CVE-2021-29607: Tensorflow cpu Incomplete Validation Vulnerability

Q: What is CVE-2021-29607?

CVE-2021-29607 is a security vulnerability in Tensorflow cpu involving Incomplete validation in `SparseSparseMinimum` under CWE-754: Improper Check for Unusual or Exceptional Conditions.

Q: Which Tensorflow cpu versions are affected?

Affected versions include releases prior to 2.3.3, 2.1.4, 2.2.3, 2.4.2 across affected packages: tensorflow-cpu, tensorflow, tensorflow-gpu.

Q: What version fixes CVE-2021-29607?

Upgrading to 2.3.3, 2.1.4, 2.2.3, 2.4.2 (or the latest patched release for your respective branch) resolves the vulnerability.

Q: Is tensorflow-cpu affected?

Yes, tensorflow-cpu is affected in releases prior to 2.3.3, 2.1.4, 2.2.3, 2.4.2. Upgrade your dependency to 2.3.3, 2.1.4, 2.2.3, 2.4.2 or later.

Q: Is tensorflow affected?

Yes, tensorflow is affected in releases prior to 2.1.4, 2.2.3, 2.3.3, 2.4.2. Upgrade your dependency to 2.1.4, 2.2.3, 2.3.3, 2.4.2 or later.

Q: What is the CVSS score of CVE-2021-29607?

CVE-2021-29607 has a CVSS v3.1 base score of 5.3 (MODERATE) with vector string CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:H.

Q: What CWE is associated with CVE-2021-29607?

CVE-2021-29607 is classified under CWE-754: Improper Check for Unusual or Exceptional Conditions (The product does not check or incorrectly checks for unusual or exceptional conditions that are not expected to occur frequently during day to day operation of the product.).

Q: How can I check PyPI dependencies for CVE-2021-29607?

Run the dependency tree command: 'pip show tensorflow-cpu'. 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-gv26-jpj9-c8gq

CVSS 5.3

CWE-754

Published 2022-03-18

Advisory Summary

CVE-2021-29607 is a MODERATE (CVSS 5.3) incomplete validation vulnerability (CWE-754: Improper Check for Unusual or Exceptional Conditions) affecting Tensorflow cpu libraries in the PyPI ecosystem. The issue involves incomplete validation in `sparsesparseminimum`. Remediation is available by upgrading affected packages to version 2.3.3, 2.1.4, 2.2.3, 2.4.2.

CVE-2021-29607 at a Glance

CVE Identifier CVE-2021-29607

GHSA Identifier GHSA-gv26-jpj9-c8gq

Severity MODERATE

CVSS v3.1 Base Score 5.3

CWE Classification CWE-754: Improper Check for Unusual or Exceptional Conditions

Affected Product Tensorflow cpu

Package Ecosystem PyPI

Published Date 2022-03-18

Last Updated 2024-11-13

Security Impact

CVSS: 5.3

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

Attack Vector Local (AV:L)

Attack Complexity High (AC:H)

Privileges Required Low (PR:L)

User Interaction None (UI:N)

Scope Unchanged (S:U)

Confidentiality None (C:N)

Integrity Low (I:L)

Availability High (A:H)

How to Fix CVE-2021-29607

To remediate this vulnerability, upgrade all affected Tensorflow cpu 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-cpu fixed: 2.3.3

pip install tensorflow-cpu>=2.3.3

tensorflow fixed: 2.1.4

pip install tensorflow>=2.1.4

tensorflow fixed: 2.2.3

pip install tensorflow>=2.2.3

tensorflow fixed: 2.3.3

pip install tensorflow>=2.3.3

tensorflow fixed: 2.4.2

pip install tensorflow>=2.4.2

tensorflow-cpu fixed: 2.1.4

pip install tensorflow-cpu>=2.1.4

tensorflow-cpu fixed: 2.2.3

pip install tensorflow-cpu>=2.2.3

tensorflow-cpu fixed: 2.4.2

pip install tensorflow-cpu>=2.4.2

tensorflow-gpu fixed: 2.1.4

pip install tensorflow-gpu>=2.1.4

tensorflow-gpu fixed: 2.2.3

pip install tensorflow-gpu>=2.2.3

tensorflow-gpu fixed: 2.3.3

pip install tensorflow-gpu>=2.3.3

tensorflow-gpu fixed: 2.4.2

pip install tensorflow-gpu>=2.4.2

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-cpu

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2021-29607, inspect your installed packages using pip:

pip show tensorflow-cpu

Analyze the terminal output to locate any version of Tensorflow cpu in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 2.3.3), your application is affected.

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

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-754: Improper Check for Unusual or Exceptional Conditions, where the product does not check or incorrectly checks for unusual or exceptional conditions that are not expected to occur frequently during day to day operation of the product. In Tensorflow cpu, 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 Incomplete validation in `SparseAdd` results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data: ```python import tensorflow as tf a_indices = tf.ones([45, 92], dtype=tf.int64) a_values = tf.ones([45], dtype=tf.int64) a_shape = tf.ones([1], dtype=tf.int64) b_indices = tf.ones([1, 1], dtype=tf.int64) b_values = tf.ones([1], dtype=tf.int64) b_shape = tf.ones([1], dtype=tf.int64) tf.raw_ops.SparseSparseMinimum(a_indices=a_indices, a_values=a_values, a_shape=a_shape, b_indices=b_indices, b_values=b_values, b_shape=b_shape) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_sparse_binary_op_shared.cc) has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of `*_indices` matches the size of corresponding `*_shape`. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation. ### Patches We have patched the issue in GitHub commit [ba6822bd7b7324ba201a28b2f278c29a98edbef2](https://github.com/tensorflow/tensorflow/commit/ba6822bd7b7324ba201a28b2f278c29a98edbef2) followed by GitHub commit [f6fde895ef9c77d848061c0517f19d0ec2682f3a](https://github.com/tensorflow/tensorflow/commit/f6fde895ef9c77d848061c0517f19d0ec2682f3a). The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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 Ying Wang and Yakun Zhang of Baidu X-Team.

