https://cve.radiocsirt.org/rss/recent/all/10 Most recent entries from all 2026-10-09T07:40:54.727134+00:00 Vulnerability-Lookup csirt@opendfir.org python-feedgen Contains only the most 10 recent entries. https://cve.radiocsirt.org/vuln/cve-2021-29534 CVE-2021-29534 — CHECK-fail in SparseConcat 2026-10-09T07:40:54.745210+00:00

Affected: tensorflow

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.SparseConcat`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/b432a38fe0e1b4b904a6c222cbce794c39703e87/tensorflow/core/kernels/sparse_concat_op.cc#L76) takes the values specified in `shapes[0]` as dimensions for the output shape. The `TensorShape` constructor(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L183-L188) uses a `CHECK` operation which triggers when `InitDims`(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L212-L296) returns a non-OK status. This is a legacy implementation of the constructor and operations should use `BuildTensorShapeBase` or `AddDimWithStatus` to prevent `CHECK`-failures in the presence of overflows. 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-6j9c-grc6-5m6g GHSA-6j9c-grc6-5m6g — CHECK-fail in SparseConcat 2026-10-09T07:40:54.745274+00:00

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

### Impact An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.SparseConcat`:

```python import tensorflow as tf import numpy as np

indices_1 = tf.constant([[514, 514], [514, 514]], dtype=tf.int64) indices_2 = tf.constant([[514, 530], [599, 877]], dtype=tf.int64) indices = [indices_1, indices_2]

values_1 = tf.zeros([0], dtype=tf.int64) values_2 = tf.zeros([0], dtype=tf.int64) values = [values_1, values_2]

shape_1 = tf.constant([442, 514, 514, 515, 606, 347, 943, 61, 2], dtype=tf.int64) shape_2 = tf.zeros([9], dtype=tf.int64) shapes = [shape_1, shape_2]

tf.raw_ops.SparseConcat(indices=indices, values=values, shapes=shapes, concat_dim=2) ```

This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/b432a38fe0e1b4b904a6c222cbce794c39703e87/tensorflow/core/kernels/sparse_concat_op.cc#L76) takes the values specified in `shapes[0]` as dimensions for the output shape:

```cc TensorShape input_shape(shapes[0].vec<int64>()); ```

The [`TensorShape` constructor](https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L183-L188) uses a `CHECK` operation which triggers when [`InitDims`](https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L212-L296) returns a non-OK status.

```cc template <class Shape> TensorShapeBase<Shape>::TensorShapeBase(gtl::ArraySlice<int64> dim_sizes) { set_…