PyPi: Tensorflow

CVE-2021-37650

Safety vulnerability ID: 41125

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-2021-37650: In affected versions the implementation for `tf.raw_ops.ExperimentalDatasetToTFRecord` and `tf.raw_ops.DatasetToTFRecord` can trigger heap buffer overflow and segmentation fault. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/data/experimental/to_tf_record_op.cc#L93-L102) assumes that all records in the dataset are of string type. However, there is no check for that, and the example given above uses numeric types. The Tensorflow team has patched the issue in GitHub commit e0b6e58c328059829c3eb968136f17aa72b6c876.

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 the implementation for `tf.raw_ops.ExperimentalDatasetToTFRecord` and `tf.raw_ops.DatasetToTFRecord` can trigger heap buffer overflow and segmentation fault. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/data/experimental/to_tf_record_op.cc#L93-L102) assumes that all records in the dataset are of string type. However, there is no check for that, and the example given above uses numeric types. We have patched the issue in GitHub commit e0b6e58c328059829c3eb968136f17aa72b6c876. 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-2021-37650.


CONFIRM:https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f8h4-7rgh-q2gm: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f8h4-7rgh-q2gm
MISC:https://github.com/tensorflow/tensorflow/commit/e0b6e58c328059829c3eb968136f17aa72b6c876: https://github.com/tensorflow/tensorflow/commit/e0b6e58c328059829c3eb968136f17aa72b6c876

Resources

Use this package?

Scan your Python project for dependency vulnerabilities in two minutes

Scan your application

Severity Details

CVSS Base Score

HIGH 7.8

CVSS v3 Details

HIGH 7.8
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)
HIGH
Availability Availability (A)
HIGH

CVSS v2 Details

MEDIUM 4.6
Access Vector (AV)
LOCAL
Access Complexity (AC)
LOW
Authentication (Au)
NONE
Confidentiality Impact (C)
PARTIAL
Integrity Impact (I)
PARTIAL
Availability Impact (A)
PARTIAL