CVE-2021-29580 - CVE House
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Status published Low CVE-2021-29580

Undefined behavior and `CHECK`-fail in `FractionalMaxPoolGrad`

Vulnerability Description

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.FractionalMaxPoolGrad` triggers an undefined behavior if one of the input tensors is empty. The code is also vulnerable to a denial of service attack as a `CHECK` condition becomes false and aborts the process. The implementation(https://github.com/tensorflow/tensorflow/blob/169054888d50ce488dfde9ca55d91d6325efbd5b/tensorflow/core/kernels/fractional_max_pool_op.cc#L215) fails to validate that input and output tensors are not empty and are of the same rank. Each of these unchecked assumptions is responsible for the above issues. 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.

Impact Analysis

Refer to official advisory for detailed impact metrics.

Remediation

Ensure systems are updated to the latest vendor-supplied patch levels.

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Credits & Attribution

No credits recorded in the NVD database.

References

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Affected Vendor

Affected Software

tensorflow
Vulnerable Versions:
< 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2

Timeline

Official Publish: May 14th, 2021
Last Modified: August 3rd, 2024
Added to House: July 21st, 2026

CVSS Vectors

V3: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L

Weaknesses (CWE)

CWE-908

MITRE ATT&CK TTPs

T1203 Exploitation for Client Execution
Execution
T1068 Exploitation for Privilege Escalation
Privilege Escalation
T1499.003 Application Exhaustion Flood
Impact