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 2021-08-12 21:15:08
Updated 2021-08-18 15:38:53
Source GitHub, Inc.
View at NVD,   CVE.org
Vulnerability category: Overflow

Exploit prediction scoring system (EPSS) score for CVE-2021-37645

Probability of exploitation activity in the next 30 days: 0.04%

Percentile, the proportion of vulnerabilities that are scored at or less: ~ 10 % EPSS Score History EPSS FAQ

CVSS scores for CVE-2021-37645

Base Score Base Severity CVSS Vector Exploitability Score Impact Score Score Source
2.1
LOW AV:L/AC:L/Au:N/C:N/I:N/A:P
3.9
2.9
NIST
5.5
MEDIUM CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
1.8
3.6
NIST
5.5
MEDIUM CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
1.8
3.6
GitHub, Inc.

CWE ids for CVE-2021-37645

  • When converting from one data type to another, such as long to integer, data can be omitted or translated in a way that produces unexpected values. If the resulting values are used in a sensitive context, then dangerous behaviors may occur.
    Assigned by: security-advisories@github.com (Primary)

References for CVE-2021-37645

Products affected by CVE-2021-37645

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