What is the CVSS score of CVE-2022-29210?

CVE-2022-29210 has a CVSS 3.1 base score of 5.5 (Medium). CVSS vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H. EPSS exploitation probability: 0.2%.

Is there a patch available for CVE-2022-29210?

Yes, a patch is available for CVE-2022-29210. Update the affected software to the latest version immediately.

Tensorflow CVE-2022-29210

MEDIUM

Classic Buffer Overflow (CWE-120)

2022-05-21 security-advisories@github.com

Buffer Overflow Tensorflow

5.5

CVSS 3.1 · NVD

Severity by source

NVD PRIMARY

5.5 MEDIUM

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

Attack Vector

Local

Attack Complexity

Low

Privileges Required

Low

User Interaction

None

Scope

Unchanged

Confidentiality

None

Integrity

None

Availability

High

Lifecycle Timeline

CVE Published

May 21, 2022 - 00:15 nvd

MEDIUM 5.5

Blast Radius

ecosystem impact

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

60 pypi packages depend on tensorflow (55 direct, 5 indirect)
5 pypi packages depend on tensorflow-gpu (5 direct, 0 indirect)

Ecosystem-wide dependent count for version 2.8.0 and other introduced versions.

DescriptionNVD

TensorFlow is an open source platform for machine learning. In version 2.8.0, the TensorKey hash function used total estimated AllocatedBytes(), which (a) is an estimate per tensor, and (b) is a very poor hash function for constants (e.g. int32_t). It also tried to access individual tensor bytes through tensor.data() of size AllocatedBytes(). This led to ASAN failures because the AllocatedBytes() is an estimate of total bytes allocated by a tensor, including any pointed-to constructs (e.g. strings), and does not refer to contiguous bytes in the .data() buffer. The discoverers could not use this byte vector anyway because types such as tstring include pointers, whereas they needed to hash the string values themselves. This issue is patched in Tensorflow versions 2.9.0 and 2.8.1.

AnalysisAI

TensorFlow is an open source platform for machine learning. Rated medium severity (CVSS 5.5), this vulnerability is low attack complexity. This Buffer Copy without Size Check vulnerability could allow attackers to overflow a buffer to corrupt adjacent memory.

Technical ContextAI

This vulnerability is classified as Buffer Copy without Size Check (CWE-120), which allows attackers to overflow a buffer to corrupt adjacent memory. TensorFlow is an open source platform for machine learning. In version 2.8.0, the TensorKey hash function used total estimated AllocatedBytes(), which (a) is an estimate per tensor, and (b) is a very poor hash function for constants (e.g. int32_t). It also tried to access individual tensor bytes through tensor.data() of size AllocatedBytes(). This led to ASAN failures because the AllocatedBytes() is an estimate of total bytes allocated by a tensor, including any pointed-to constructs (e.g. strings), and does not refer to contiguous bytes in the .data() buffer. The discoverers could not use this byte vector anyway because types such as tstring include pointers, whereas they needed to hash the string values themselves. This issue is patched in Tensorflow versions 2.9.0 and 2.8.1. Affected products include: Google Tensorflow. Version information: version 2.8.0.

RemediationAI

A vendor patch is available. Apply the latest security update as soon as possible. Always validate buffer sizes before copy operations. Use bounded functions (strncpy, snprintf). Enable compiler protections.