Vulnerability Monitor

The vendors, products, and vulnerabilities you care about

CVE-2022-21731


Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ConcatV2` can be used to trigger a denial of service attack via a segfault caused by a type confusion. The `axis` argument is translated into `concat_dim` in the `ConcatShapeHelper` helper function. Then, a value for `min_rank` is computed based on `concat_dim`. This is then used to validate that the `values` tensor has at least the required rank. However, `WithRankAtLeast` receives the lower bound as a 64-bits value and then compares it against the maximum 32-bits integer value that could be represented. Due to the fact that `min_rank` is a 32-bits value and the value of `axis`, the `rank` argument is a negative value, so the error check is bypassed. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.


Published

2022-02-03T12:15:07.873

Last Modified

2025-05-05T17:17:49.390

Status

Modified

Source

[email protected]

Severity

CVSSv3.1: 6.5 (MEDIUM)

CVSSv2 Vector

AV:N/AC:L/Au:S/C:N/I:N/A:P

  • Access Vector: NETWORK
  • Access Complexity: LOW
  • Authentication: SINGLE
  • Confidentiality Impact: NONE
  • Integrity Impact: NONE
  • Availability Impact: PARTIAL
Exploitability Score

8.0

Impact Score

2.9

Weaknesses
  • Type: Primary
    CWE-843
  • Type: Secondary
    CWE-843

Affected Vendors & Products
Type Vendor Product Version/Range Vulnerable?
Application google tensorflow ≤ 2.5.2 Yes
Application google tensorflow ≤ 2.6.2 Yes
Application google tensorflow 2.7.0 Yes

References