CVE-2022-35996 Floating point exception in `Conv2D` in TensorFlow

2022-09-1622:55:10

CWE-369

GitHub_M

www.cve.org

denial of service

tensorflow

conv2d

github commit

patched

cve-2022-35996

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

35.2%

JSON

TensorFlow is an open source platform for machine learning. If Conv2D is given empty input and the filter and padding sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 611d80db29dd7b0cfb755772c69d60ae5bca05f9. 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"
      }
    ]
  }
]