CVE-2023-25668 TensorFlow vulnerable to heap out-of-buffer read in the QuantizeAndDequantize operation

What is CVE-2023-25668?

CVE-2023-25668 is a critical 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. Attackers using Tensorflow prior to 2.12.0 or 2.11.1 can access heap memory which is not in the control of user, leading to a crash or remote code execution. The fix will be included in TensorFlow version 2.12.0 and will also cherrypick this commit on TensorFlow version 2.11.1.

Weakness: CWE-125, CWE-122

Which versions are affected by CVE-2023-25668?

10 open source packages ship an affected version, including tensorflow, tensorflow-cpu and tensorflow-gpu. It affects 1 product.

Products include Google Tensorflow.

How do I fix CVE-2023-25668?

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-2023-25668 being exploited?

There is no known exploitation of CVE-2023-25668 in the wild and no public exploit code.

Other vulnerabilities in Google Tensorflow

• CVE-2018-7575 Integer Overflow or Wraparound in Google TensorFlow Critical 9.8
• CVE-2021-37678 Arbitrary code execution due to YAML deserialization Critical 9.3
• CVE-2021-35958 Path traversal in n/a Critical 9.1
• CVE-2020-15202 Integer truncation in Shard API usage Critical 9.0
• CVE-2020-15205 Data leak in Tensorflow Critical 9.0

All Google Tensorflow vulnerabilities

Sources

• CVE record
• NVD
• OSV
• GitHub advisory
• How this page is made

Also known as AZL-31200, AZL-35313, BIT-tensorflow-2023-25668, GHSA-gw97-ff7c-9v96, PYSEC-2026-548, PYSEC-2026-549 and 1 more.