https://cve.radiocsirt.org/rss/recent/all/10 Most recent entries from all 2026-10-08T23:10:51.182655+00:00 Vulnerability-Lookup csirt@opendfir.org python-feedgen Contains only the most 10 recent entries. https://cve.radiocsirt.org/vuln/cve-2021-29535 CVE-2021-29535 — Heap buffer overflow in `QuantizedMul` 2026-10-08T23:10:51.184429+00:00

Affected: tensorflow

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `QuantizedMul` by passing in invalid thresholds for the quantization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/87cf4d3ea9949051e50ca3f071fc909538a51cd0/tensorflow/core/kernels/quantized_mul_op.cc#L287-L290) assumes that the 4 arguments are always valid scalars and tries to access the numeric value directly. However, if any of these tensors is empty, then `.flat<T>()` is an empty buffer and accessing the element at position 0 results in overflow. 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-m3f9-w3p3-p669 GHSA-m3f9-w3p3-p669 — Heap buffer overflow in `QuantizedMul` 2026-10-08T23:10:51.184486+00:00

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

### Impact An attacker can cause a heap buffer overflow in `QuantizedMul` by passing in invalid thresholds for the quantization:

```python import tensorflow as tf

x = tf.constant([256, 328], shape=[1, 2], dtype=tf.quint8) y = tf.constant([256, 328], shape=[1, 2], dtype=tf.quint8) min_x = tf.constant([], dtype=tf.float32) max_x = tf.constant([], dtype=tf.float32) min_y = tf.constant([], dtype=tf.float32) max_y = tf.constant([], dtype=tf.float32)

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/87cf4d3ea9949051e50ca3f071fc909538a51cd0/tensorflow/core/kernels/quantized_mul_op.cc#L287-L290) assumes that the 4 arguments are always valid scalars and tries to access the numeric value directly:

```cc const float min_x = context->input(2).flat<float>()(0); const float max_x = context->input(3).flat<float>()(0); const float min_y = context->input(4).flat<float>()(0); const float max_y = context->input(5).flat<float>()(0); ```

However, if any of these tensors is empty, then `.flat<T>()` is an empty buffer and accessing the element at position 0 results in overflow.

### Patches We have patched the issue in GitHub commit [efea03b38fb8d3b81762237dc85e579cc5fc6e87](https://github.com/tensorflow/tensorflow/commit/efea03b38fb8d3b81762237dc85e579cc5fc6e87).

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, Ten…