PyPi: Tensorflow

CVE-2021-37641

Safety vulnerability ID: 41116

This vulnerability was reviewed by experts

The information on this page was manually curated by our Cybersecurity Intelligence Team.

Created at Aug 12, 2021 Updated at Oct 25, 2024
Scan your Python projects for vulnerabilities →

Advisory

TensorFlow 2.3.4, 2.4.3, 2.5.1 and 2.6.0 include a fix for CVE-2021-37641: In affected versions if the arguments to 'tf.raw_ops.RaggedGather' don't determine a valid ragged tensor code can trigger a read from outside of bounds of heap allocated buffers. The implementation (https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/ragged_gather_op.cc#L70) directly reads the first dimension of a tensor shape before checking that said tensor has rank of at least 1 (i.e., it is not a scalar). Furthermore, the implementation does not check that the list given by 'params_nested_splits' is not an empty list of tensors. The Tensorflow team has patched the issue in GitHub commit a2b743f6017d7b97af1fe49087ae15f0ac634373.

Affected package

tensorflow

Latest version: 2.18.0

TensorFlow is an open source machine learning framework for everyone.

Affected versions

Fixed versions

Vulnerability changelog

TensorFlow is an end-to-end open source platform for machine learning. In affected versions if the arguments to `tf.raw_ops.RaggedGather` don't determine a valid ragged tensor code can trigger a read from outside of bounds of heap allocated buffers. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/ragged_gather_op.cc#L70) directly reads the first dimension of a tensor shape before checking that said tensor has rank of at least 1 (i.e., it is not a scalar). Furthermore, the implementation does not check that the list given by `params_nested_splits` is not an empty list of tensors. We have patched the issue in GitHub commit a2b743f6017d7b97af1fe49087ae15f0ac634373. 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. See CVE-2021-37641.


CONFIRM:https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c8h-vvrj-w2p8: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c8h-vvrj-w2p8
MISC:https://github.com/tensorflow/tensorflow/commit/a2b743f6017d7b97af1fe49087ae15f0ac634373: https://github.com/tensorflow/tensorflow/commit/a2b743f6017d7b97af1fe49087ae15f0ac634373

Resources

Use this package?

Scan your Python project for dependency vulnerabilities in two minutes

Scan your application

Severity Details

CVSS Base Score

HIGH 7.1

CVSS v3 Details

HIGH 7.1
Attack Vector (AV)
LOCAL
Attack Complexity (AC)
LOW
Privileges Required (PR)
LOW
User Interaction (UI)
NONE
Scope (S)
UNCHANGED
Confidentiality Impact (C)
HIGH
Integrity Impact (I)
NONE
Availability Availability (A)
HIGH

CVSS v2 Details

LOW 3.6
Access Vector (AV)
LOCAL
Access Complexity (AC)
LOW
Authentication (Au)
NONE
Confidentiality Impact (C)
PARTIAL
Integrity Impact (I)
NONE
Availability Impact (A)
PARTIAL