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CVE-2021-29547
Good to know:
Date: May 14, 2021
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.
Language: Python
Severity Score
Severity Score
Weakness Type (CWE)
Out-of-bounds Read
CWE-125Top Fix
CVSS v3.1
Base Score: |
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---|---|
Attack Vector (AV): | LOCAL |
Attack Complexity (AC): | LOW |
Privileges Required (PR): | LOW |
User Interaction (UI): | NONE |
Scope (S): | UNCHANGED |
Confidentiality (C): | NONE |
Integrity (I): | NONE |
Availability (A): | HIGH |
CVSS v2
Base Score: |
|
---|---|
Access Vector (AV): | LOCAL |
Access Complexity (AC): | LOW |
Authentication (AU): | NONE |
Confidentiality (C): | NONE |
Integrity (I): | NONE |
Availability (A): | PARTIAL |
Additional information: |