Vulnerability CVE-2021-37675


Published: 2021-08-12   Modified: 2021-08-13

Description:
TensorFlow is an end-to-end open source platform for machine learning. In affected versions most implementations of convolution operators in TensorFlow are affected by a division by 0 vulnerability where an attacker can trigger a denial of service via a crash. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/framework/common_shape_fns.cc#L577) is missing several validations before doing divisions and modulo operations. We have patched the issue in GitHub commit 8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

Type:

CWE-369

(Divide By Zero)

CVSS2 => (AV:L/AC:L/Au:N/C:N/I:N/A:P)

CVSS Base Score
Impact Subscore
Exploitability Subscore
2.1/10
2.9/10
3.9/10
Exploit range
Attack complexity
Authentication
Local
Low
No required
Confidentiality impact
Integrity impact
Availability impact
None
None
Partial
Affected software
Google -> Tensorflow 

 References:
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c8h-2mv3-49ww
https://github.com/tensorflow/tensorflow/commit/8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4

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