Vulnerability-Lookup

Vulnerability from bitnami_vulndb

Published

2024-03-06 11:17

Modified

2026-09-08 08:34

Summary

Integer overflow due to conversion to unsigned in TensorFlow

Details

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of tf.raw_ops.QuantizeAndDequantizeV4Grad is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The implementation uses the axis value as the size argument to absl::InlinedVector constructor. But, the constructor uses an unsigned type for the argument, so the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit 96f364a1ca3009f98980021c4b32be5fdcca33a1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, and TensorFlow 2.4.3, as these are also affected and still in supported range.

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{
  "affected": [
    {
      "package": {
        "ecosystem": "Bitnami",
        "name": "tensorflow",
        "purl": "pkg:bitnami/tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.4"
            },
            {
              "introduced": "2.4.0"
            },
            {
              "fixed": "2.4.3"
            },
            {
              "introduced": "2.5.0"
            },
            {
              "fixed": "2.5.1"
            }
          ],
          "type": "SEMVER"
        }
      ],
      "severity": [
        {
          "score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
          "type": "CVSS_V3"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2021-37645"
  ],
  "database_specific": {
    "cpes": [
      "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
      "cpe:2.3:a:google:tensorflow:2.5.0:*:*:*:*:*:*:*",
      "cpe:2.3:a:google:tensorflow:2.6.0:rc0:*:*:*:*:*:*",
      "cpe:2.3:a:google:tensorflow:2.6.0:rc1:*:*:*:*:*:*",
      "cpe:2.3:a:google:tensorflow:2.6.0:rc2:*:*:*:*:*:*"
    ],
    "severity": "Medium"
  },
  "details": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.QuantizeAndDequantizeV4Grad` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L126) uses the `axis` value as the size argument to `absl::InlinedVector` constructor. But, the constructor uses an unsigned type for the argument, so the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit 96f364a1ca3009f98980021c4b32be5fdcca33a1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, and TensorFlow 2.4.3, as these are also affected and still in supported range.",
  "id": "BIT-tensorflow-2021-37645",
  "modified": "2026-09-08T08:34:36.952Z",
  "published": "2024-03-06T11:17:40.526Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/commit/96f364a1ca3009f98980021c4b32be5fdcca33a1"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9w2p-5mgw-p94c"
    },
    {
      "type": "WEB",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-37645"
    }
  ],
  "schema_version": "1.5.0",
  "summary": "Integer overflow due to conversion to unsigned in TensorFlow"
}

CVE-2021-37645 (GCVE-0-2021-37645)

Vulnerability from cvelistv5 – Published: 2021-08-12 21:05 – Updated: 2024-08-04 01:23

Title

Integer overflow due to conversion to unsigned in TensorFlow

Summary

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.QuantizeAndDequantizeV4Grad` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L126) uses the `axis` value as the size argument to `absl::InlinedVector` constructor. But, the constructor uses an unsigned type for the argument, so the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit 96f364a1ca3009f98980021c4b32be5fdcca33a1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, and TensorFlow 2.4.3, as these are also affected and still in supported range.

Severity

5.5 (Medium)


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

CWE

CWE-681 - Incorrect Conversion between Numeric Types

Assigner

GitHub_M mitre root

References

2 references

URL	Tags
https://github.com/tensorflow/tensorflow/security…	x_refsource_CONFIRM
https://github.com/tensorflow/tensorflow/commit/9…	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version
tensorflow	tensorflow	Affected: >= 2.5.0, < 2.5.1 Affected: < 2.4.3

Show details on NVD website

JSON

To clipboard

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Sightings

Author	Source	Type	Date	Other

Nomenclature

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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.

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.
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Vulnerability from bitnami_vulndb

CVE-2021-37645 (GCVE-0-2021-37645)

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