Skip to content
LLMMedium

CVE-2021-37677: TensorFlow is an end-to-end open source platform for machine learning. In affected versions the shap…

Occurred
Aug 12, 2021
Published
Aug 12, 2021
Source
NVD CVE

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.

Tags

  • CVE
  • CVE-2021-37677
  • cvss:MEDIUM

Classification

Category confidence: 85%
Severity confidence: 90%

Rationale: TensorFlow vulnerability affects ML platform causing denial of service, fits LLM category as it is a core ML framework.

Classifier: Qwen/Qwen3.5-35B-A3B-FP8

Visit source