CVE-2022-21726 Out of bounds read in Tensorflow
Attackers can trigger out-of-bounds reads in TensorFlow's Dequantize operation via invalid axis values, potentially leaking memory or causing crashes.
- Exploited in the wild
- Not known
- Login needed
- Any signed-in user
- Attackable
- Over the internet
- Victim action needed
- Not needed
- Fix
- Available
What is CVE-2022-21726?
CVE-2022-21726 is a high-severity memory corruption vulnerability in Google Tensorflow, published on 3 Feb 2022. Any signed-in user can exploit it over the network, with no action from the victim.
Official description
Tensorflow is an Open Source Machine Learning Framework. The implementation of `Dequantize` does not fully validate the value of `axis` and can result in heap OOB accesses. The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked and this results in reading past the end of the array containing the dimensions of the input tensor. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Weakness: CWE-125
Which versions are affected by CVE-2022-21726?
22 open source packages ship an affected version, including tensorflow, tensorflow-cpu and tensorflow-gpu. It affects 1 product.
| Package | Affected | Fixed in |
|---|---|---|
tensorflow Bitnami | All versions | 2.5.3, 2.6.3, 2.7.1 |
tensorflow PyPI | All versions | 2.5.3, 2.6.3, 2.7.1 |
tensorflow PyPI | All versions | 2.5.3 |
tensorflow PyPI | All versions | 2.5.3 |
tensorflow PyPI | From 2.6.0 | 2.6.3 |
tensorflow PyPI | From 2.6.0 | 2.6.3 |
16 more packages
tensorflow PyPI | From 2.7.0 | 2.7.1 |
tensorflow PyPI | From 2.7.0 | 2.7.1 |
tensorflow-cpu PyPI | All versions | 2.5.3, 2.6.3 |
tensorflow-cpu PyPI | All versions | 2.5.3 |
tensorflow-cpu PyPI | All versions | 2.5.3 |
tensorflow-cpu PyPI | From 2.6.0 | 2.6.3 |
tensorflow-cpu PyPI | From 2.6.0 | 2.6.3 |
tensorflow-cpu PyPI | From 2.7.0 | 2.7.1 |
tensorflow-cpu PyPI | From 2.7.0 | 2.7.1 |
tensorflow-gpu PyPI | All versions | 2.5.3, 2.6.3 |
tensorflow-gpu PyPI | All versions | 2.5.3 |
tensorflow-gpu PyPI | All versions | 2.5.3 |
tensorflow-gpu PyPI | From 2.6.0 | 2.6.3 |
tensorflow-gpu PyPI | From 2.6.0 | 2.6.3 |
tensorflow-gpu PyPI | From 2.7.0 | 2.7.1 |
tensorflow-gpu PyPI | From 2.7.0 | 2.7.1 |
Products include Google Tensorflow.
How do I fix CVE-2022-21726?
Upgrade tensorflow to a fixed version for your release line: 2.5.3, 2.6.3 or 2.7.1.
Upgrade to the fixed version. Memory-safe languages, compiler hardening and fuzzing prevent most new cases. More about Memory corruption.
Is CVE-2022-21726 being exploited?
It is not confirmed as exploited in the wild, but public exploit code for CVE-2022-21726 exists.
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-2022-21726, GHSA-23hm-7w47-xw72, PYSEC-2022-105, PYSEC-2022-50, PYSEC-2026-3082.