CVE-2021-41196 - CVE House

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Status published Medium CVE-2021-41196

Crash in `max_pool3d` when size argument is 0 or negative

5.5 CVSS

Vulnerability Description

TensorFlow is an open source platform for machine learning. In affected versions the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow's implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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

More from tensorflow

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Arbitrary code injection vulnerability in Keras framework < 2.13

TensorFlow segfault in array_ops.upper_bound

TensorFlow has Floating Point Exception in TFLite in conv kernel

TensorFlow has double free in Fractional(Max/Avg)Pool

TensorFlow has null dereference on ParallelConcat with XLA

Affected Vendor

tensorflow

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Affected Software

tensorflow

Vulnerable Versions:

>= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4

Timeline

Official Publish: November 5th, 2021

Last Modified: August 4th, 2024

Added to House: July 21st, 2026

CVSS Vectors

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

Weaknesses (CWE)

MITRE ATT&CK TTPs

T1190 Exploit Public-Facing Application

T1574 Hijack Execution Flow

Privilege Escalation

T1059 Command and Scripting Interpreter

T1485 Data Destruction

T1499 Endpoint Denial of Service