CVE-2023-25659 TensorFlow vulnerable to Out-of-Bounds Read in DynamicStitch
Attackers can trigger an out-of-bounds read in TensorFlow's DynamicStitch operation by providing mismatched indices and data shapes, potentially causing crashes or leaking memory.
- Exploited in the wild
- Not known
- Login needed
- Not needed
- Attackable
- Over the internet
- Victim action needed
- Not needed
- Fix
- Available
What is CVE-2023-25659?
CVE-2023-25659 is a high-severity memory corruption vulnerability in Google Tensorflow, published on 24 Mar 2023. An attacker can exploit it over the internet without logging in, with no action from the victim.
Official description
TensorFlow is an open source platform for machine learning. Prior to versions 2.12.0 and 2.11.1, if the parameter `indices` for `DynamicStitch` does not match the shape of the parameter `data`, it can trigger an stack OOB read. A fix is included in TensorFlow version 2.12.0 and version 2.11.1.
Weakness: CWE-125
Which versions are affected by CVE-2023-25659?
10 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 | 2.12.0 |
tensorflow PyPI | All versions | 2.11.1 |
tensorflow PyPI | All versions | 2.11.1 |
tensorflow PyPI | All versions | 2.11.1 |
tensorflow-cpu PyPI | All versions | 2.11.1 |
tensorflow-cpu PyPI | All versions | 2.11.1 |
4 more packages
tensorflow-cpu PyPI | All versions | 2.11.1 |
tensorflow-gpu PyPI | All versions | 2.11.1 |
tensorflow-gpu PyPI | All versions | 2.11.1 |
tensorflow-gpu PyPI | All versions | 2.11.1 |
Products include Google Tensorflow.
How do I fix CVE-2023-25659?
Upgrade tensorflow to a fixed version for your release line: 2.12.0 or 2.11.1.
Upgrade to the fixed version. Memory-safe languages, compiler hardening and fuzzing prevent most new cases. More about Memory corruption.
Is CVE-2023-25659 being exploited?
There is no known exploitation of CVE-2023-25659 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 AZL-31201, AZL-35305, BIT-tensorflow-2023-25659, GHSA-93vr-9q9m-pj8p, PYSEC-2026-1959, PYSEC-2026-3142 and 1 more.