PYSEC-2026-3224: Missing validation in `QuantizedConv2D` results in undefined behavior in TensorFlow
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of tf.rawops.QuantizedConv2D does not fully validate the input arguments. In this case, references get bound to nullptr for each argument that is empty. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
Affected Software
Remediation
Recommended actions to resolve this vulnerability, in priority order.
- Upgrade
Upgrade
TensorFlowto a version that resolves this vulnerability.Fixed in 2.9.0 - Upgrade
Upgrade
TensorFlowto a version that resolves this vulnerability.Fixed in 2.8.1 - Upgrade
Upgrade
TensorFlowto a version that resolves this vulnerability.Fixed in 2.7.2 - Upgrade
Upgrade
TensorFlowto a version that resolves this vulnerability.Fixed in 2.6.4
Event History
Frequently Asked Questions
What input is needed to trigger the issue?
An attacker or local user needs to invoke tf.raw_ops.QuantizedConv2D with one or more empty arguments. The affected implementation can bind references for empty arguments to nullptr, leading to undefined behavior.
Which TensorFlow releases contain the fix?
The issue is patched in TensorFlow 2.9.0, 2.8.1, 2.7.2, and 2.6.4. Versions earlier than those releases are affected.
What is the likely security impact?
The provided CVSS vector indicates local access and low privileges are required, with no user interaction. The stated impact is availability only, consistent with a null pointer dereference causing a denial of service.