What is the CVSS score of CVE-2021-37655?

CVE-2021-37655 has a CVSS 3.1 base score of 7.3 (High). CVSS vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:H. EPSS exploitation probability: 0.2%.

Is there a patch available for CVE-2021-37655?

Yes, a patch is available for CVE-2021-37655. Update the affected software to the latest version immediately.

Tensorflow CVE-2021-37655

HIGH

Out-of-bounds Read (CWE-125)

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

Buffer Overflow Information Disclosure Tensorflow

7.3

CVSS 3.1 · NVD

Severity by source

NVD PRIMARY

7.3 HIGH

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

Attack Vector

Local

Attack Complexity

Low

Privileges Required

Low

User Interaction

None

Scope

Unchanged

Confidentiality

High

Integrity

Low

Availability

High

Lifecycle Timeline

CVE Published

Aug 12, 2021 - 21:15 nvd

HIGH 7.3

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 trigger a read from outside of bounds of heap allocated data by sending invalid arguments to tf.raw_ops.ResourceScatterUpdate. The implementation has an incomplete validation of the relationship between the shapes of indices and updates: instead of checking that the shape of indices is a prefix of the shape of updates (so that broadcasting can happen), code only checks that the number of elements in these two tensors are in a divisibility relationship. We have patched the issue in GitHub commit 01cff3f986259d661103412a20745928c727326f. 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 7.3), this vulnerability is low attack complexity. This Out-of-bounds Read vulnerability could allow attackers to read data from memory outside the intended buffer boundaries.

Technical ContextAI

This vulnerability is classified as Out-of-bounds Read (CWE-125), which allows attackers to read data from memory outside the intended buffer boundaries. TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a read from outside of bounds of heap allocated data by sending invalid arguments to tf.raw_ops.ResourceScatterUpdate. The implementation has an incomplete validation of the relationship between the shapes of indices and updates: instead of checking that the shape of indices is a prefix of the shape of updates (so that broadcasting can happen), code only checks that the number of elements in these two tensors are in a divisibility relationship. We have patched the issue in GitHub commit 01cff3f986259d661103412a20745928c727326f. 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. Validate array indices and buffer lengths. Use memory-safe languages. Enable AddressSanitizer during testing.