Vulnerability-Lookup

GSD-2020-15209

Vulnerability from gsd - Updated: 2023-12-13 01:21

Details

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, a crafted TFLite model can force a node to have as input a tensor backed by a `nullptr` buffer. This can be achieved by changing a buffer index in the flatbuffer serialization to convert a read-only tensor to a read-write one. The runtime assumes that these buffers are written to before a possible read, hence they are initialized with `nullptr`. However, by changing the buffer index for a tensor and implicitly converting that tensor to be a read-write one, as there is nothing in the model that writes to it, we get a null pointer dereference. The issue is patched in commit 0b5662bc, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

Aliases

CVE-2020-15209

Aliases

CVE-2020-15209

JSON

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{
  "GSD": {
    "alias": "CVE-2020-15209",
    "description": "In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, a crafted TFLite model can force a node to have as input a tensor backed by a `nullptr` buffer. This can be achieved by changing a buffer index in the flatbuffer serialization to convert a read-only tensor to a read-write one. The runtime assumes that these buffers are written to before a possible read, hence they are initialized with `nullptr`. However, by changing the buffer index for a tensor and implicitly converting that tensor to be a read-write one, as there is nothing in the model that writes to it, we get a null pointer dereference. The issue is patched in commit 0b5662bc, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.",
    "id": "GSD-2020-15209",
    "references": [
      "https://www.suse.com/security/cve/CVE-2020-15209.html"
    ]
  },
  "gsd": {
    "metadata": {
      "exploitCode": "unknown",
      "remediation": "unknown",
      "reportConfidence": "confirmed",
      "type": "vulnerability"
    },
    "osvSchema": {
      "aliases": [
        "CVE-2020-15209"
      ],
      "details": "In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, a crafted TFLite model can force a node to have as input a tensor backed by a `nullptr` buffer. This can be achieved by changing a buffer index in the flatbuffer serialization to convert a read-only tensor to a read-write one. The runtime assumes that these buffers are written to before a possible read, hence they are initialized with `nullptr`. However, by changing the buffer index for a tensor and implicitly converting that tensor to be a read-write one, as there is nothing in the model that writes to it, we get a null pointer dereference. The issue is patched in commit 0b5662bc, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.",
      "id": "GSD-2020-15209",
      "modified": "2023-12-13T01:21:44.080377Z",
      "schema_version": "1.4.0"
    }
  },
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          "attackComplexity": "HIGH",
          "attackVector": "NETWORK",
          "availabilityImpact": "HIGH",
          "baseScore": 5.9,
          "baseSeverity": "MEDIUM",
          "confidentialityImpact": "NONE",
          "integrityImpact": "NONE",
          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
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          "affected_range": "\u003c1.15.4||\u003e=2.0.0,\u003c2.0.3||\u003e=2.1.0,\u003c2.1.2||\u003e=2.2.0,\u003c2.2.1||\u003e=2.3.0,\u003c2.3.1",
          "affected_versions": "All versions before 1.15.4, all versions starting from 2.0.0 before 2.0.3, all versions starting from 2.1.0 before 2.1.2, all versions starting from 2.2.0 before 2.2.1, all versions starting from 2.3.0 before 2.3.1",
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          "description": "In tensorflow-lite, a crafted `TFLite` model can force a node to have as input a tensor backed by a `nullptr` buffer. This can be achieved by changing a buffer index in the flatbuffer serialization to convert a read-only tensor to a read-write one. The runtime assumes that these buffers are written to before a possible read, hence they are initialized with `nullptr`. However, by changing the buffer index for a tensor and implicitly converting that tensor to be a read-write one, as there is nothing in the model that writes to it, we get a null pointer dereference.",
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          "package_slug": "pypi/tensorflow-cpu",
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          "solution": "Upgrade to versions 2.1.2, 2.2.1, 2.3.1 or above.",
          "title": "NULL Pointer Dereference",
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        },
        {
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          "package_slug": "pypi/tensorflow-gpu",
          "pubdate": "2020-09-25",
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          "title": "NULL Pointer Dereference",
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        },
        {
          "affected_range": "\u003c1.15.4||\u003e=2.0.0,\u003c2.0.3||\u003e=2.1.0,\u003c2.1.2||\u003e=2.2.0,\u003c2.2.1||\u003e=2.3.0,\u003c2.3.1",
          "affected_versions": "All versions before 1.15.4, all versions starting from 2.0.0 before 2.0.3, all versions starting from 2.1.0 before 2.1.2, all versions starting from 2.2.0 before 2.2.1, all versions starting from 2.3.0 before 2.3.1",
          "cvss_v2": "AV:N/AC:M/Au:N/C:N/I:N/A:P",
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          "cwe_ids": [
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            "CWE-476",
            "CWE-937"
          ],
          "date": "2021-09-16",
          "description": "In tensorflow-lite, a crafted `TFLite` model can force a node to have as input a tensor backed by a `nullptr` buffer. This can be achieved by changing a buffer index in the flatbuffer serialization to convert a read-only tensor to a read-write one. The runtime assumes that these buffers are written to before a possible read, hence they are initialized with `nullptr`. However, by changing the buffer index for a tensor and implicitly converting that tensor to be a read-write one, as there is nothing in the model that writes to it, we get a null pointer dereference.",
          "fixed_versions": [
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            "2.0.3",
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          "title": "NULL Pointer Dereference",
          "urls": [
            "https://nvd.nist.gov/vuln/detail/CVE-2020-15209"
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          "uuid": "d0b71674-045f-48e0-8eaf-a9e2c8801ddb"
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    },
    "nvd.nist.gov": {
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          "impactScore": 3.6
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      },
      "lastModifiedDate": "2021-09-16T15:45Z",
      "publishedDate": "2020-09-25T19:15Z"
    }
  }
}

