CVE-2022-35970 Segfault in `QuantizedInstanceNorm` in TensorFlow

2022-09-1620:45:13

CWE-20

GitHub_M

www.cve.org

tensorflow

segfault

quantizedinstancenorm

denial of service

patched

github commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0

cherrypick

nonzero rank

denial of service attack

5.9 Medium

CVSS3

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

0.001 Low

EPSS

Percentile

32.5%

JSON

TensorFlow is an open source platform for machine learning. If QuantizedInstanceNorm is given x_min or x_max tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. 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"
      }
    ]
  }
]