# Using TensorFlow Securely

This document discusses the TensorFlow security model. It describes the security
risks to consider when using models, checkpoints or input data for training or
serving. We also provide guidelines on what constitutes a vulnerability in
TensorFlow and how to report them.

This document applies to other repositories in the TensorFlow organization,
covering security practices for the entirety of the TensorFlow ecosystem.

TensorFlow via the command `import tensorflow as tf`.

The primary function of this module is to import all of the public TensorFlow
interfaces into a single place. The interfaces themselves are located in
sub-modules, as described below.

Note that the file `__init__.py` in the TensorFlow source code tree is actually
only a placeholder to enable test cases to run. The TensorFlow build replaces

+    the special unrelocated first GOT entry.  */
+
+    extern ElfW(Dyn) _DYNAMIC[] attribute_hidden;
+    return (ElfW(Addr)) &_DYNAMIC - elf_machine_dynamic ();
 }
 
 /* Set up the loaded object described by L so its unrelocated PLT
diff --git a/sysdeps/ieee754/dbl-64/k_rem_pio2.c b/sysdeps/ieee754/dbl-64/k_rem_pio2.c
index fcf956a..e2c5d29 100644
--- a/sysdeps/ieee754/dbl-64/k_rem_pio2.c