3.6 Low
CVSS2
Attack Vector
LOCAL
Attack Complexity
LOW
Authentication
NONE
Confidentiality Impact
PARTIAL
Integrity Impact
NONE
Availability Impact
PARTIAL
AV:L/AC:L/Au:N/C:P/I:N/A:P
7.1 High
CVSS3
Attack Vector
LOCAL
Attack Complexity
LOW
Privileges Required
LOW
User Interaction
NONE
Scope
UNCHANGED
Confidentiality Impact
HIGH
Integrity Impact
NONE
Availability Impact
HIGH
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H
0.0005 Low
EPSS
Percentile
17.8%
An attacker can read data outside of bounds of heap allocated buffer in tf.raw_ops.QuantizeAndDequantizeV3
:
import tensorflow as tf
tf.raw_ops.QuantizeAndDequantizeV3(
input=[2.5,2.5], input_min=[0,0], input_max=[1,1], num_bits=[30],
signed_input=False, range_given=False, narrow_range=False, axis=3)
This is because the implementation does not validate the value of user supplied axis
attribute before using it to index in the array backing the input
argument:
const int depth = (axis_ == -1) ? 1 : input.dim_size(axis_);
We have patched the issue in GitHub commit 99085e8ff02c3763a0ec2263e44daec416f6a387.
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.
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
This vulnerability has been reported by Aivul Team from Qihoo 360.
3.6 Low
CVSS2
Attack Vector
LOCAL
Attack Complexity
LOW
Authentication
NONE
Confidentiality Impact
PARTIAL
Integrity Impact
NONE
Availability Impact
PARTIAL
AV:L/AC:L/Au:N/C:P/I:N/A:P
7.1 High
CVSS3
Attack Vector
LOCAL
Attack Complexity
LOW
Privileges Required
LOW
User Interaction
NONE
Scope
UNCHANGED
Confidentiality Impact
HIGH
Integrity Impact
NONE
Availability Impact
HIGH
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H
0.0005 Low
EPSS
Percentile
17.8%