CVSS3
Attack Vector
NETWORK
Attack Complexity
LOW
Privileges Required
LOW
User Interaction
NONE
Scope
UNCHANGED
Confidentiality Impact
NONE
Integrity Impact
NONE
Availability Impact
HIGH
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
EPSS
Percentile
30.4%
A malicious invalid input crashes a tensorflow model (Check Failed) and can be used to trigger a denial of service attack.
To minimize the bug, we built a simple single-layer TensorFlow model containing a Convolution3DTranspose layer, which works well with expected inputs and can be deployed in real-world systems. However, if we call the model with a malicious input which has a zero dimension, it gives Check Failed failure and crashes.
import tensorflow as tf
class MyModel(tf.keras.Model):
def __init__(self):
super().__init__()
self.conv = tf.keras.layers.Convolution3DTranspose(2, [3,3,3], padding="same")
def call(self, input):
return self.conv(input)
model = MyModel() # Defines a valid model.
x = tf.random.uniform([1, 32, 32, 32, 3], minval=0, maxval=0, dtype=tf.float32) # This is a valid input.
output = model.predict(x)
print(output.shape) # (1, 32, 32, 32, 2)
x = tf.random.uniform([1, 32, 32, 0, 3], dtype=tf.float32) # This is an invalid input.
output = model(x) # crash
This Convolution3DTranspose layer is a very common API in modern neural networks. The ML models containing such vulnerable components could be deployed in ML applications or as cloud services. This failure could be potentially used to trigger a denial of service attack on ML cloud services.
We have patched the issue in
The fix will be included in TensorFlow 2.12.0. We will also cherrypick this commit on TensorFlow 2.11.1
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Vendor | Product | Version | CPE |
---|---|---|---|
* | tensorflow-cpu | * | cpe:2.3:a:*:tensorflow-cpu:*:*:*:*:*:*:*:* |
tensorflow | tensorflow | * | cpe:2.3:a:tensorflow:tensorflow:*:*:*:*:*:*:*:* |
github.com/advisories/GHSA-fxgc-95xx-grvq
github.com/keras-team/keras/commit/85db5d07db54b853484bfd358c3894d948c36baf
github.com/tensorflow/tensorflow/commit/948fe6369a5711d4b4568ea9bbf6015c6dfb77e2
github.com/tensorflow/tensorflow/security/advisories/GHSA-fxgc-95xx-grvq
nvd.nist.gov/vuln/detail/CVE-2023-25661