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CVE-2021-29549: TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runti…

Occurred
May 14, 2021
Published
May 14, 2021
Source
NVD CVE

Summary

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L289-L295) computes a modulo operation without validating that the divisor is not zero. Since `vector_num_elements` is determined based on input shapes(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L522-L544), a user can trigger scenarios where this quantity is 0. 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.

Tags

  • CVE
  • CVE-2021-29549
  • cvss:LOW

Classification

Category confidence: 85%
Severity confidence: 90%

Rationale: TensorFlow vulnerability affects ML platform causing denial of service, fits LLM category as ML framework issue.

Classifier: Qwen/Qwen3.5-35B-A3B-FP8

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