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Update SECURITY.md 

simple error correction
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seo-inyoung 2020-05-15 20:05:11 +09:00 committed by GitHub
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@ -64,7 +64,7 @@ your model, and we recommend you run the TensorFlow process in a sandbox.
It is possible to write models that are secure in a sense that they can safely It is possible to write models that are secure in a sense that they can safely
process untrusted inputs assuming there are no bugs. There are two main reasons process untrusted inputs assuming there are no bugs. There are two main reasons
to not rely on this: first, it is easy to write models which must not be exposed to not rely on this: First, it is easy to write models which must not be exposed
to untrusted inputs, and second, there are bugs in any software system of to untrusted inputs, and second, there are bugs in any software system of
sufficient complexity. Letting users control inputs could allow them to trigger sufficient complexity. Letting users control inputs could allow them to trigger
bugs either in TensorFlow or in dependent libraries. bugs either in TensorFlow or in dependent libraries.
@ -149,7 +149,7 @@ attack (or worse). Because TensorFlow behaves correctly, this is not a
vulnerability in TensorFlow (although it would be a vulnerability of this vulnerability in TensorFlow (although it would be a vulnerability of this
hypothetical system). hypothetical system).
As a general rule, it is incorrect behavior for Tensorflow to access memory it As a general rule, it is incorrect behavior for TensorFlow to access memory it
does not own, or to terminate in an unclean way. Bugs in TensorFlow that lead to does not own, or to terminate in an unclean way. Bugs in TensorFlow that lead to
such behaviors constitute a vulnerability. such behaviors constitute a vulnerability.