Home/CVE/TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWith
CVE

CVE-2021-29573

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWith

TensorFlow is an end-to-end open source platform for machine learning. The implementation of tf.raw_ops.MaxPoolGradWithArgmax is vulnerable to a division by 0. The implementation(https://github.com/tensorflow/tensorflow/blob/279bab6efa22752a2827621b7edb56a730233bd8/tensorflow/core/kernels/maxpooling_op.cc#L1033-L1034) fails to validate that the batch dimension of the tensor is non-zero, before dividing by this quantity.

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

LOW · CVSS 2.5 EPSS 9e-05
Schedule remediation
  • Public exploit or PoC is available
Sigma rules0 YARA rules0
⬡

Weakness Classification

CWE-369Divide By Zero
CWE-369Divide By Zero
▤

Affected Products & Versions

4
google tensorflow< 2.1.4
google tensorflow>= 2.2.0 and < 2.2.3
google tensorflow>= 2.3.0 and < 2.3.3
google tensorflow>= 2.4.0 and < 2.4.2
▤

Affected Packages

3
Language-ecosystem packages (from OSV) tied to this CVE, with the version that fixes it - the dependency-level detail NVD doesn’t carry.
PyPI tensorflow LOW fixed in 2.1.4
PyPI tensorflow-cpu LOW fixed in 2.1.4
PyPI tensorflow-gpu LOW fixed in 2.1.4
⚠

Public Exploits & PoCs

1
pocgithub.com · GHSA-9vpm-rcf4-9wqwgithub.com
▣

Scoring & Timeline

2.5
LOW · CVSS v3.1 · security-advisories@github.com
View on NVD
Attack Vector
Network Adjacent Local Physical
Attack Complexity
Low High
Privileges Required
None Low High
User Interaction
None Required
Scope
Unchanged Changed
Confidentiality
None Low High
Integrity
None Low High
Availability
None Low High
Published to NVD14 May 2021 · 08:15 PM
CVSS VectorCVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
🔗

References & Sources

1
Source URLs (vendor pages, mailing lists, write-ups). Exploit/PoC links are in their own section above to avoid duplication.
https://github.com/tensorflow/tensorflow/commit/376c352a37ce5a68b721406dc7e77ac4b6cf483dPatchThird Party Advisory
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