CVE-2020-15209 (GCVE-0-2020-15209)

Vulnerability from cvelistv5 – Published: 2020-09-25 18:45 – Updated: 2024-08-04 13:08

Title

Null pointer dereference in tensorflow-lite

Summary

Severity

5.9 (Medium)


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

CWE

CWE-476 - {"CWE-476":"NULL Pointer Dereference"}

Assigner

GitHub_M CNA under the mitre root

CNA scorecard C 72/100 over 7761 records in the last 180 days details

References

4 references

URL	Tags
https://github.com/tensorflow/tensorflow/releases…	x_refsource_MISC
https://github.com/tensorflow/tensorflow/security…	x_refsource_CONFIRM
https://github.com/tensorflow/tensorflow/commit/0…	x_refsource_MISC
http://lists.opensuse.org/opensuse-security-annou…	vendor-advisoryx_refsource_SUSE

Impacted products

1 product

Vendor	Product	Version
tensorflow	tensorflow	Affected: < 1.15.4 Affected: >= 2.0.0, < 2.0.3 Affected: >= 2.1.0, < 2.1.2 Affected: >= 2.2.0, < 2.2.1 Affected: >= 2.3.0, < 2.3.1

Show details on NVD website

JSON

To clipboard

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          "dateUpdated": "2024-08-04T13:08:22.925Z",
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        ],
        "title": "CVE Program Container"
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    "cna": {
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          "vendor": "tensorflow",
          "versions": [
            {
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        {
          "lang": "en",
          "value": "In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, a crafted TFLite model can force a node to have as input a tensor backed by a `nullptr` buffer. This can be achieved by changing a buffer index in the flatbuffer serialization to convert a read-only tensor to a read-write one. The runtime assumes that these buffers are written to before a possible read, hence they are initialized with `nullptr`. However, by changing the buffer index for a tensor and implicitly converting that tensor to be a read-write one, as there is nothing in the model that writes to it, we get a null pointer dereference. The issue is patched in commit 0b5662bc, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1."
        }
      ],
      "metrics": [
        {
          "cvssV3_1": {
            "attackComplexity": "HIGH",
            "attackVector": "NETWORK",
            "availabilityImpact": "HIGH",
            "baseScore": 5.9,
            "baseSeverity": "MEDIUM",
            "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:H",
            "version": "3.1"
          }
        }
      ],
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          "descriptions": [
            {
              "cweId": "CWE-476",
              "description": "{\"CWE-476\":\"NULL Pointer Dereference\"}",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2020-10-29T15:06:17.000Z",
        "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
        "shortName": "GitHub_M"
      },
      "references": [
        {
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1"
        },
        {
          "tags": [
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          "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qh32-6jjc-qprm"
        },
        {
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          "url": "https://github.com/tensorflow/tensorflow/commit/0b5662bc2be13a8c8f044d925d87fb6e56247cd8"
        },
        {
          "name": "openSUSE-SU-2020:1766",
          "tags": [
            "vendor-advisory",
            "x_refsource_SUSE"
          ],
          "url": "http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html"
        }
      ],
      "source": {
        "advisory": "GHSA-qh32-6jjc-qprm",
        "discovery": "UNKNOWN"
      },
      "title": "Null pointer dereference in tensorflow-lite",
      "x_legacyV4Record": {
        "CVE_data_meta": {
          "ASSIGNER": "security-advisories@github.com",
          "ID": "CVE-2020-15209",
          "STATE": "PUBLIC",
          "TITLE": "Null pointer dereference in tensorflow-lite"
        },
        "affects": {
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                    {
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                            "version_value": "\u003c 1.15.4"
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                            "version_value": "\u003e= 2.0.0, \u003c 2.0.3"
                          },
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                            "version_value": "\u003e= 2.1.0, \u003c 2.1.2"
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                          {
                            "version_value": "\u003e= 2.2.0, \u003c 2.2.1"
                          },
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                            "version_value": "\u003e= 2.3.0, \u003c 2.3.1"
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            }
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        },
        "impact": {
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            "attackComplexity": "HIGH",
            "attackVector": "NETWORK",
            "availabilityImpact": "HIGH",
            "baseScore": 5.9,
            "baseSeverity": "MEDIUM",
            "confidentialityImpact": "NONE",
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  "cveMetadata": {
    "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
    "assignerShortName": "GitHub_M",
    "cveId": "CVE-2020-15209",
    "datePublished": "2020-09-25T18:45:35.000Z",
    "dateReserved": "2020-06-25T00:00:00.000Z",
    "dateUpdated": "2024-08-04T13:08:22.925Z",
    "state": "PUBLISHED"
  },
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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

Sightings and recorded dates, grouped by day · UTC

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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.

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.

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