---
id: CVE-2020-15200
aliases:
  - GHSA-x7rp-74x2-mjf3
  - BIT-tensorflow-2020-15200
  - PYSEC-2020-123
  - PYSEC-2020-280
  - PYSEC-2020-315
title: Segfault in Tensorflow
summary: Segfault in Tensorflow
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 >= 2.3.0, < 2.3.1'
  - 'tensorflow-cpu >= 2.3.0, < 2.3.1'
  - 'tensorflow-gpu >= 2.3.0, < 2.3.1'
patched:
  - tensorflow 2.3.1
  - tensorflow-cpu 2.3.1
  - tensorflow-gpu 2.3.1
published: '2020-09-25'
updated: '2026-07-08'
source: OSV
sourceUrl: 'https://osv.dev/vulnerability/GHSA-x7rp-74x2-mjf3'
references:
  - url: >-
      https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x7rp-74x2-mjf3
  - url: 'https://nvd.nist.gov/vuln/detail/CVE-2020-15200'
  - url: >-
      https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-280.yaml
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-315.yaml
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-123.yaml
  - url: 'https://github.com/tensorflow/tensorflow'
  - url: 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1'
tags:
  - osv
  - pip
epss: 0.00851
epssPercentile: 0.56386
ingestedAt: '2026-07-08T18:25:54.139Z'
---

## Overview

### Impact
The `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Thus, the [following code](https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/count_ops.cc#L248-L265
) sets up conditions to cause a heap buffer overflow:
```cc
    auto per_batch_counts = BatchedMap<W>(num_batches);
    int batch_idx = 0;
    for (int idx = 0; idx < num_values; ++idx) {
      while (idx >= splits_values(batch_idx)) {
        batch_idx++;
      }
      const auto& value = values_values(idx);
      if (value >= 0 && (maxlength_ <= 0 || value < maxlength_)) {
        per_batch_counts[batch_idx - 1][value] = 1;
      }
    }
```

A `BatchedMap` is equivalent to a vector where each element is a hashmap. However, if the first element of `splits_values` is not 0, `batch_idx` will never be 1, hence there will be no hashmap at index 0 in `per_batch_counts`. Trying to access that in the user code results in a segmentation fault.

### Patches
We have patched the issue in 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and will release a patch release.

We recommend users to upgrade to TensorFlow 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 is a variant of [GHSA-p5f8-gfw5-33w4](https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p5f8-gfw5-33w4)

## Affected packages

- `tensorflow >= 2.3.0, < 2.3.1`
- `tensorflow-cpu >= 2.3.0, < 2.3.1`
- `tensorflow-gpu >= 2.3.0, < 2.3.1`

## Remediation

Upgrade to a patched release:

- `tensorflow 2.3.1`
- `tensorflow-cpu 2.3.1`
- `tensorflow-gpu 2.3.1`