CVE-2020-15202: Tensorflow Integer Truncation Vulnerability

Q: What is CVE-2020-15202?

CVE-2020-15202 is a security vulnerability in Tensorflow involving Integer truncation in Shard API usage under CWE-197: Numeric Truncation Error.

Q: Which Tensorflow versions are affected?

Affected versions include releases prior to 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 across affected packages: tensorflow, tensorflow-cpu, tensorflow-gpu.

Q: What version fixes CVE-2020-15202?

Upgrading to 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 (or the latest patched release for your respective branch) resolves the vulnerability.

Q: Is tensorflow affected?

Yes, tensorflow is affected in releases prior to 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1. Upgrade your dependency to 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 or later.

Q: Is tensorflow-cpu affected?

Yes, tensorflow-cpu is affected in releases prior to 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1. Upgrade your dependency to 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 or later.

Q: What is the CVSS score of CVE-2020-15202?

CVE-2020-15202 has a CVSS v3.1 base score of 9.0 (HIGH) with vector string CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H.

Q: What CWE is associated with CVE-2020-15202?

CVE-2020-15202 is classified under CWE-197: Numeric Truncation Error (Truncation errors occur when a primitive is cast to a primitive of a smaller size and data is lost in the conversion.).

Q: How can I check PyPI dependencies for CVE-2020-15202?

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.

HIGH

Advisory Identifier: GHSA-h6fg-mjxg-hqq4

CVSS 9.0

CWE-197 CWE-754

Published 2020-09-25

Advisory Summary

CVE-2020-15202 is a HIGH (CVSS 9.0) integer truncation vulnerability (CWE-197: Numeric Truncation Error) affecting Tensorflow libraries in the PyPI ecosystem. The issue involves integer truncation in shard api usage. Remediation is available by upgrading affected packages to version 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1.

CVE-2020-15202 at a Glance

CVE Identifier CVE-2020-15202

GHSA Identifier GHSA-h6fg-mjxg-hqq4

Severity HIGH

CVSS v3.1 Base Score 9.0

CWE Classification CWE-197: Numeric Truncation Error

Affected Product Tensorflow

Package Ecosystem PyPI

Published Date 2020-09-25

Last Updated 2024-10-28

Security Impact

CVSS: 9.0

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

Attack Vector Network (AV:N)

Attack Complexity High (AC:H)

Privileges Required None (PR:N)

User Interaction None (UI:N)

Scope Changed (S:C)

Confidentiality High (C:H)

Integrity High (I:H)

Availability High (A:H)

How to Fix CVE-2020-15202

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: 1.15.4

pip install tensorflow>=1.15.4

tensorflow fixed: 2.0.3

pip install tensorflow>=2.0.3

tensorflow fixed: 2.1.2

pip install tensorflow>=2.1.2

tensorflow fixed: 2.2.1

pip install tensorflow>=2.2.1

tensorflow fixed: 2.3.1

pip install tensorflow>=2.3.1

tensorflow-cpu fixed: 1.15.4

pip install tensorflow-cpu>=1.15.4

tensorflow-cpu fixed: 2.0.3

pip install tensorflow-cpu>=2.0.3

tensorflow-cpu fixed: 2.1.2

pip install tensorflow-cpu>=2.1.2

tensorflow-cpu fixed: 2.2.1

pip install tensorflow-cpu>=2.2.1

tensorflow-cpu fixed: 2.3.1

pip install tensorflow-cpu>=2.3.1

tensorflow-gpu fixed: 1.15.4

pip install tensorflow-gpu>=1.15.4

tensorflow-gpu fixed: 2.0.3

pip install tensorflow-gpu>=2.0.3

tensorflow-gpu fixed: 2.1.2

pip install tensorflow-gpu>=2.1.2

tensorflow-gpu fixed: 2.2.1

pip install tensorflow-gpu>=2.2.1

tensorflow-gpu fixed: 2.3.1

pip install tensorflow-gpu>=2.3.1

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-2020-15202, 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 1.15.4), 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-197: Numeric Truncation Error, where truncation errors occur when a primitive is cast to a primitive of a smaller size and data is lost in the conversion. 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 The `Shard` API in TensorFlow expects the last argument to be a function taking two `int64` (i.e., `long long`) arguments: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/util/work_sharder.h#L59-L60 However, there are several places in TensorFlow where a lambda taking `int` or `int32` arguments is being used: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/random_op.cc#L204-L205 https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/random_op.cc#L317-L318 In these cases, if the amount of work to be parallelized is large enough, integer truncation occurs. Depending on how the two arguments of the lambda are used, this can result in segfaults, read/write outside of heap allocated arrays, stack overflows, or data corruption. ### Patches We have patched the issue in 27b417360cbd671ef55915e4bb6bb06af8b8a832 and ca8c013b5e97b1373b3bb1c97ea655e69f31a575. We 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.

