CVE-2021-29544 – tensorflow-gpu

Package

Manager: pip
Name: tensorflow-gpu
Vulnerable Version: >=2.4.0 <2.4.2

Severity

Level: Low

CVSS v3.1: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L

CVSS v4.0: CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N

EPSS: 0.00067 pctl0.21175

Details

CHECK-fail in `QuantizeAndDequantizeV4Grad` ### Impact An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.QuantizeAndDequantizeV4Grad`: ```python import tensorflow as tf gradient_tensor = tf.constant([0.0], shape=[1]) input_tensor = tf.constant([0.0], shape=[1]) input_min = tf.constant([[0.0]], shape=[1, 1]) input_max = tf.constant([[0.0]], shape=[1, 1]) tf.raw_ops.QuantizeAndDequantizeV4Grad( gradients=gradient_tensor, input=input_tensor, input_min=input_min, input_max=input_max, axis=0) ``` This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L162-L163) does not validate the rank of the `input_*` tensors. In turn, this results in the tensors being passes as they are to [`QuantizeAndDequantizePerChannelGradientImpl`](https://github.com/tensorflow/tensorflow/blob/95078c145b5a7a43ee046144005f733092756ab5/tensorflow/core/kernels/quantize_and_dequantize_op.h#L295-L306): ```cc template <typename Device, typename T> struct QuantizeAndDequantizePerChannelGradientImpl { static void Compute(const Device& d, typename TTypes<T, 3>::ConstTensor gradient, typename TTypes<T, 3>::ConstTensor input, const Tensor* input_min_tensor, const Tensor* input_max_tensor, typename TTypes<T, 3>::Tensor input_backprop, typename TTypes<T>::Flat input_min_backprop, typename TTypes<T>::Flat input_max_backprop) { ... auto input_min = input_min_tensor->vec<T>(); auto input_max = input_max_tensor->vec<T>(); ... } ``` However, the `vec<T>` method, requires the rank to 1 and triggers a `CHECK` failure otherwise. ### Patches We have patched the issue in GitHub commit [20431e9044cf2ad3c0323c34888b192f3289af6b](https://github.com/tensorflow/tensorflow/commit/20431e9044cf2ad3c0323c34888b192f3289af6b). The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 as this is the only other affected version. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by Yakun Zhang and Ying Wang of Baidu X-Team.

Metadata

Created: 2021-05-21T14:23:22Z
Modified: 2024-11-19T19:33:14Z
Source: https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2021/05/GHSA-6g85-3hm8-83f9/GHSA-6g85-3hm8-83f9.json
CWE IDs: ["CWE-754"]
Alternative ID: GHSA-6g85-3hm8-83f9
Finding: F002
Auto approve: 1