Vulnerability Monitor

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CVE-2021-29547

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.

Published

2021-05-14T20:15:12.763

Last Modified

2024-11-21T06:01:21.313

Status

Modified

Source

[email protected]

Severity

CVSSv3.1: 2.5 (LOW)

CVSSv2 Vector

AV:L/AC:L/Au:N/C:N/I:N/A:P

  • Access Vector: LOCAL
  • Access Complexity: LOW
  • Authentication: NONE
  • Confidentiality Impact: NONE
  • Integrity Impact: NONE
  • Availability Impact: PARTIAL
Exploitability Score

3.9

Impact Score

2.9

Weaknesses
  • Type: Primary
    CWE-125
Affected Vendors & Products
Type Vendor Product Version/Range Vulnerable?
Application google tensorflow < 2.1.4 Yes
Application google tensorflow < 2.2.3 Yes
Application google tensorflow < 2.3.3 Yes
Application google tensorflow < 2.4.2 Yes
References