AVID-2026-R0737

Description

Heap buffer overflow caused by rounding (CVE-2021-29529)

Details

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a heap buffer overflow in tf.raw_ops.QuantizedResizeBilinear by manipulating input values so that float rounding results in off-by-one error in accessing image elements. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/44b7f486c0143f68b56c34e2d01e146ee445134a/tensorflow/core/kernels/quantized_resize_bilinear_op.cc#L62-L66) computes two integers (representing the upper and lower bounds for interpolation) by ceiling and flooring a floating point value. For some values of in, interpolation->upper[i] might be smaller than interpolation->lower[i]. This is an issue if interpolation->upper[i] is capped at in_size-1 as it means that interpolation->lower[i] points outside of the image. Then, in the interpolation code(https://github.com/tensorflow/tensorflow/blob/44b7f486c0143f68b56c34e2d01e146ee445134a/tensorflow/core/kernels/quantized_resize_bilinear_op.cc#L245-L264), this would result in heap buffer overflow. 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-2021-29529 describes a heap buffer overflow in TensorFlow’s quantized_resize_bilinear operation, a software vulnerability in a widely-used AI framework. TensorFlow is a core dependency in many AI software stacks (training/inference pipelines, model serving, etc.), so this issue constitutes a software supply chain risk for general-purpose AI systems. The vulnerability is actionable (local access with specific input), has CVE coverage with references, and the fix is documented, making it relevant to AI software supply chains and security of AI tooling.

References

• NVD entry
• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-jfp7-4j67-8r3q
• https://github.com/tensorflow/tensorflow/commit/f851613f8f0fb0c838d160ced13c134f778e3ce7

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