---
id: CVE-2020-15265
aliases:
  - GHSA-rrfp-j2mp-hq9c
  - BIT-tensorflow-2020-15265
  - PYSEC-2020-138
  - PYSEC-2020-295
  - PYSEC-2020-330
title: Segfault in `tf.quantization.quantize_and_dequantize`
summary: Segfault in `tf.quantization.quantize_and_dequantize`
severity: medium
cvss: 5.9
cvssVector: 'CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H'
vendor: tensorflow
product: tensorflow
ecosystem: pip
affected:
  - tensorflow < 2.4.0
  - tensorflow-cpu < 2.4.0
  - tensorflow-gpu < 2.4.0
patched:
  - tensorflow 2.4.0
  - tensorflow-cpu 2.4.0
  - tensorflow-gpu 2.4.0
published: '2020-11-13'
updated: '2026-07-08'
source: OSV
sourceUrl: 'https://osv.dev/vulnerability/GHSA-rrfp-j2mp-hq9c'
references:
  - url: >-
      https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rrfp-j2mp-hq9c
  - url: 'https://nvd.nist.gov/vuln/detail/CVE-2020-15265'
  - url: 'https://github.com/tensorflow/tensorflow/issues/42105'
  - url: >-
      https://github.com/tensorflow/tensorflow/commit/eccb7ec454e6617738554a255d77f08e60ee0808
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-295.yaml
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-330.yaml
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-138.yaml
  - url: 'https://github.com/tensorflow/tensorflow'
tags:
  - osv
  - pip
epss: 0.00908
epssPercentile: 0.58261
ingestedAt: '2026-07-08T18:25:53.013Z'
---

## Overview

### 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 with issues and questions.

### Attribution
This vulnerability has been reported in #42105

## Affected packages

- `tensorflow < 2.4.0`
- `tensorflow-cpu < 2.4.0`
- `tensorflow-gpu < 2.4.0`

## Remediation

Upgrade to a patched release:

- `tensorflow 2.4.0`
- `tensorflow-cpu 2.4.0`
- `tensorflow-gpu 2.4.0`