CVE-2021-29607 Affected Tensorflow cpu Versions

12 component(s)

Fixed Versions:

2.3.32.1.42.2.32.4.2

Product / Package	Ecosystem	Affected Versions	Fixed Version
tensorflow-cpu pypi/tensorflow-cpu	PyPI	≥ 2.3.0 < 2.3.3	2.3.3
tensorflow pypi/tensorflow	PyPI	< 2.1.4	2.1.4
tensorflow pypi/tensorflow	PyPI	≥ 2.2.0 < 2.2.3	2.2.3
tensorflow pypi/tensorflow	PyPI	≥ 2.3.0 < 2.3.3	2.3.3
tensorflow pypi/tensorflow	PyPI	≥ 2.4.0 < 2.4.2	2.4.2
tensorflow-cpu pypi/tensorflow-cpu	PyPI	< 2.1.4	2.1.4
tensorflow-cpu pypi/tensorflow-cpu	PyPI	≥ 2.2.0 < 2.2.3	2.2.3
tensorflow-cpu pypi/tensorflow-cpu	PyPI	≥ 2.4.0 < 2.4.2	2.4.2
tensorflow-gpu pypi/tensorflow-gpu	PyPI	< 2.1.4	2.1.4
tensorflow-gpu pypi/tensorflow-gpu	PyPI	≥ 2.2.0 < 2.2.3	2.2.3
tensorflow-gpu pypi/tensorflow-gpu	PyPI	≥ 2.3.0 < 2.3.3	2.3.3
tensorflow-gpu pypi/tensorflow-gpu	PyPI	≥ 2.4.0 < 2.4.2	2.4.2

References

GitHub Advisory / Wiki ADVISORY

https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gv26-jpj9-c8gq

NVD — CVE-2021-29607 NVD

https://nvd.nist.gov/vuln/detail/CVE-2021-29607

Security Fix Commit FIX COMMIT

https://github.com/tensorflow/tensorflow/commit/ba6822bd7b7324ba201a28b2f278c29a98edbef2

Security Fix Commit FIX COMMIT

https://github.com/tensorflow/tensorflow/commit/f6fde895ef9c77d848061c0517f19d0ec2682f3a

Tensorflow cpu Source Repository REPOSITORY

https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-535.yaml

Tensorflow cpu Source Repository REPOSITORY

https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-733.yaml

Tensorflow cpu Source Repository REPOSITORY

https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-244.yaml

Frequently Asked Questions

What is CVE-2021-29607?

CVE-2021-29607 is a security vulnerability in Tensorflow cpu involving Incomplete validation in `SparseSparseMinimum` under CWE-754: Improper Check for Unusual or Exceptional Conditions.

Which Tensorflow cpu versions are affected?

Affected versions include releases prior to 2.3.3, 2.1.4, 2.2.3, 2.4.2 across affected packages: tensorflow-cpu, tensorflow, tensorflow-gpu.

What version fixes CVE-2021-29607?

Upgrading to 2.3.3, 2.1.4, 2.2.3, 2.4.2 (or the latest patched release for your respective branch) resolves the vulnerability.

Is tensorflow-cpu affected?

Yes, tensorflow-cpu is affected in releases prior to 2.3.3, 2.1.4, 2.2.3, 2.4.2. Upgrade your dependency to 2.3.3, 2.1.4, 2.2.3, 2.4.2 or later.

Is tensorflow affected?

Yes, tensorflow is affected in releases prior to 2.1.4, 2.2.3, 2.3.3, 2.4.2. Upgrade your dependency to 2.1.4, 2.2.3, 2.3.3, 2.4.2 or later.

What is the CVSS score of CVE-2021-29607?

CVE-2021-29607 has a CVSS v3.1 base score of 5.3 (MODERATE) with vector string CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:H.

What CWE is associated with CVE-2021-29607?

CVE-2021-29607 is classified under CWE-754: Improper Check for Unusual or Exceptional Conditions (The product does not check or incorrectly checks for unusual or exceptional conditions that are not expected to occur frequently during day to day operation of the product.).

How can I check PyPI dependencies for CVE-2021-29607?

Run the dependency tree command: 'pip show tensorflow-cpu'. 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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CVSS V3

5.3 MODERATE

Attack Vector Local (AV:L)

Attack Complexity High (AC:H)

Privileges Required Low (PR:L)

User Interaction None (UI:N)

Scope Unchanged (S:U)

Confidentiality None (C:N)

Integrity Low (I:L)

Availability High (A:H)

Vector String

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

Advisory Metadata

Source ID: GHSA-gv26-jpj9-c8gq
Schema Version: 1.4.0
Published: 2022-03-18 17:52
Last Modified: 2024-11-13 16:11
Database Record File: advisories/github-reviewed/2022/03/GHSA-gv26-jpj9-c8gq/GHSA-gv26-jpj9-c8gq.json