---
id: CVE-2020-15207
aliases:
  - GHSA-q4qf-3fc6-8x34
  - BIT-tensorflow-2020-15207
  - PYSEC-2020-130
  - PYSEC-2020-287
  - PYSEC-2020-322
title: Segfault and data corruption in tensorflow-lite
summary: Segfault and data corruption in tensorflow-lite
severity: high
cvss: 8.7
cvssVector: 'CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:N/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: '2026-09-10'
sourceUpdated: '2026-09-10T03:48:57.818899589Z'
source: OSV
sourceUrl: 'https://osv.dev/vulnerability/GHSA-q4qf-3fc6-8x34'
references:
  - url: >-
      https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q4qf-3fc6-8x34
  - url: 'https://nvd.nist.gov/vuln/detail/CVE-2020-15207'
  - url: >-
      https://github.com/tensorflow/tensorflow/commit/2d88f470dea2671b430884260f3626b1fe99830a
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-287.yaml
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-322.yaml
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-130.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: 0.01243
epssPercentile: 0.67442
ingestedAt: '2026-09-12T03:13:01.720Z'
---

## Overview

### Impact
To mimic Python's indexing with negative values, TFLite uses `ResolveAxis` to convert negative values to positive indices. However, the only check that the converted index is now valid is only present in debug builds:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/internal/reference/reduce.h#L68-L72

If the `DCHECK` does not trigger, then code execution moves ahead with a negative index. This, in turn, results in accessing data out of bounds which results in segfaults and/or data corruption.
### Patches
We have patched the issue in 2d88f470dea2671b430884260f3626b1fe99830a and will release patch releases for all versions between 1.15 and 2.3.

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`