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.
References
Link | Resource |
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https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4fg4-p75j-w5xj | Exploit Patch Third Party Advisory |
https://github.com/tensorflow/tensorflow/commit/d6ed5bcfe1dcab9e85a4d39931bd18d99018e75b | Patch Third Party Advisory |
Configurations
Configuration 1 (hide)
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Information
Published : 2021-05-14 13:15
Updated : 2021-07-27 10:25
NVD link : CVE-2021-29547
Mitre link : CVE-2021-29547
JSON object : View
CWE
CWE-125
Out-of-bounds Read
Products Affected
- tensorflow