "1.8.0",
        "1.9.0",
        "2.0.0",
        "2.0.1",
        "2.0.2",
        "2.1.0",
        "2.1.1",
        "2.2.0",
        "2.3.0"
      ]
    }
  ],
  "aliases": [
    "CVE-2020-15208",
    "GHSA-mxjj-953w-2c2v"
  ],
  "details": "In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.",
  "id": "PYSEC-2020-323",
  "modified": "2021-12-09T06:35:14.801373Z",
  "published": "2020-09-25T19:15:00Z",
  "references": [
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/8ee24e7949a203d234489f9da2c5bf45a7d5157d"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mxjj-953w-2c2v"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html"
    }
  ]
}

pysec-2020-131

Vulnerability from pysec

Published

2020-09-25 19:15

Modified

2020-10-29 16:15

Details

Aliases

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow",
        "purl": "pkg:pypi/tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "8ee24e7949a203d234489f9da2c5bf45a7d5157d"
            }
          ],
          "repo": "https://github.com/tensorflow/tensorflow",
          "type": "GIT"
        },
        {
          "events": [
            {
              "introduced": "0"
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            {
              "fixed": "1.15.4"
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            {
              "fixed": "2.0.3"
            },
            {
              "introduced": "2.1.0"
            },
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            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.1"
            },
            {
              "introduced": "2.3.0"
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            {
              "fixed": "2.3.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
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        "0.12.0rc1",
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        "1.1.0rc1",
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        "1.2.0rc1",
        "1.2.0rc2",
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        "1.3.0rc0",
        "1.3.0rc1",
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        "1.4.1",
        "1.5.0rc0",
        "1.5.0rc1",
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        "1.6.0rc1",
        "1.6.0",
        "1.7.0rc0",
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        "1.8.0rc0",
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        "1.9.0rc1",
        "1.9.0rc2",
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        "1.10.0rc1",
        "1.10.0",
        "1.10.1",
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        "1.11.0rc1",
        "1.11.0rc2",
        "1.11.0",
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      ]
    }
  ],
  "aliases": [
    "CVE-2020-15208",
    "GHSA-mxjj-953w-2c2v"
  ],
  "details": "In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.",
  "id": "PYSEC-2020-131",
  "modified": "2020-10-29T16:15:00Z",
  "published": "2020-09-25T19:15:00Z",
  "references": [
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/8ee24e7949a203d234489f9da2c5bf45a7d5157d"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mxjj-953w-2c2v"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html"
    }
  ]
}

pysec-2020-288

Vulnerability from pysec

Published

2020-09-25 19:15

Modified

2021-12-09 06:34

Details

Aliases

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu",
        "purl": "pkg:pypi/tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
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              "introduced": "0"
            },
            {
              "fixed": "8ee24e7949a203d234489f9da2c5bf45a7d5157d"
            }
          ],
          "repo": "https://github.com/tensorflow/tensorflow",
          "type": "GIT"
        },
        {
          "events": [
            {
              "introduced": "0"
            },
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              "fixed": "1.15.4"
            },
            {
              "introduced": "2.0.0"
            },
            {
              "fixed": "2.0.3"
            },
            {
              "introduced": "2.1.0"
            },
            {
              "fixed": "2.1.2"
            },
            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.1"
            },
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "1.15.0",
        "2.1.0",
        "2.1.1",
        "2.2.0",
        "2.3.0"
      ]
    }
  ],
  "aliases": [
    "CVE-2020-15208",
    "GHSA-mxjj-953w-2c2v"
  ],
  "details": "In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.",
  "id": "PYSEC-2020-288",
  "modified": "2021-12-09T06:34:43.041754Z",
  "published": "2020-09-25T19:15:00Z",
  "references": [
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/8ee24e7949a203d234489f9da2c5bf45a7d5157d"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mxjj-953w-2c2v"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html"
    }
  ]
}

cve-2020-15208

Vulnerability from cvelistv5

Published

2020-09-25 18:45

Modified

2024-08-04 13:08

Severity ?

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

Summary

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

References

▼	URL	Tags
	https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1	x_refsource_MISC
	https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mxjj-953w-2c2v	x_refsource_CONFIRM
	https://github.com/tensorflow/tensorflow/commit/8ee24e7949a203d234489f9da2c5bf45a7d5157d	x_refsource_MISC
	http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html	vendor-advisory, x_refsource_SUSE

Impacted products

Vendor

Product

Version

▼

tensorflow

Version: < 1.15.4
Version: >= 2.0.0, < 2.0.3
Version: >= 2.1.0, < 2.1.2
Version: >= 2.2.0, < 2.2.1
Version: >= 2.3.0, < 2.3.1

Show details on NVD website

JSON

To clipboard

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Sightings

Author	Source	Type	Date

Nomenclature

Seen: The vulnerability was mentioned, discussed, or seen somewhere by the user.
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.

Action not permitted

ghsa-mxjj-953w-2c2v

Vulnerability from github

Impact

Patches

For more information

Attribution

pysec-2020-323

Vulnerability from pysec

pysec-2020-131

Vulnerability from pysec

pysec-2020-288

Vulnerability from pysec

cve-2020-15208

Vulnerability from cvelistv5

Tags

Sightings

Nomenclature