Vulnerability-Lookup

Vulnerability from bitnami_vulndb

Published

2024-03-06 11:13

Modified

2025-05-20 10:02

Summary

Segfault in `QuantizedMatMul` in TensorFlow

Details

TensorFlow is an open source platform for machine learning. If QuantizedMatMul is given nonscalar input for: min_a, max_a, min_b, or max_b It gives a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit aca766ac7693bf29ed0df55ad6bfcc78f35e7f48. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

JSON

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{
  "affected": [
    {
      "package": {
        "ecosystem": "Bitnami",
        "name": "tensorflow",
        "purl": "pkg:bitnami/tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.7.0"
            },
            {
              "fixed": "2.7.2"
            },
            {
              "introduced": "2.8.0"
            },
            {
              "fixed": "2.8.1"
            },
            {
              "introduced": "2.9.0"
            },
            {
              "fixed": "2.9.1"
            }
          ],
          "type": "SEMVER"
        }
      ],
      "severity": [
        {
          "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
          "type": "CVSS_V3"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2022-35973"
  ],
  "database_specific": {
    "cpes": [
      "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*"
    ],
    "severity": "High"
  },
  "details": "TensorFlow is an open source platform for machine learning. If `QuantizedMatMul` is given nonscalar input for: `min_a`, `max_a`, `min_b`, or `max_b` It gives a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit aca766ac7693bf29ed0df55ad6bfcc78f35e7f48. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.",
  "id": "BIT-tensorflow-2022-35973",
  "modified": "2025-05-20T10:02:07.006Z",
  "published": "2024-03-06T11:13:38.492Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/aca766ac7693bf29ed0df55ad6bfcc78f35e7f48"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-689c-r7h2-fv9v"
    },
    {
      "type": "WEB",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-35973"
    }
  ],
  "schema_version": "1.5.0",
  "summary": "Segfault in `QuantizedMatMul` in TensorFlow"
}

CVE-2022-35973 (GCVE-0-2022-35973)

Vulnerability from cvelistv5 – Published: 2022-09-16 21:00 – Updated: 2025-04-23 17:02

Title

Segfault in `QuantizedMatMul` in TensorFlow

Summary

TensorFlow is an open source platform for machine learning. If `QuantizedMatMul` is given nonscalar input for: `min_a`, `max_a`, `min_b`, or `max_b` It gives a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit aca766ac7693bf29ed0df55ad6bfcc78f35e7f48. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

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-20 - Improper Input Validation

Assigner

GitHub_M

References

URL

Tags

	https://github.com/tensorflow/tensorflow/security…	x_refsource_CONFIRM
	https://github.com/tensorflow/tensorflow/commit/a…	x_refsource_MISC

Impacted products

	Vendor	Product	Version
	tensorflow	tensorflow	Affected: < 2.7.2 Affected: >= 2.8.0, < 2.8.1 Affected: >= 2.9.0, < 2.9.1

Show details on NVD website

JSON

To clipboard

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        "metrics": [
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Sightings

Author	Source	Type	Date

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.

Action not permitted

Vulnerability from bitnami_vulndb

CVE-2022-35973 (GCVE-0-2022-35973)

Tags

Sightings

Nomenclature