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    tensorflow/tensorflow/blob/master/SECURITY.md


    # Using TensorFlow Securely

This document discusses how to safely deal with untrusted programs (models or
model parameters), and input data. Below, we also provide guidelines on how to
report vulnerabilities in TensorFlow.

## TensorFlow models are programs

TensorFlow's runtime system interprets and executes programs. What machine
learning practitioners term
[**models**](https://developers.google.com/machine-learning/glossary/#model) are
expressed as programs that TensorFlow executes.  TensorFlow programs are encoded
as computation
[**graphs**](https://developers.google.com/machine-learning/glossary/#graph).
The model's parameters are often stored separately in **checkpoints**.

At runtime, TensorFlow executes the computation graph using the parameters
provided. Note that the behavior of the computation graph may change
depending on the parameters provided. TensorFlow itself is not a sandbox. When
executing the computation graph, TensorFlow may read and write files, send and



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