  The growing need for reliable communication over untrusted networks has
caused a renewed interest in adversarial channel models, which often behave
much differently than traditional stochastic channel models. Of particular
practical use is the assumption of a \textit{causal} or \textit{online}
adversary who is limited to causal knowledge of the transmitted codeword. In
this work, we consider stochastic-adversarial mixed noise models. In the set-up
considered, a transmit node (Alice) attempts to communicate with a receive node
(Bob) over a binary erasure channel (BEC) or binary symmetric channel (BSC) in
the presence of an online adversary (Calvin) who can erase or flip up to a
certain number of bits at the input of the channel. Calvin knows the encoding
scheme and has causal access to Bob's reception through \textit{feedback
snooping}. For erasures, we provide a complete capacity characterization with
and without transmitter feedback. For bit-flips, we provide interesting
converse and achievability bounds.
