What is the CVSS score of CVE-2021-37678?

CVE-2021-37678 has a CVSS 3.1 base score of 8.8 (High). CVSS vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H. EPSS exploitation probability: 0.5%.

Is there a patch available for CVE-2021-37678?

Yes, a patch is available for CVE-2021-37678. Update the affected software to the latest version immediately.

Python CVE-2021-37678

HIGH

Deserialization of Untrusted Data (CWE-502)

2021-08-12 security-advisories@github.com

Deserialization Python RCE Tensorflow

8.8

CVSS 3.1 · NVD

Severity by source

NVD PRIMARY

8.8 HIGH

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

Primary rating from NVD · only source for this CVE.

CVSS VectorNVD

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

Attack Vector

Local

Attack Complexity

Low

Privileges Required

Low

User Interaction

None

Scope

Changed

Confidentiality

High

Integrity

High

Availability

High

Lifecycle Timeline

CVE Published

Aug 12, 2021 - 23:15 nvd

HIGH 8.8

Blast Radius

ecosystem impact

† from your stack dependencies † transitive graph · vuln.today resolves 4-path depth

64 pypi packages depend on tensorflow (62 direct, 2 indirect)
3 pypi packages depend on tensorflow-gpu (3 direct, 0 indirect)

Ecosystem-wide dependent count for version 2.3.0 and other introduced versions.

DescriptionNVD

TensorFlow is an end-to-end open source platform for machine learning. In affected versions TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format. The implementation uses yaml.unsafe_load which can perform arbitrary code execution on the input. Given that YAML format support requires a significant amount of work, we have removed it for now. We have patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012. 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.

AnalysisAI

TensorFlow is an end-to-end open source platform for machine learning. Rated high severity (CVSS 8.8), this vulnerability is low attack complexity. This Deserialization of Untrusted Data vulnerability could allow attackers to execute arbitrary code through malicious serialized objects.

Technical ContextAI

This vulnerability is classified as Deserialization of Untrusted Data (CWE-502), which allows attackers to execute arbitrary code through malicious serialized objects. TensorFlow is an end-to-end open source platform for machine learning. In affected versions TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format. The implementation uses yaml.unsafe_load which can perform arbitrary code execution on the input. Given that YAML format support requires a significant amount of work, we have removed it for now. We have patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012. 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. Affected products include: Google Tensorflow.

RemediationAI

A vendor patch is available. Apply the latest security update as soon as possible. Avoid deserializing untrusted data. Use safe serialization formats (JSON). Implement integrity checks and type allowlists.