CVE-2021-37661: Tensorflow Crash Caused By Integer Conversion Vulnerability

Q: What is CVE-2021-37661?

CVE-2021-37661 is a security vulnerability in Tensorflow involving Crash caused by integer conversion to unsigned under CWE-681: Incorrect Conversion between Numeric Types.

Q: Which Tensorflow versions are affected?

Affected versions include releases prior to 2.3.4, 2.4.3, 2.5.1 across affected packages: tensorflow, tensorflow-cpu, tensorflow-gpu.

Q: What version fixes CVE-2021-37661?

Upgrading to 2.3.4, 2.4.3, 2.5.1 (or the latest patched release for your respective branch) resolves the vulnerability.

Q: Is tensorflow affected?

Yes, tensorflow is affected in releases prior to 2.3.4, 2.4.3, 2.5.1. Upgrade your dependency to 2.3.4, 2.4.3, 2.5.1 or later.

Q: Is tensorflow-cpu affected?

Yes, tensorflow-cpu is affected in releases prior to 2.3.4, 2.4.3, 2.5.1. Upgrade your dependency to 2.3.4, 2.4.3, 2.5.1 or later.

Q: What is the CVSS score of CVE-2021-37661?

CVE-2021-37661 has a CVSS v3.1 base score of 5.5 (MODERATE) with vector string CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H.

Q: What CWE is associated with CVE-2021-37661?

CVE-2021-37661 is classified under CWE-681: Incorrect Conversion between Numeric Types (When converting from one data type to another, such as long to integer, data can be omitted or translated in a way that produces unexpected values. If the resulting values are used in a sensitive context, then dangerous behaviors may occur.).

Q: How can I check PyPI dependencies for CVE-2021-37661?

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.

MODERATE

Advisory Identifier: GHSA-gf88-j2mg-cc82

CVSS 5.5

CWE-681

Published 2021-08-25

Advisory Summary

CVE-2021-37661 is a MODERATE (CVSS 5.5) crash caused by integer conversion vulnerability (CWE-681: Incorrect Conversion between Numeric Types) affecting Tensorflow libraries in the PyPI ecosystem. The issue involves crash caused by integer conversion to unsigned. Remediation is available by upgrading affected packages to version 2.3.4, 2.4.3, 2.5.1.

CVE-2021-37661 at a Glance

CVE Identifier CVE-2021-37661

GHSA Identifier GHSA-gf88-j2mg-cc82

Severity MODERATE

CVSS v3.1 Base Score 5.5

CWE Classification CWE-681: Incorrect Conversion between Numeric Types

Affected Product Tensorflow

Package Ecosystem PyPI

Published Date 2021-08-25

Last Updated 2024-11-13

Security Impact

CVSS: 5.5

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

Attack Vector Local (AV:L)

Attack Complexity Low (AC:L)

Privileges Required Low (PR:L)

User Interaction None (UI:N)

Scope Unchanged (S:U)

Confidentiality None (C:N)

Integrity None (I:N)

Availability High (A:H)

How to Fix CVE-2021-37661

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: 2.3.4

pip install tensorflow>=2.3.4

tensorflow fixed: 2.4.3

pip install tensorflow>=2.4.3

tensorflow fixed: 2.5.1

pip install tensorflow>=2.5.1

tensorflow-cpu fixed: 2.3.4

pip install tensorflow-cpu>=2.3.4

tensorflow-cpu fixed: 2.4.3

pip install tensorflow-cpu>=2.4.3

tensorflow-cpu fixed: 2.5.1

pip install tensorflow-cpu>=2.5.1

tensorflow-gpu fixed: 2.3.4

pip install tensorflow-gpu>=2.3.4

tensorflow-gpu fixed: 2.4.3

pip install tensorflow-gpu>=2.4.3

tensorflow-gpu fixed: 2.5.1

pip install tensorflow-gpu>=2.5.1

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-2021-37661, 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 2.3.4), 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-681: Incorrect Conversion between Numeric Types, where when converting from one data type to another, such as long to integer, data can be omitted or translated in a way that produces unexpected values. if the resulting values are used in a sensitive context, then dangerous behaviors may occur. 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 An attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments: ```python import tensorflow as tf from tensorflow.python.ops import gen_boosted_trees_ops import numpy as np v= tf.Variable([0.0, 0.0, 0.0, 0.0, 0.0]) gen_boosted_trees_ops.boosted_trees_create_quantile_stream_resource( quantile_stream_resource_handle = v.handle, epsilon = [74.82224], num_streams = [-49], max_elements = np.int32(586)) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40): ```cc class BoostedTreesQuantileStreamResource : public ResourceBase { public: BoostedTreesQuantileStreamResource(const float epsilon, const int64 max_elements, const int64 num_streams) : are_buckets_ready_(false), epsilon_(epsilon), num_streams_(num_streams), max_elements_(max_elements) { streams_.reserve(num_streams_); ... } } ``` However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. ### Patches We have patched the issue in GitHub commit [8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992](https://github.com/tensorflow/tensorflow/commit/8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992). The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. ### 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-2021-37661 Affected Tensorflow Versions

