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PYSEC-2026-994
No affected components available
Impact
When mlir::tfg::ConvertGenericFunctionToFunctionDef is given empty function attributes, it gives a null dereference.
// Import the function attributes with a `tf.` prefix to match the current
// infrastructure expectations.
for (const auto& namedAttr : func.attr()) {
const std::string& name = "tf." + namedAttr.first;
const AttrValue& tf_attr = namedAttr.second;
TF_ASSIGN_OR_RETURN(Attribute attr,
ConvertAttributeValue(tf_attr, builder, tfgDialect));
attrs.append(name, attr);
}
If namedAttr.first is empty, it will crash.
Patches
We have patched the issue in GitHub commit 1cf45b831eeb0cab8655c9c7c5d06ec6f45fc41b.
The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
The vulnerability can be exploited over the network without needing physical access. It is difficult for an attacker to exploit this vulnerability and may require special conditions. An attacker does not need any special privileges or access rights. No user interaction is needed for the attacker to exploit this vulnerability. The impact is confined to the system where the vulnerability exists. There is a high impact on the availability of the system.
Exploitation attempts have been detected. Elevated vigilance and prompt remediation are advised.
The exploit probability is very low. The vulnerability is unlikely to be exploited in the next 30 days.
We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.
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