Vulnerability-Lookup

FKIE_CVE-2020-26267

Vulnerability from fkie_nvd - Published: 2020-12-10 23:15 - Updated: 2026-06-17 03:07

Severity

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

Summary

In affected versions of TensorFlow the tf.raw_ops.DataFormatVecPermute API does not validate the src_format and dst_format attributes. The code assumes that these two arguments define a permutation of NHWC. This can result in uninitialized memory accesses, read outside of bounds and even crashes. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.

References

URL	Tags
security-advisories@github.com	https://github.com/tensorflow/tensorflow/commit/ebc70b7a592420d3d2f359e4b1694c236b82c7ae	Patch, Third Party Advisory
security-advisories@github.com	https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c9f3-9wfr-wgh7	Exploit, Patch, Third Party Advisory
af854a3a-2127-422b-91ae-364da2661108	https://github.com/tensorflow/tensorflow/commit/ebc70b7a592420d3d2f359e4b1694c236b82c7ae	Patch, Third Party Advisory
af854a3a-2127-422b-91ae-364da2661108	https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c9f3-9wfr-wgh7	Exploit, Patch, Third Party Advisory

Impacted products

Vendor	Product	Version
google	tensorflow	*
google	tensorflow	*
google	tensorflow	*
google	tensorflow	*
google	tensorflow	*

JSON

To clipboard

{
  "affected": [
    {
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          "product": "tensorflow",
          "vendor": "tensorflow",
          "versions": [
            {
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              "version": "\u003c 1.15.5"
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              "version": "\u003e= 2.0.0, \u003c 2.0.4"
            },
            {
              "status": "affected",
              "version": "\u003e= 2.1.0, \u003c 2.1.3"
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              "version": "\u003e= 2.2.0, \u003c 2.2.2"
            },
            {
              "status": "affected",
              "version": "\u003e= 2.3.0, \u003c 2.3.2"
            }
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      ],
      "source": "security-advisories@github.com"
    }
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  "configurations": [
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      "nodes": [
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              "matchCriteriaId": "CA3A54AC-E0F8-4741-8A80-04EEF746B14B",
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            }
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  ],
  "cveTags": [],
  "descriptions": [
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      "lang": "en",
      "value": "In affected versions of TensorFlow the tf.raw_ops.DataFormatVecPermute API does not validate the src_format and dst_format attributes. The code assumes that these two arguments define a permutation of NHWC. This can result in uninitialized memory accesses, read outside of bounds and even crashes. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0."
    },
    {
      "lang": "es",
      "value": "En las versiones afectadas de TensorFlow, la API tf.raw_ops.DataFormatVecPermute no comprueba los atributos src_format y dst_format.\u0026#xa0;El c\u00f3digo asume que estos dos argumentos definen una permutaci\u00f3n de NHWC.\u0026#xa0;Esto puede resultar en accesos de memoria no inicializados, lectura fuera de l\u00edmites e incluso fallos.\u0026#xa0;Esto es corregido en las versiones 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2 y 2.4.0."
    }
  ],
  "id": "CVE-2020-26267",
  "lastModified": "2026-06-17T03:07:57.653",
  "metrics": {
    "cvssMetricV2": [
      {
        "acInsufInfo": false,
        "baseSeverity": "MEDIUM",
        "cvssData": {
          "accessComplexity": "LOW",
          "accessVector": "LOCAL",
          "authentication": "SINGLE",
          "availabilityImpact": "PARTIAL",
          "baseScore": 4.3,
          "confidentialityImpact": "PARTIAL",
          "integrityImpact": "PARTIAL",
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          "version": "2.0"
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        "impactScore": 6.4,
        "obtainAllPrivilege": false,
        "obtainOtherPrivilege": false,
        "obtainUserPrivilege": false,
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        "type": "Primary",
        "userInteractionRequired": false
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          "attackVector": "LOCAL",
          "availabilityImpact": "LOW",
          "baseScore": 4.4,
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          "confidentialityImpact": "NONE",
          "integrityImpact": "LOW",
          "privilegesRequired": "LOW",
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        "type": "Secondary"
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          "availabilityImpact": "HIGH",
          "baseScore": 7.8,
          "baseSeverity": "HIGH",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "HIGH",
          "privilegesRequired": "LOW",
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  "vulnStatus": "Modified",
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  ]
}

CVE-2020-26267 (GCVE-0-2020-26267)

Vulnerability from cvelistv5 – Published: 2020-12-10 22:10 – Updated: 2024-08-04 15:56

Title

Lack of validation in data format attributes in TensorFlow

Summary

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-125 - Out-of-bounds Read

Assigner

GitHub_M CNA under the mitre root

CNA scorecard C 72/100 over 7630 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/e…	x_refsource_MISC

Impacted products

1 product

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

Show details on NVD website

JSON

To clipboard

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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.

Vulnerability timeline

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

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