pysec - pysec-2020-301

pysec-2020-301

Vulnerability from pysec

Published

2020-12-10 23:15

Modified

2021-12-09 06:34

Details

In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.

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": "14755416e364f17fb1870882fa778c7fec7f16e3"
            }
          ],
          "repo": "https://github.com/tensorflow/tensorflow",
          "type": "GIT"
        },
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.15.5"
            },
            {
              "introduced": "2.0.0"
            },
            {
              "fixed": "2.0.4"
            },
            {
              "introduced": "2.1.0"
            },
            {
              "fixed": "2.1.3"
            },
            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.2"
            },
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "1.15.0",
        "2.1.0",
        "2.1.1",
        "2.1.2",
        "2.2.0",
        "2.2.1",
        "2.3.0",
        "2.3.1"
      ]
    }
  ],
  "aliases": [
    "CVE-2020-26270",
    "GHSA-m648-33qf-v3gp"
  ],
  "details": "In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.",
  "id": "PYSEC-2020-301",
  "modified": "2021-12-09T06:34:44.825248Z",
  "published": "2020-12-10T23:15:00Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m648-33qf-v3gp"
    },
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/14755416e364f17fb1870882fa778c7fec7f16e3"
    }
  ]
}

CVE-2020-26270 (GCVE-0-2020-26270)

Vulnerability from cvelistv5

Published

2020-12-10 22:10

Modified

2024-08-04 15:56

Severity ?

4.4 (Medium) - CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L

CWE

CWE-20 - Improper Input Validation

Summary

References

URL

Tags

	https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m648-33qf-v3gp	x_refsource_CONFIRM
	https://github.com/tensorflow/tensorflow/commit/14755416e364f17fb1870882fa778c7fec7f16e3	x_refsource_MISC

Impacted products

	Vendor	Product	Version
	tensorflow	tensorflow	Version: < 1.15.5 Version: >= 2.0.0, < 2.0.4 Version: >= 2.1.0, < 2.1.3 Version: >= 2.2.0, < 2.2.2 Version: >= 2.3.0, < 2.3.2

Show details on NVD website

JSON

To clipboard

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ghsa-m648-33qf-v3gp

Vulnerability from github

Published

2020-12-10 19:07

Modified

2024-10-28 20:08

Severity ?

4.4 (Medium) - CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L
4.8 (Medium) - CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:L/VA:L/SC:N/SI:N/SA:N

Summary

CHECK-fail in LSTM with zero-length input in TensorFlow

Details

Impact

Running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend.

This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer.

Patches

We have patched the issue in GitHub commit 14755416e364f17fb1870882fa778c7fec7f16e3 and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.

Since this issue also impacts TF versions before 2.4, we will patch all releases between 1.15 and 2.3 inclusive.

For more information

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

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.15.5"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
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            },
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    },
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      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
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      "ranges": [
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          "events": [
            {
              "introduced": "2.1.0"
            },
            {
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          ],
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        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
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              "introduced": "2.2.0"
            },
            {
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        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.2"
            }
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        "name": "tensorflow-cpu"
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    },
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        "name": "tensorflow-cpu"
      },
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          "events": [
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              "introduced": "2.2.0"
            },
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        "name": "tensorflow-cpu"
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        "name": "tensorflow-gpu"
      },
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            },
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            }
          ],
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        }
      ]
    },
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        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.2"
            }
          ],
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        }
      ]
    }
  ],
  "aliases": [
    "CVE-2020-26270"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-20"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2020-12-10T19:06:36Z",
    "nvd_published_at": null,
    "severity": "MODERATE"
  },
  "details": "### Impact\nRunning an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a `CHECK` failure when using the CUDA backend.\n\nThis can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer.\n\n### Patches\nWe have patched the issue in GitHub commit [14755416e364f17fb1870882fa778c7fec7f16e3](https://github.com/tensorflow/tensorflow/commit/14755416e364f17fb1870882fa778c7fec7f16e3) and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.\n\nSince this issue also impacts TF versions before 2.4, we will patch all releases between 1.15 and 2.3 inclusive.\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.",
  "id": "GHSA-m648-33qf-v3gp",
  "modified": "2024-10-28T20:08:27Z",
  "published": "2020-12-10T19:07:31Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m648-33qf-v3gp"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2020-26270"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/14755416e364f17fb1870882fa778c7fec7f16e3"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-301.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-336.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-256.yaml"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/tensorflow/tensorflow"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:L/VA:L/SC:N/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "CHECK-fail in LSTM with zero-length input in TensorFlow"
}

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.
Published Proof of Concept: A public proof of concept is available for this vulnerability.
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

pysec-2020-301

Vulnerability from pysec

CVE-2020-26270 (GCVE-0-2020-26270)

Vulnerability from cvelistv5

ghsa-m648-33qf-v3gp

Vulnerability from github

Impact

Patches

For more information

Tags

Sightings

Nomenclature