PyPi: Tensorflow-Rocm

CVE-2021-37650

Safety vulnerability ID: 57787

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 Nov 29, 2024
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Advisory

Tensorflow-rocm 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-rocm

Latest version: 2.14.0.600

TensorFlow is an open source machine learning framework for everyone.

Affected versions

Fixed versions

Vulnerability changelog

This vulnerability has no description

Resources

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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