Vulnerability-Lookup

PYSEC-2020-139

Vulnerability from pysec - Published: 2020-10-21 21:15 - Updated: 2021-09-01 08:19

Details

In Tensorflow before version 2.4.0, when the boxes argument of tf.image.crop_and_resize has a very large value, the CPU kernel implementation receives it as a C++ nan floating point value. Attempting to operate on this is undefined behavior which later produces a segmentation fault. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.

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": "2.4.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "0.12.0rc0",
        "0.12.0rc1",
        "0.12.0",
        "0.12.1",
        "1.0.0",
        "1.0.1",
        "1.1.0rc0",
        "1.1.0rc1",
        "1.1.0rc2",
        "1.1.0",
        "1.2.0rc0",
        "1.2.0rc1",
        "1.2.0rc2",
        "1.2.0",
        "1.2.1",
        "1.3.0rc0",
        "1.3.0rc1",
        "1.3.0rc2",
        "1.3.0",
        "1.4.0rc0",
        "1.4.0rc1",
        "1.4.0",
        "1.4.1",
        "1.5.0rc0",
        "1.5.0rc1",
        "1.5.0",
        "1.5.1",
        "1.6.0rc0",
        "1.6.0rc1",
        "1.6.0",
        "1.7.0rc0",
        "1.7.0rc1",
        "1.7.0",
        "1.7.1",
        "1.8.0rc0",
        "1.8.0rc1",
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        "1.9.0rc2",
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        "1.10.0",
        "1.10.1",
        "1.11.0rc0",
        "1.11.0rc1",
        "1.11.0rc2",
        "1.11.0",
        "1.12.0rc0",
        "1.12.0rc1",
        "1.12.0rc2",
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        "1.12.3",
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        "1.13.0rc1",
        "1.13.0rc2",
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        "1.13.2",
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        "2.0.0",
        "2.0.1",
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        "2.0.4",
        "2.1.0rc0",
        "2.1.0rc1",
        "2.1.0rc2",
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      ]
    }
  ],
  "aliases": [
    "CVE-2020-15266",
    "GHSA-xwhf-g6j5-j5gc"
  ],
  "details": "In Tensorflow before version 2.4.0, when the `boxes` argument of `tf.image.crop_and_resize` has a very large value, the CPU kernel implementation receives it as a C++ `nan` floating point value. Attempting to operate on this is undefined behavior which later produces a segmentation fault. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.",
  "id": "PYSEC-2020-139",
  "modified": "2021-09-01T08:19:35.637564Z",
  "published": "2020-10-21T21:15:00Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/pull/42143/commits/3ade2efec2e90c6237de32a19680caaa3ebc2845"
    },
    {
      "type": "REPORT",
      "url": "https://github.com/tensorflow/tensorflow/issues/42129"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xwhf-g6j5-j5gc"
    }
  ]
}

CVE-2020-15266 (GCVE-0-2020-15266)

Vulnerability from cvelistv5 – Published: 2020-10-21 20:30 – Updated: 2024-08-04 13:15

Title

Undefined behavior in Tensorflow

Summary

In Tensorflow before version 2.4.0, when the `boxes` argument of `tf.image.crop_and_resize` has a very large value, the CPU kernel implementation receives it as a C++ `nan` floating point value. Attempting to operate on this is undefined behavior which later produces a segmentation fault. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.

Severity

3.7 (Low)


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

CWE

CWE-119 - Improper Restriction of Operations within the Bounds of a Memory Buffer

Assigner

GitHub_M mitre root

References

3 references

URL	Tags
https://github.com/tensorflow/tensorflow/security…	x_refsource_CONFIRM
https://github.com/tensorflow/tensorflow/issues/42129	x_refsource_CONFIRM
https://github.com/tensorflow/tensorflow/pull/421…	x_refsource_CONFIRM

Impacted products

1 product

Vendor	Product	Version
tensorflow	tensorflow	Affected: < 2.4.0

Show details on NVD website

JSON

To clipboard

{
  "containers": {
    "adp": [
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        "providerMetadata": {
          "dateUpdated": "2024-08-04T13:15:18.938Z",
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    "cna": {
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          "lang": "en",
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      "metrics": [
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            "attackComplexity": "HIGH",
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            "confidentialityImpact": "NONE",
            "integrityImpact": "NONE",
            "privilegesRequired": "NONE",
            "scope": "UNCHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:L",
            "version": "3.1"
          }
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      "problemTypes": [
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        "discovery": "UNKNOWN"
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            "userInteraction": "NONE",
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}

GHSA-XWHF-G6J5-J5GC

Vulnerability from github – Published: 2020-11-13 17:18 – Updated: 2024-10-28 14:46

Summary

Float cast overflow undefined behavior

Details

Impact

When the boxes argument of tf.image.crop_and_resize has a very large value, the CPU kernel implementation receives it as a C++ nan floating point value. Attempting to operate on this is undefined behavior which later produces a segmentation fault.

Patches

We have patched the issue in c0319231333f0f16e1cc75ec83660b01fedd4182 and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.

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 in #42129

Severity

3.7 (Low)


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

6.3 (Medium)


                  
                    CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.4.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.4.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.4.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2020-15266"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-119"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2020-11-13T17:17:13Z",
    "nvd_published_at": "2020-10-21T21:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nWhen the `boxes` argument of `tf.image.crop_and_resize` has a very large value, the CPU kernel implementation receives it as a C++ `nan` floating point value. Attempting to operate on this is undefined behavior which later produces a segmentation fault.\n\n### Patches\n\nWe have patched the issue in c0319231333f0f16e1cc75ec83660b01fedd4182 and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.\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 in #42129",
  "id": "GHSA-xwhf-g6j5-j5gc",
  "modified": "2024-10-28T14:46:31Z",
  "published": "2020-11-13T17:18:29Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xwhf-g6j5-j5gc"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2020-15266"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/issues/42129"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/pull/42143/commits/3ade2efec2e90c6237de32a19680caaa3ebc2845"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-296.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-331.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-139.yaml"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/tensorflow/tensorflow"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:L",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Float cast overflow undefined behavior"
}

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.

Detection rules are retrieved from Rulezet.

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.
Browse all ATT&CK techniques and the vulnerabilities related to each.

Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.

Action not permitted

PYSEC-2020-139

CVE-2020-15266 (GCVE-0-2020-15266)

GHSA-XWHF-G6J5-J5GC

Impact

Patches

For more information

Attribution

Tags

Sightings

Nomenclature

Related by attack behaviour