https://cve.radiocsirt.org/rss/recent/all/10 Most recent entries from all 2026-10-09T06:28:03.365842+00:00 Vulnerability-Lookup csirt@opendfir.org python-feedgen Contains only the most 10 recent entries. https://cve.radiocsirt.org/vuln/cve-2021-29528 CVE-2021-29528 — Division by 0 in `QuantizedMul` 2026-10-09T06:28:03.367445+00:00

Affected: tensorflow

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a division by 0 in `tf.raw_ops.QuantizedMul`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/55900e961ed4a23b438392024912154a2c2f5e85/tensorflow/core/kernels/quantized_mul_op.cc#L188-L198) does a division by a quantity that is controlled by the caller. 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.

 https://cve.radiocsirt.org/vuln/ghsa-6f84-42vf-ppwp GHSA-6f84-42vf-ppwp — Division by 0 in `QuantizedMul` 2026-10-09T06:28:03.367501+00:00

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

### Impact An attacker can trigger a division by 0 in `tf.raw_ops.QuantizedMul`:

```python import tensorflow as tf

x = tf.zeros([4, 1], dtype=tf.quint8) y = tf.constant([], dtype=tf.quint8) min_x = tf.constant(0.0) max_x = tf.constant(0.0010000000474974513) min_y = tf.constant(0.0) max_y = tf.constant(0.0010000000474974513)

tf.raw_ops.QuantizedMul(x=x, y=y, min_x=min_x, max_x=max_x, min_y=min_y, max_y=max_y) ```

This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/55900e961ed4a23b438392024912154a2c2f5e85/tensorflow/core/kernels/quantized_mul_op.cc#L188-L198) does a division by a quantity that is controlled by the caller:

```cc template <class T, class Toutput> void VectorTensorMultiply(const T* vector_data, int32 vector_offset, int64 vector_num_elements, const T* tensor_data, int32 tensor_offset, int64 tensor_num_elements, Toutput* output) { for (int i = 0; i < tensor_num_elements; ++i) { const int64 vector_i = i % vector_num_elements; ... } } ```

### Patches We have patched the issue in GitHub commit [a1b11d2fdd1e51bfe18bb1ede804f60abfa92da6](https://github.com/tensorflow/tensorflow/commit/a1b11d2fdd1e51bfe18bb1ede804f60abfa92da6).

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 st…