CVE-2022-35973 Segfault in `QuantizedMatMul` in TensorFlow

2022-09-1621:00:14

CWE-20

GitHub_M

www.cve.org

tensorflow

segfault

quantizedmatmul

cve-2022-35973

denial of service

github

patch

tensorflow 2.10.0

cherrypick

tensorflow 2.9.1

tensorflow 2.8.1

tensorflow 2.7.2

CVSS3

5.9

Attack Vector

NETWORK

Attack Complexity

HIGH

Privileges Required

NONE

User Interaction

NONE

Scope

UNCHANGED

Confidentiality Impact

NONE

Integrity Impact

NONE

Availability Impact

HIGH

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

EPSS

0.001

Percentile

32.3%

JSON

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.

CNA Affected

[
  {
    "product": "tensorflow",
    "vendor": "tensorflow",
    "versions": [
      {
        "status": "affected",
        "version": "< 2.7.2"
      },
      {
        "status": "affected",
        "version": ">= 2.8.0, < 2.8.1"
      },
      {
        "status": "affected",
        "version": ">= 2.9.0, < 2.9.1"
      }
    ]
  }
]