---
id: CVE-2020-15195
aliases:
  - GHSA-63xm-rx5p-xvqr
  - BIT-tensorflow-2020-15195
  - PYSEC-2020-118
  - PYSEC-2020-275
  - PYSEC-2020-310
title: Heap buffer overflow in Tensorflow
summary: Heap buffer overflow in Tensorflow
severity: high
cvss: 8.5
cvssVector: 'CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:C/C:H/I:H/A:H'
vendor: tensorflow
product: tensorflow
ecosystem: pip
affected:
  - tensorflow < 1.15.4
  - 'tensorflow >= 2.0.0, < 2.0.3'
  - 'tensorflow >= 2.1.0, < 2.1.2'
  - 'tensorflow >= 2.2.0, < 2.2.1'
  - 'tensorflow >= 2.3.0, < 2.3.1'
  - tensorflow-cpu < 1.15.4
  - 'tensorflow-cpu >= 2.0.0, < 2.0.3'
  - 'tensorflow-cpu >= 2.1.0, < 2.1.2'
  - 'tensorflow-cpu >= 2.2.0, < 2.2.1'
  - 'tensorflow-cpu >= 2.3.0, < 2.3.1'
  - tensorflow-gpu < 1.15.4
  - 'tensorflow-gpu >= 2.0.0, < 2.0.3'
  - 'tensorflow-gpu >= 2.1.0, < 2.1.2'
  - 'tensorflow-gpu >= 2.2.0, < 2.2.1'
  - 'tensorflow-gpu >= 2.3.0, < 2.3.1'
patched:
  - tensorflow 1.15.4
  - tensorflow 2.0.3
  - tensorflow 2.1.2
  - tensorflow 2.2.1
  - tensorflow 2.3.1
  - tensorflow-cpu 1.15.4
  - tensorflow-cpu 2.0.3
  - tensorflow-cpu 2.1.2
  - tensorflow-cpu 2.2.1
  - tensorflow-cpu 2.3.1
  - tensorflow-gpu 1.15.4
  - tensorflow-gpu 2.0.3
  - tensorflow-gpu 2.1.2
  - tensorflow-gpu 2.2.1
  - tensorflow-gpu 2.3.1
published: '2020-09-25'
updated: '2026-07-08'
source: OSV
sourceUrl: 'https://osv.dev/vulnerability/GHSA-63xm-rx5p-xvqr'
references:
  - url: >-
      https://github.com/tensorflow/tensorflow/security/advisories/GHSA-63xm-rx5p-xvqr
  - url: 'https://nvd.nist.gov/vuln/detail/CVE-2020-15195'
  - url: >-
      https://github.com/tensorflow/tensorflow/commit/390611e0d45c5793c7066110af37c8514e6a6c54
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-275.yaml
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-310.yaml
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-118.yaml
  - url: 'https://github.com/tensorflow/tensorflow'
  - url: 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1'
  - url: 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'
tags:
  - osv
  - pip
epss: 0.0095
epssPercentile: 0.59629
ingestedAt: '2026-07-08T18:25:46.277Z'
---

## Overview

### Impact
The implementation of `SparseFillEmptyRowsGrad` uses a double indexing pattern:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/sparse_fill_empty_rows_op.cc#L263-L269

It is possible for `reverse_index_map(i)` to be an index outside of bounds of `grad_values`, thus resulting in a heap buffer overflow.

### Patches
We have patched the issue in 390611e0d45c5793c7066110af37c8514e6a6c54 and will release a patch release for all affected versions.

We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

### 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 by members of the Aivul Team from Qihoo 360.

## Affected packages

- `tensorflow < 1.15.4`
- `tensorflow >= 2.0.0, < 2.0.3`
- `tensorflow >= 2.1.0, < 2.1.2`
- `tensorflow >= 2.2.0, < 2.2.1`
- `tensorflow >= 2.3.0, < 2.3.1`
- `tensorflow-cpu < 1.15.4`
- `tensorflow-cpu >= 2.0.0, < 2.0.3`
- `tensorflow-cpu >= 2.1.0, < 2.1.2`
- `tensorflow-cpu >= 2.2.0, < 2.2.1`
- `tensorflow-cpu >= 2.3.0, < 2.3.1`
- `tensorflow-gpu < 1.15.4`
- `tensorflow-gpu >= 2.0.0, < 2.0.3`
- `tensorflow-gpu >= 2.1.0, < 2.1.2`
- `tensorflow-gpu >= 2.2.0, < 2.2.1`
- `tensorflow-gpu >= 2.3.0, < 2.3.1`

## Remediation

Upgrade to a patched release:

- `tensorflow 1.15.4`
- `tensorflow 2.0.3`
- `tensorflow 2.1.2`
- `tensorflow 2.2.1`
- `tensorflow 2.3.1`
- `tensorflow-cpu 1.15.4`
- `tensorflow-cpu 2.0.3`
- `tensorflow-cpu 2.1.2`
- `tensorflow-cpu 2.2.1`
- `tensorflow-cpu 2.3.1`
- `tensorflow-gpu 1.15.4`
- `tensorflow-gpu 2.0.3`
- `tensorflow-gpu 2.1.2`
- `tensorflow-gpu 2.2.1`
- `tensorflow-gpu 2.3.1`