Vulnerability Monitor

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CVE-2021-37645

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.QuantizeAndDequantizeV4Grad` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L126) uses the `axis` value as the size argument to `absl::InlinedVector` constructor. But, the constructor uses an unsigned type for the argument, so the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit 96f364a1ca3009f98980021c4b32be5fdcca33a1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, and TensorFlow 2.4.3, as these are also affected and still in supported range.

Published

2021-08-12T21:15:07.887

Last Modified

2024-11-21T06:15:35.897

Status

Modified

Source

[email protected]

Severity

CVSSv3.1: 5.5 (MEDIUM)

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-681
Affected Vendors & Products
Type Vendor Product Version/Range Vulnerable?
Application google tensorflow < 2.3.4 Yes
Application google tensorflow < 2.4.3 Yes
Application google tensorflow 2.5.0 Yes
Application google tensorflow 2.6.0 Yes
Application google tensorflow 2.6.0 Yes
Application google tensorflow 2.6.0 Yes
References