What is the CVSS score of CVE-2021-37657?

CVE-2021-37657 has a CVSS 3.1 base score of 7.8 (High). CVSS vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H. EPSS exploitation probability: 0.2%.

Is there a patch available for CVE-2021-37657?

Yes, a patch is available for CVE-2021-37657. Update the affected software to the latest version immediately.

Tensorflow CVE-2021-37657

HIGH

Access of Uninitialized Pointer (CWE-824)

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

Denial Of Service Memory Corruption Tensorflow

7.8

CVSS 3.1 · NVD

Severity by source

NVD PRIMARY

7.8 HIGH

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

Attack Vector

Local

Attack Complexity

Low

Privileges Required

Low

User Interaction

None

Scope

Unchanged

Confidentiality

High

Integrity

High

Availability

High

Lifecycle Timeline

CVE Published

Aug 12, 2021 - 21:15 nvd

HIGH 7.8

Blast Radius

ecosystem impact

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

50 pypi packages depend on tensorflow (48 direct, 2 indirect)
3 pypi packages depend on tensorflow-gpu (3 direct, 0 indirect)

Ecosystem-wide dependent count for version 2.4.0 and other introduced versions.

DescriptionNVD

TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type tf.raw_ops.MatrixDiagV*. The implementation has incomplete validation that the value of k is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09. 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 7.8), this vulnerability is low attack complexity.

Technical ContextAI

This vulnerability is classified under CWE-824. TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type tf.raw_ops.MatrixDiagV*. The implementation has incomplete validation that the value of k is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09. 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. Apply vendor patches when available. Implement network segmentation and monitoring as interim mitigations.