CVE-2020-15202 Affected Tensorflow Versions

15 component(s)

Fixed Versions:

1.15.42.0.32.1.22.2.12.3.1

Product / Package	Ecosystem	Affected Versions	Fixed Version
tensorflow pypi/tensorflow	PyPI	< 1.15.4	1.15.4
tensorflow pypi/tensorflow	PyPI	≥ 2.0.0 < 2.0.3	2.0.3
tensorflow pypi/tensorflow	PyPI	≥ 2.1.0 < 2.1.2	2.1.2
tensorflow pypi/tensorflow	PyPI	≥ 2.2.0 < 2.2.1 All 1 versions 2.2.0	2.2.1
tensorflow pypi/tensorflow	PyPI	≥ 2.3.0 < 2.3.1 All 1 versions 2.3.0	2.3.1
tensorflow-cpu pypi/tensorflow-cpu	PyPI	< 1.15.4	1.15.4
tensorflow-cpu pypi/tensorflow-cpu	PyPI	≥ 2.0.0 < 2.0.3	2.0.3
tensorflow-cpu pypi/tensorflow-cpu	PyPI	≥ 2.1.0 < 2.1.2	2.1.2
tensorflow-cpu pypi/tensorflow-cpu	PyPI	≥ 2.2.0 < 2.2.1 All 1 versions 2.2.0	2.2.1
tensorflow-cpu pypi/tensorflow-cpu	PyPI	≥ 2.3.0 < 2.3.1 All 1 versions 2.3.0	2.3.1
tensorflow-gpu pypi/tensorflow-gpu	PyPI	< 1.15.4	1.15.4
tensorflow-gpu pypi/tensorflow-gpu	PyPI	≥ 2.0.0 < 2.0.3	2.0.3
tensorflow-gpu pypi/tensorflow-gpu	PyPI	≥ 2.1.0 < 2.1.2	2.1.2
tensorflow-gpu pypi/tensorflow-gpu	PyPI	≥ 2.2.0 < 2.2.1 All 1 versions 2.2.0	2.2.1
tensorflow-gpu pypi/tensorflow-gpu	PyPI	≥ 2.3.0 < 2.3.1 All 1 versions 2.3.0	2.3.1

References

GitHub Advisory / Wiki ADVISORY

https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h6fg-mjxg-hqq4

NVD — CVE-2020-15202 NVD

https://nvd.nist.gov/vuln/detail/CVE-2020-15202

Security Fix Commit FIX COMMIT

https://github.com/tensorflow/tensorflow/commit/27b417360cbd671ef55915e4bb6bb06af8b8a832

Security Fix Commit FIX COMMIT

https://github.com/tensorflow/tensorflow/commit/ca8c013b5e97b1373b3bb1c97ea655e69f31a575

Tensorflow Source Repository REPOSITORY

https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-282.yaml

Tensorflow Source Repository REPOSITORY

https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-317.yaml

Tensorflow Source Repository REPOSITORY

https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-125.yaml

Tensorflow Source Repository REPOSITORY

https://github.com/tensorflow/tensorflow

Tensorflow Release RELEASE

https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1

Tensorflow Security Information SECURITY

http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html

Frequently Asked Questions

What is CVE-2020-15202?

CVE-2020-15202 is a security vulnerability in Tensorflow involving Integer truncation in Shard API usage under CWE-197: Numeric Truncation Error.

Which Tensorflow versions are affected?

Affected versions include releases prior to 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 across affected packages: tensorflow, tensorflow-cpu, tensorflow-gpu.

What version fixes CVE-2020-15202?

Upgrading to 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 (or the latest patched release for your respective branch) resolves the vulnerability.

Is tensorflow affected?

Yes, tensorflow is affected in releases prior to 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1. Upgrade your dependency to 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 or later.

Is tensorflow-cpu affected?

Yes, tensorflow-cpu is affected in releases prior to 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1. Upgrade your dependency to 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 or later.

What is the CVSS score of CVE-2020-15202?

CVE-2020-15202 has a CVSS v3.1 base score of 9.0 (HIGH) with vector string CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H.

What CWE is associated with CVE-2020-15202?

CVE-2020-15202 is classified under CWE-197: Numeric Truncation Error (Truncation errors occur when a primitive is cast to a primitive of a smaller size and data is lost in the conversion.).

How can I check PyPI dependencies for CVE-2020-15202?

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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    "severity" : "HIGH",
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CVSS V3

9.0 HIGH

Attack Vector Network (AV:N)

Attack Complexity High (AC:H)

Privileges Required None (PR:N)

User Interaction None (UI:N)

Scope Changed (S:C)

Confidentiality High (C:H)

Integrity High (I:H)

Availability High (A:H)

Vector String

CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H

Advisory Metadata

Source ID: GHSA-h6fg-mjxg-hqq4
Schema Version: 1.4.0
Published: 2020-09-25 18:28
Last Modified: 2024-10-28 21:21
Database Record File: advisories/github-reviewed/2020/09/GHSA-h6fg-mjxg-hqq4/GHSA-h6fg-mjxg-hqq4.json