| Package | Affected versions | Patched versions |
|---|---|---|
| tensorflow | ≥ 2.2.0, < 2.2.3≥ 2.3.0, < 2.3.3≥ 2.4.0, < 2.4.2< 2.1.4 | 2.2.32.3.32.4.22.1.4 |
| tensorflow-cpu | ≥ 2.2.0, < 2.2.3≥ 2.3.0, < 2.3.3≥ 2.4.0, < 2.4.2< 2.1.4 | 2.2.32.3.32.4.22.1.4 |
| tensorflow-gpu | ≥ 2.2.0, < 2.2.3≥ 2.3.0, < 2.3.3≥ 2.4.0, < 2.4.2< 2.1.4 | 2.2.32.3.32.4.22.1.4 |
| tensorflow | ≥ 2.2.0, < 2.2.3≥ 2.3.0, < 2.3.3≥ 2.4.0, < 2.4.2< 2.1.4 | 2.2.32.3.32.4.22.1.4 |
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.
Running one of these products? Scan your site to see whether it exposes a vulnerable version.
Scan my site free