AVID-2026-R0732

Description

Heap buffer overflow in Conv3DBackprop* (CVE-2021-29520)

Details

TensorFlow is an end-to-end open source platform for machine learning. Missing validation between arguments to tf.raw_ops.Conv3DBackprop* operations can result in heap buffer overflows. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/4814fafb0ca6b5ab58a09411523b2193fed23fed/tensorflow/core/kernels/conv_grad_shape_utils.cc#L94-L153) assumes that the input, filter_sizes and out_backprop tensors have the same shape, as they are accessed in parallel. 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.

Reason for inclusion in AVID: CVE-2021-29520 describes a heap buffer overflow in TensorFlow’s Conv3DBackprop operations. This is a software vulnerability within a major AI framework used to build and run ML models, impacting AI software stacks (training/inference) and their supply chains. The report provides the CVE, affected versions, impact detail, and fixes, indicating clear security risk in software components used in general-purpose AI systems.

References

Affected or Relevant Artifacts

Developer: tensorflow
Deployer: tensorflow
Artifact Details:

Type	Name
System	tensorflow

Impact

AVID Taxonomy Categorization

Risk domains: Security
SEP subcategories: S0100: Software Vulnerability
Lifecycle stages: L06: Deployment

CVSS

Version	3.1
Vector String	CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
Base Score	2.5
Base Severity	🟢 Low
Attack Vector	LOCAL
Attack Complexity	🔴 High
Privileges Required	🟢 Low
User Interaction	NONE
Scope	UNCHANGED
Confidentiality Impact	NONE
Integrity Impact	NONE
Availability Impact	🟢 Low

CWE

ID	Description
CWE-120	CWE-120: Buffer Copy without Checking Size of Input (‘Classic Buffer Overflow’)

Other information

Report Type: Advisory
Credits:
Date Reported: 2021-05-14
Version: 0.3.3
AVID Entry