CVE-2021-37645 Integer overflow due to conversion to unsigned in TensorFlow
An integer overflow in TensorFlow's QuantizeAndDequantizeV4Grad operation allows attackers to cause a denial of service via memory allocation errors.
- Exploited in the wild
- Not known
- Login needed
- Any signed-in user
- Attackable
- Local or same network only
- Victim action needed
- Not needed
- Fix
- Available
What is CVE-2021-37645?
CVE-2021-37645 is a medium-severity vulnerability in Google Tensorflow, published on 12 Aug 2021. It can only be exploited from the same machine or local network, with no action from the victim.
Official description
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.
Weakness: CWE-681
Which versions are affected by CVE-2021-37645?
16 open source packages ship an affected version, including tensorflow, tensorflow-cpu and tensorflow-gpu. It affects 1 product.
| Package | Affected | Fixed in |
|---|---|---|
tensorflow Bitnami | From 2.3.0 | 2.3.4, 2.4.3, 2.5.1 |
tensorflow PyPI | All versions | 2.4.3 |
tensorflow PyPI | All versions | 2.4.3 |
tensorflow PyPI | From 2.3.0 | 2.3.4, 2.4.3 |
tensorflow PyPI | From 2.5.0 | 2.5.1 |
tensorflow PyPI | From 2.5.0 | 2.5.1 |
10 more packages
tensorflow-cpu PyPI | All versions | 2.4.3 |
tensorflow-cpu PyPI | All versions | 2.4.3 |
tensorflow-cpu PyPI | From 2.3.0 | 2.3.4, 2.4.3 |
tensorflow-cpu PyPI | From 2.5.0 | 2.5.1 |
tensorflow-cpu PyPI | From 2.5.0 | 2.5.1 |
tensorflow-gpu PyPI | All versions | 2.4.3 |
tensorflow-gpu PyPI | All versions | 2.4.3 |
tensorflow-gpu PyPI | From 2.3.0 | 2.3.4, 2.4.3 |
tensorflow-gpu PyPI | From 2.5.0 | 2.5.1 |
tensorflow-gpu PyPI | From 2.5.0 | 2.5.1 |
Products include Google Tensorflow.
How do I fix CVE-2021-37645?
Upgrade tensorflow to a fixed version for your release line: 2.3.4, 2.4.3 or 2.5.1.
Is CVE-2021-37645 being exploited?
There is no known exploitation of CVE-2021-37645 in the wild and no public exploit code.
Other vulnerabilities in Google Tensorflow
- CVE-2023-25668 TensorFlow vulnerable to heap out-of-buffer read in the QuantizeAndDequantize operation
- CVE-2018-7575 Integer Overflow or Wraparound in Google TensorFlow
- CVE-2021-37678 Arbitrary code execution due to YAML deserialization
- CVE-2021-35958 Path traversal in n/a
- CVE-2020-15202 Integer truncation in Shard API usage
Sources
Also known as BIT-tensorflow-2021-37645, GHSA-9w2p-5mgw-p94c, PYSEC-2021-267, PYSEC-2021-558, PYSEC-2021-756.