During execution, EinsumHelper::ParseEquation()
is supposed to set the flags in input_has_ellipsis
vector and *output_has_ellipsis
boolean to indicate whether there is ellipsis in the corresponding inputs and output.
However, the code only changes these flags to true
and never assigns false
.
for (int i = 0; i < num_inputs; ++i) {
input_label_counts->at(i).resize(num_labels);
for (const int label : input_labels->at(i)) {
if (label != kEllipsisLabel)
input_label_counts->at(i)[label] += 1;
else
input_has_ellipsis->at(i) = true;
}
}
output_label_counts->resize(num_labels);
for (const int label : *output_labels) {
if (label != kEllipsisLabel)
output_label_counts->at(label) += 1;
else
*output_has_ellipsis = true;
}
This results in unitialized variable access if callers assume that EinsumHelper::ParseEquation()
always sets these flags.
We have patched the issue in GitHub commit f09caa532b6e1ac8d2aa61b7832c78c5b79300c6.
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
{ "nvd_published_at": "2021-11-05T20:15:00Z", "cwe_ids": [ "CWE-824" ], "severity": "HIGH", "github_reviewed": true, "github_reviewed_at": "2021-11-08T22:49:15Z" }