Lines Matching refs:untrusted

3 This document discusses how to safely deal with untrusted programs (models or
33 ## Running untrusted models
35 As a general rule: **Always** execute untrusted models inside a sandbox (e.g.,
38 There are several ways in which a model could become untrusted. Obviously, if an
39 untrusted party supplies TensorFlow kernels, arbitrary code may be executed.
40 The same is true if the untrusted party provides Python code, such as the
43 Even if the untrusted party only supplies the serialized computation
63 ## Accepting untrusted Inputs
66 process untrusted inputs assuming there are no bugs. There are two main reasons
68 to untrusted inputs, and second, there are bugs in any software system of
73 to untrusted (e.g., user-provided) inputs in a sandbox.
88 internal communication only. It is not built for use in an untrusted network.**
107 Connecting it to an untrusted network allows anyone on this network to run the
109 graphs using untrusted inputs as described above, but they would not be able to
111 directly to an untrusted network, **but only if the graphs it is configured to
117 authenticating requests to any TensorFlow server connected to an untrusted