CVE-2021-29547
Published May 14, 2021
Last updated 3 years ago
Overview
- Description
- 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.
- Source
- security-advisories@github.com
- NVD status
- Analyzed
Risk scores
CVSS 3.1
- Type
- Primary
- Base score
- 5.5
- Impact score
- 3.6
- Exploitability score
- 1.8
- Vector string
- CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
- Severity
- MEDIUM
CVSS 2.0
- Type
- Primary
- Base score
- 2.1
- Impact score
- 2.9
- Exploitability score
- 3.9
- Vector string
- AV:L/AC:L/Au:N/C:N/I:N/A:P
Weaknesses
- security-advisories@github.com
- CWE-125
Social media
- Hype score
- Not currently trending
Configurations
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