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CVE-2021-29547: TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a segfa…

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 segfault and denial of service via accessing data outside of bounds in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/55a97caa9e99c7f37a0bbbeb414dc55553d3ae7f/tensorflow/core/kernels/quantized_batch_norm_op.cc#L176-L189) assumes the inputs are not empty. If any of these inputs is empty, `.flat<T>()` is an empty buffer, so accessing the element at index 0 is accessing data outside of 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.

Tags

  • CVE
  • CVE-2021-29547
  • cvss:LOW

Classification

Category confidence: 85%
Severity confidence: 90%

Rationale: TensorFlow vulnerability affects ML platform causing denial of service, not a direct AI safety incident.

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

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