CVE-2021-37677: google tensorflow Improper Input Validation

Vulnerability summary

CVE-2021-37677 is a medium (CVSS 5.5) Improper Input Validation vulnerability in google tensorflow. EPSS estimates a 0.15% chance of exploitation in the next 30 days, higher than 3.5% of scored vulnerabilities.

Timeline

1. 12-08-2021
   PublishedVulnerability first disclosed.
2. 04-08-2024
   Last modifiedVulnerability information updated.

Description

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.

• CWE-20Improper Input ValidationThe product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly.
• CWE-1284Improper Validation of Specified Quantity in InputThe product receives input that is expected to specify a quantity (such as size or length), but it does not validate or incorrectly validates that the quantity has the required properties.