---
id: CVE-2019-16778
aliases:
  - GHSA-844w-j86r-4x2j
  - PYSEC-2019-209
  - PYSEC-2019-227
  - PYSEC-2019-234
title: Heap buffer overflow in `UnsortedSegmentSum` in TensorFlow
summary: Heap buffer overflow in `UnsortedSegmentSum` in TensorFlow
severity: low
cvss: 2.6
cvssVector: 'CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:L'
vendor: tensorflow
product: tensorflow
ecosystem: pip
affected:
  - tensorflow < 1.15.0
  - tensorflow-cpu < 1.15.0
  - tensorflow-gpu < 1.15.0
patched:
  - tensorflow 1.15.0
  - tensorflow-cpu 1.15.0
  - tensorflow-gpu 1.15.0
published: '2019-12-16'
updated: '2026-07-08'
source: OSV
sourceUrl: 'https://osv.dev/vulnerability/GHSA-844w-j86r-4x2j'
references:
  - url: >-
      https://github.com/tensorflow/tensorflow/security/advisories/GHSA-844w-j86r-4x2j
  - url: 'https://nvd.nist.gov/vuln/detail/CVE-2019-16778'
  - url: >-
      https://github.com/tensorflow/tensorflow/commit/db4f9717c41bccc3ce10099ab61996b246099892
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2019-227.yaml
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2019-234.yaml
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2019-209.yaml
  - url: 'https://github.com/tensorflow/tensorflow'
  - url: >-
      https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2019-002.md
tags:
  - osv
  - pip
epss: 0.00788
epssPercentile: 0.54716
ingestedAt: '2026-07-08T18:25:47.289Z'
---

## Overview

### Impact

A heap buffer overflow in `UnsortedSegmentSum` can be produced when the `Index` template argument is `int32`. In this case `data_size` and `num_segments` fields are truncated from `int64` to `int32` and can produce negative numbers, resulting in accessing out of bounds heap memory.

This is unlikely to be exploitable and was detected and fixed internally. We are making the security advisory only to notify users that it is better to update to TensorFlow 1.15 or 2.0 or later as these versions already have this fixed.

### Patches

Patched by db4f9717c41bccc3ce10099ab61996b246099892 and released in all official releases after 1.15 and 2.0.

### For more information
Please consult [`SECURITY.md`](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.

## Affected packages

- `tensorflow < 1.15.0`
- `tensorflow-cpu < 1.15.0`
- `tensorflow-gpu < 1.15.0`

## Remediation

Upgrade to a patched release:

- `tensorflow 1.15.0`
- `tensorflow-cpu 1.15.0`
- `tensorflow-gpu 1.15.0`