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githubGitHub Advisory DatabaseGHSA-FXQH-CFJM-FP93
HistoryMay 21, 2021 - 2:24 p.m.

Division by 0 in `Reverse`

2021-05-2114:24:39
CWE-369
GitHub Advisory Database
github.com
9

2.1 Low

CVSS2

Attack Vector

LOCAL

Attack Complexity

LOW

Authentication

NONE

Confidentiality Impact

NONE

Integrity Impact

NONE

Availability Impact

PARTIAL

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

5.5 Medium

CVSS3

Attack Vector

LOCAL

Attack Complexity

LOW

Privileges Required

LOW

User Interaction

NONE

Scope

UNCHANGED

Confidentiality Impact

NONE

Integrity Impact

NONE

Availability Impact

HIGH

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

0.0004 Low

EPSS

Percentile

12.8%

Impact

An attacker can cause a denial of service via a FPE runtime error in tf.raw_ops.Reverse:

import tensorflow as tf

tensor_input = tf.constant([], shape=[0, 1, 1], dtype=tf.int32)
dims = tf.constant([False, True, False], shape=[3], dtype=tf.bool)

tf.raw_ops.Reverse(tensor=tensor_input, dims=dims)

This is because the implementation performs a division based on the first dimension of the tensor argument:

const int64 N = input.dim_size(0);
const int64 cost_per_unit = input.NumElements() / N;

Since this is controlled by the user, an attacker can trigger a denial of service.

Patches

We have patched the issue in GitHub commit 4071d8e2f6c45c1955a811fee757ca2adbe462c1.

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been reported by Ying Wang and Yakun Zhang of Baidu X-Team.

Affected configurations

Vulners
Node
tensorflowgpuRange<2.4.2
OR
tensorflowgpuRange<2.3.3
OR
tensorflowgpuRange<2.2.3
OR
tensorflowgpuRange<2.1.4
OR
tensorflowcpuRange<2.4.2
OR
tensorflowcpuRange<2.3.3
OR
tensorflowcpuRange<2.2.3
OR
tensorflowcpuRange<2.1.4
OR
tensorflowtensorflowRange<2.4.2
OR
tensorflowtensorflowRange<2.3.3
OR
tensorflowtensorflowRange<2.2.3
OR
tensorflowtensorflowRange<2.1.4

2.1 Low

CVSS2

Attack Vector

LOCAL

Attack Complexity

LOW

Authentication

NONE

Confidentiality Impact

NONE

Integrity Impact

NONE

Availability Impact

PARTIAL

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

5.5 Medium

CVSS3

Attack Vector

LOCAL

Attack Complexity

LOW

Privileges Required

LOW

User Interaction

NONE

Scope

UNCHANGED

Confidentiality Impact

NONE

Integrity Impact

NONE

Availability Impact

HIGH

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

0.0004 Low

EPSS

Percentile

12.8%

Related for GHSA-FXQH-CFJM-FP93