CVE-2022-41895 `MirrorPadGrad` heap out of bounds read in Tensorflow
An attacker can trigger a heap out-of-bounds read in TensorFlow's MirrorPadGrad operation via oversized padding inputs, potentially causing crashes or information disclosure.
- Exploited in the wild
- Not known
- Login needed
- Any signed-in user
- Attackable
- Over the internet
- Victim action needed
- A user has to click or open something
- Fix
- Available
What is CVE-2022-41895?
CVE-2022-41895 is a medium-severity memory corruption vulnerability in Google Tensorflow, published on 18 Nov 2022. Any signed-in user can exploit it over the network, and only if a user opens a file or follows a link.
Official description
TensorFlow is an open source platform for machine learning. If `MirrorPadGrad` is given outsize input `paddings`, TensorFlow will give a heap OOB error. We have patched the issue in GitHub commit 717ca98d8c3bba348ff62281fdf38dcb5ea1ec92. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
Weakness: CWE-125
Which versions are affected by CVE-2022-41895?
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 | 2.8.4, 2.9.3, 2.10.1 |
tensorflow PyPI | All versions | 2.8.4, 2.9.3, 2.10.1 |
tensorflow PyPI | All versions | 2.8.4 |
tensorflow PyPI | All versions | 2.8.4 |
tensorflow PyPI | From 2.10.0 | 2.10.1 |
tensorflow PyPI | From 2.10.0 | 2.10.1 |
16 more packages
tensorflow PyPI | From 2.9.0 | 2.9.3 |
tensorflow PyPI | From 2.9.0 | 2.9.3 |
tensorflow-cpu PyPI | All versions | 2.8.4, 2.9.3, 2.10.1 |
tensorflow-cpu PyPI | All versions | 2.8.4 |
tensorflow-cpu PyPI | All versions | 2.8.4 |
tensorflow-cpu PyPI | From 2.10.0 | 2.10.1 |
tensorflow-cpu PyPI | From 2.10.0 | 2.10.1 |
tensorflow-cpu PyPI | From 2.9.0 | 2.9.3 |
tensorflow-cpu PyPI | From 2.9.0 | 2.9.3 |
tensorflow-gpu PyPI | All versions | 2.8.4, 2.9.3, 2.10.1 |
tensorflow-gpu PyPI | All versions | 2.8.4 |
tensorflow-gpu PyPI | All versions | 2.8.4 |
tensorflow-gpu PyPI | From 2.10.0 | 2.10.1 |
tensorflow-gpu PyPI | From 2.10.0 | 2.10.1 |
tensorflow-gpu PyPI | From 2.9.0 | 2.9.3 |
tensorflow-gpu PyPI | From 2.9.0 | 2.9.3 |
Products include Google Tensorflow.
How do I fix CVE-2022-41895?
Upgrade tensorflow to a fixed version for your release line: 2.8.4, 2.9.3 or 2.10.1.
Upgrade to the fixed version. Memory-safe languages, compiler hardening and fuzzing prevent most new cases. More about Memory corruption.
Is CVE-2022-41895 being exploited?
It is not confirmed as exploited in the wild, but public exploit code for CVE-2022-41895 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 AZL-11533, BIT-tensorflow-2022-41895, GHSA-gq2j-cr96-gvqx, PYSEC-2026-1000, PYSEC-2026-3192, PYSEC-2026-3332.