CVE-2019-16778: Tensorflow Heap Buffer Overflow Vulnerability

LOW
Advisory Identifier: GHSA-844w-j86r-4x2j
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CVSS 2.6
CWE-122 CWE-681
Published
Advisory Summary

CVE-2019-16778 is a LOW (CVSS 2.6) heap buffer overflow vulnerability (CWE-122: Heap-based Buffer Overflow) affecting Tensorflow libraries in the PyPI ecosystem. The issue involves heap buffer overflow in `unsortedsegmentsum` in tensorflow. Remediation is available by upgrading affected packages to version 1.15.0.

CVE-2019-16778 at a Glance

CVE Identifier CVE-2019-16778
GHSA Identifier GHSA-844w-j86r-4x2j
Severity LOW
CVSS v3.1 Base Score 2.6
CWE Classification CWE-122: Heap-based Buffer Overflow
Affected Product Tensorflow
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 2.6

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:L).

Attack Vector Network (AV:N)
Attack Complexity High (AC:H)
Privileges Required Low (PR:L)
User Interaction Required (UI:R)
Scope Unchanged (S:U)
Confidentiality None (C:N)
Integrity None (I:N)
Availability Low (A:L)

How to Fix CVE-2019-16778

To remediate this vulnerability, upgrade all affected Tensorflow dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

tensorflow fixed: 1.15.0 
pip install tensorflow>=1.15.0
tensorflow-cpu fixed: 1.15.0 
pip install tensorflow-cpu>=1.15.0
tensorflow-gpu fixed: 1.15.0 
pip install tensorflow-gpu>=1.15.0
Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release: 

pip show tensorflow

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2019-16778, inspect your installed packages using pip:

pip show tensorflow

Analyze the terminal output to locate any version of Tensorflow in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 1.15.0), your application is affected.

Note: The pip show tensorflow command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-122: Heap-based Buffer Overflow, where a heap overflow condition is a buffer overflow, where the buffer that can be overwritten is allocated in the heap portion of memory, generally meaning that the buffer was allocated using a routine such as malloc(). In Tensorflow, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

### 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.

CVE-2019-16778 Affected Tensorflow Versions

3 component(s)
Fixed Versions:
1.15.0
Product / Package Ecosystem Affected Versions Fixed Version
tensorflow
pypi/tensorflow
PyPI
< 1.15.0
1.15.0
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
< 1.15.0
1.15.0
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
< 1.15.0
1.15.0

References

GitHub Advisory / Wiki ADVISORY
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-844w-j86r-4x2j
NVD — CVE-2019-16778 NVD
https://nvd.nist.gov/vuln/detail/CVE-2019-16778
Security Fix Commit FIX COMMIT
https://github.com/tensorflow/tensorflow/commit/db4f9717c41bccc3ce10099ab61996b246099892
Tensorflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2019-227.yaml
Tensorflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2019-234.yaml
Tensorflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2019-209.yaml
Tensorflow Source Repository REPOSITORY
https://github.com/tensorflow/tensorflow
Tensorflow Source Repository REPOSITORY
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2019-002.md

Frequently Asked Questions

What is CVE-2019-16778?
CVE-2019-16778 is a security vulnerability in Tensorflow involving Heap buffer overflow in `UnsortedSegmentSum` in TensorFlow under CWE-122: Heap-based Buffer Overflow.
Which Tensorflow versions are affected?
Affected versions include releases prior to 1.15.0 across affected packages: tensorflow, tensorflow-cpu, tensorflow-gpu.
What version fixes CVE-2019-16778?
Upgrading to 1.15.0 (or the latest patched release for your respective branch) resolves the vulnerability.
Is tensorflow affected?
Yes, tensorflow is affected in releases prior to 1.15.0. Upgrade your dependency to 1.15.0 or later.
Is tensorflow-cpu affected?
Yes, tensorflow-cpu is affected in releases prior to 1.15.0. Upgrade your dependency to 1.15.0 or later.
What is the CVSS score of CVE-2019-16778?
CVE-2019-16778 has a CVSS v3.1 base score of 2.6 (LOW) with vector string CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:L.
What CWE is associated with CVE-2019-16778?
CVE-2019-16778 is classified under CWE-122: Heap-based Buffer Overflow (A heap overflow condition is a buffer overflow, where the buffer that can be overwritten is allocated in the heap portion of memory, generally meaning that the buffer was allocated using a routine such as malloc().).
How can I check PyPI dependencies for CVE-2019-16778?
Run the dependency tree command: 'pip show tensorflow'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
View Raw JSON 
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  "schema_version" : "1.4.0",
  "id" : "GHSA-844w-j86r-4x2j",
  "modified" : "2024-10-28T14:44:38Z",
  "published" : "2019-12-16T20:17:10Z",
  "aliases" : [ "CVE-2019-16778" ],
  "summary" : "Heap buffer overflow in `UnsortedSegmentSum` in TensorFlow",
  "details" : "### Impact\n\nA 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.\n\nThis 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.\n\n### Patches\n\nPatched by db4f9717c41bccc3ce10099ab61996b246099892 and released in all official releases after 1.15 and 2.0.\n\n### For more information\nPlease 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.",
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  }, {
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    "url" : "https://github.com/tensorflow/tensorflow/commit/db4f9717c41bccc3ce10099ab61996b246099892"
  }, {
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    "url" : "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2019-227.yaml"
  }, {
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    "url" : "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2019-234.yaml"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2019-209.yaml"
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    "url" : "https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2019-002.md"
  } ],
  "database_specific" : {
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    "severity" : "LOW",
    "github_reviewed" : true,
    "github_reviewed_at" : "2019-12-16T20:16:12Z",
    "nvd_published_at" : "2019-12-16T21:15:00Z"
  }
}