CVSS2
Attack Vector
LOCAL
Attack Complexity
LOW
Authentication
NONE
Confidentiality Impact
PARTIAL
Integrity Impact
PARTIAL
Availability Impact
PARTIAL
AV:L/AC:L/Au:N/C:P/I:P/A:P
CVSS3
Attack Vector
LOCAL
Attack Complexity
LOW
Privileges Required
LOW
User Interaction
NONE
Scope
UNCHANGED
Confidentiality Impact
HIGH
Integrity Impact
HIGH
Availability Impact
HIGH
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
EPSS
Percentile
12.6%
Due to incomplete validation in MKL implementation of requantization, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays:
import tensorflow as tf
tf.raw_ops.RequantizationRangePerChannel(
input=[],
input_min=[0,0,0,0,0],
input_max=[1,1,1,1,1],
clip_value_max=1)
The implementation does not validate the dimensions of the input
tensor.
A similar issue occurs in MklRequantizePerChannelOp
:
import tensorflow as tf
from tensorflow.python.ops import gen_math_ops
gen_math_ops.requantize_per_channel(
input=[],
input_min=[-100,-100,-100,-100,-100],
input_max=[-100,-100,-100],
requested_output_min=[-100,-100,-100,-100,-100],
requested_output_max=[],
out_type=tf.int)
The implementation does not perform full validation for all the input arguments.
We have patched the issue in GitHub commit 9e62869465573cb2d9b5053f1fa02a81fce21d69 and in the Github commit 203214568f5bc237603dbab6e1fd389f1572f5c9.
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.
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 members of the Aivul Team from Qihoo 360.
Vendor | Product | Version | CPE |
---|---|---|---|
* | tensorflow-gpu | 2.5.0 | cpe:2.3:a:*:tensorflow-gpu:2.5.0:*:*:*:*:*:*:* |
* | tensorflow-gpu | * | cpe:2.3:a:*:tensorflow-gpu:*:*:*:*:*:*:*:* |
* | tensorflow-cpu | 2.5.0 | cpe:2.3:a:*:tensorflow-cpu:2.5.0:*:*:*:*:*:*:* |
* | tensorflow-cpu | * | cpe:2.3:a:*:tensorflow-cpu:*:*:*:*:*:*:*:* |
tensorflow | tensorflow | 2.5.0 | cpe:2.3:a:tensorflow:tensorflow:2.5.0:*:*:*:*:*:*:* |
tensorflow | tensorflow | * | cpe:2.3:a:tensorflow:tensorflow:*:*:*:*:*:*:*:* |
github.com/advisories/GHSA-v82p-hv3v-p6qp
github.com/tensorflow/tensorflow/commit/203214568f5bc237603dbab6e1fd389f1572f5c9
github.com/tensorflow/tensorflow/commit/9e62869465573cb2d9b5053f1fa02a81fce21d69
github.com/tensorflow/tensorflow/security/advisories/GHSA-v82p-hv3v-p6qp
nvd.nist.gov/vuln/detail/CVE-2021-37665
CVSS2
Attack Vector
LOCAL
Attack Complexity
LOW
Authentication
NONE
Confidentiality Impact
PARTIAL
Integrity Impact
PARTIAL
Availability Impact
PARTIAL
AV:L/AC:L/Au:N/C:P/I:P/A:P
CVSS3
Attack Vector
LOCAL
Attack Complexity
LOW
Privileges Required
LOW
User Interaction
NONE
Scope
UNCHANGED
Confidentiality Impact
HIGH
Integrity Impact
HIGH
Availability Impact
HIGH
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
EPSS
Percentile
12.6%