https://cve.radiocsirt.org/rss/recent/all/10 Most recent entries from all 2026-10-25T23:48:17.548415+00:00 Vulnerability-Lookup csirt@opendfir.org python-feedgen Contains only the most 10 recent entries. https://cve.radiocsirt.org/vuln/cve-2020-15265 CVE-2020-15265 — Segfault in Tensorflow 2026-10-25T23:48:17.550864+00:00

Affected: tensorflow

In Tensorflow before version 2.4.0, an attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dim_size only does a DCHECK to validate the argument and then uses it to access the corresponding element of an array. Since in normal builds, `DCHECK`-like macros are no-ops, this results in segfault and access out of bounds of the array. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.

 https://cve.radiocsirt.org/vuln/ghsa-rrfp-j2mp-hq9c GHSA-rrfp-j2mp-hq9c — Segfault in `tf.quantization.quantize_and_dequantize` 2026-10-25T23:48:17.550917+00:00

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

### Impact An attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`:

```python tf.quantization.quantize_and_dequantize( input=[2.5, 2.5], input_min=[0,0], input_max=[1,1], axis=10) ```

This results in accessing [a dimension outside the rank of the input tensor](https://github.com/tensorflow/tensorflow/blob/0225022b725993bfc19b87a02a2faaad9a53bc17/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L74) in the C++ kernel implementation: ``` const int depth = (axis_ == -1) ? 1 : input.dim_size(axis_); ```

However, [`dim_size` only does a `DCHECK`](https://github.com/tensorflow/tensorflow/blob/0225022b725993bfc19b87a02a2faaad9a53bc17/tensorflow/core/framework/tensor_shape.cc#L292-L307) to validate the argument and then uses it to access the corresponding element of an array: ``` int64 TensorShapeBase<Shape>::dim_size(int d) const { DCHECK_GE(d, 0); DCHECK_LT(d, dims()); DoStuffWith(dims_[d]); } ```

Since in normal builds, `DCHECK`-like macros are no-ops, this results in segfault and access out of bounds of the array.

### Patches

We have patched the issue in eccb7ec454e6617738554a255d77f08e60ee0808 and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.

### 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…