AVID-2026-R0774

Description

Heap out of bounds read in RequantizationRange (CVE-2021-29569)

Details

TensorFlow is an end-to-end open source platform for machine learning. The implementation of tf.raw_ops.MaxPoolGradWithArgmax can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/ac328eaa3870491ababc147822cd04e91a790643/tensorflow/core/kernels/requantization_range_op.cc#L49-L50) assumes that the input_min and input_max tensors have at least one element, as it accesses the first element in two arrays. If the tensors are empty, .flat<T>() is an empty object, backed by an empty array. Hence, accesing even the 0th element is a read outside the bounds. 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-2021-29569 describes a heap out-of-bounds read in TensorFlow’s RequantizationRange affecting tf.raw_ops.MaxPoolGradWithArgmax. TensorFlow is an ML framework used in AI pipelines, and the vulnerability is in the software (tensorflow artifact) used to build/train/deploy AI systems. This is a security vulnerability (memory read out-of-bounds) with a CVE entry and a documented fix. Therefore, it concerns AI software components and the general-purpose AI system supply chain.

References

• NVD entry
• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3h8m-483j-7xxm
• https://github.com/tensorflow/tensorflow/commit/ef0c008ee84bad91ec6725ddc42091e19a30cf0e

Affected or Relevant Artifacts

• Developer: tensorflow
• Deployer: tensorflow
• Artifact Details:

Impact

AVID Taxonomy Categorization

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

CVSS

CWE

Other information

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