CVE-2021-37677 (GCVE-0-2021-37677)

Vulnerability from cvelistv5 – Published: 2021-08-12 22:35 – Updated: 2024-08-04 01:23
VLAI
Title
Missing validation in shape inference for `Dequantize` in TensorFlow
Summary
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) uses `axis` to select between two different values for `minmax_rank` which is then used to retrieve tensor dimensions. However, code assumes that `axis` can be either `-1` or a value greater than `-1`, with no validation for the other values. We have patched the issue in GitHub commit da857cfa0fde8f79ad0afdbc94e88b5d4bbec764. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Severity
5.5 (Medium)
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
CWE
  • CWE-20 - Improper Input Validation
Assigner
GitHub_M CNA under the mitre root
CNA scorecard C 72/100 over 7752 records in the last 180 days details
References
Impacted products
Vendor Product Version CPE status
tensorflow tensorflow Affected: >= 2.5.0, < 2.5.1
Affected: >= 2.4.0, < 2.4.3
Affected: < 2.3.4
guessed Create a notification for this product.
Show details on NVD website
To clipboard 

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