PYSEC-2026-550: TensorFlow vulnerable to heap out-of-buffer read in the QuantizeAndDequantize operation
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.
Affected Software
Remediation
Recommended actions to resolve this vulnerability, in priority order.
- Upgrade
Upgrade
TensorFlowto a version that resolves this vulnerability.Fixed in 2.12.0 - Upgrade
Upgrade
TensorFlowto a version that resolves this vulnerability.Fixed in 2.11.1
Event History
Frequently Asked Questions
Which TensorFlow versions are affected?
TensorFlow versions prior to 2.12.0 are affected. The fix is included in 2.12.0 and was also cherry-picked for version 2.11.1.
Does exploiting this issue require authentication or user interaction?
No. The supplied CVSS vector indicates network exploitation with low attack complexity, no privileges required, and no user interaction required.
What is the potential impact of successful exploitation?
An attacker may read heap memory outside the intended buffer, which can lead to a crash or remote code execution. Confidentiality, integrity, and availability impacts are all rated high in the supplied CVSS vector.