9 component(s)

Fixed Versions:

2.3.42.4.32.5.1

Product / Package	Ecosystem	Affected Versions	Fixed Version
tensorflow pypi/tensorflow	PyPI	< 2.3.4	2.3.4
tensorflow pypi/tensorflow	PyPI	≥ 2.4.0 < 2.4.3	2.4.3
tensorflow pypi/tensorflow	PyPI	≥ 2.5.0 < 2.5.1 All 1 versions 2.5.0	2.5.1
tensorflow-cpu pypi/tensorflow-cpu	PyPI	< 2.3.4	2.3.4
tensorflow-cpu pypi/tensorflow-cpu	PyPI	≥ 2.4.0 < 2.4.3	2.4.3
tensorflow-cpu pypi/tensorflow-cpu	PyPI	≥ 2.5.0 < 2.5.1 All 1 versions 2.5.0	2.5.1
tensorflow-gpu pypi/tensorflow-gpu	PyPI	< 2.3.4	2.3.4
tensorflow-gpu pypi/tensorflow-gpu	PyPI	≥ 2.4.0 < 2.4.3	2.4.3
tensorflow-gpu pypi/tensorflow-gpu	PyPI	≥ 2.5.0 < 2.5.1 All 1 versions 2.5.0	2.5.1

References

GitHub Advisory / Wiki ADVISORY

https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gf88-j2mg-cc82

NVD — CVE-2021-37661 NVD

https://nvd.nist.gov/vuln/detail/CVE-2021-37661

Security Fix Commit FIX COMMIT

https://github.com/tensorflow/tensorflow/commit/8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992

Tensorflow Source Repository REPOSITORY

https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-574.yaml

Tensorflow Source Repository REPOSITORY

https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-772.yaml

Tensorflow Source Repository REPOSITORY

https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-283.yaml

Tensorflow Source Repository REPOSITORY

https://github.com/tensorflow/tensorflow

Frequently Asked Questions

What is CVE-2021-37661?

CVE-2021-37661 is a security vulnerability in Tensorflow involving Crash caused by integer conversion to unsigned under CWE-681: Incorrect Conversion between Numeric Types.

Which Tensorflow versions are affected?

Affected versions include releases prior to 2.3.4, 2.4.3, 2.5.1 across affected packages: tensorflow, tensorflow-cpu, tensorflow-gpu.

What version fixes CVE-2021-37661?

Upgrading to 2.3.4, 2.4.3, 2.5.1 (or the latest patched release for your respective branch) resolves the vulnerability.

Is tensorflow affected?

Yes, tensorflow is affected in releases prior to 2.3.4, 2.4.3, 2.5.1. Upgrade your dependency to 2.3.4, 2.4.3, 2.5.1 or later.

Is tensorflow-cpu affected?

Yes, tensorflow-cpu is affected in releases prior to 2.3.4, 2.4.3, 2.5.1. Upgrade your dependency to 2.3.4, 2.4.3, 2.5.1 or later.

What is the CVSS score of CVE-2021-37661?

CVE-2021-37661 has a CVSS v3.1 base score of 5.5 (MODERATE) with vector string CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H.

What CWE is associated with CVE-2021-37661?

CVE-2021-37661 is classified under CWE-681: Incorrect Conversion between Numeric Types (When converting from one data type to another, such as long to integer, data can be omitted or translated in a way that produces unexpected values. If the resulting values are used in a sensitive context, then dangerous behaviors may occur.).

How can I check PyPI dependencies for CVE-2021-37661?

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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  "summary" : "Crash caused by integer conversion to unsigned",
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CVSS V3

5.5 MODERATE

Attack Vector Local (AV:L)

Attack Complexity Low (AC:L)

Privileges Required Low (PR:L)

User Interaction None (UI:N)

Scope Unchanged (S:U)

Confidentiality None (C:N)

Integrity None (I:N)

Availability High (A:H)

Vector String

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

Advisory Metadata

Source ID: GHSA-gf88-j2mg-cc82
Schema Version: 1.4.0
Published: 2021-08-25 14:42
Last Modified: 2024-11-13 20:54
Database Record File: advisories/github-reviewed/2021/08/GHSA-gf88-j2mg-cc82/GHSA-gf88-j2mg-cc82.json