  As today's organizational computer networks are ever evolving and becoming
more and more complex, finding potential vulnerabilities and conducting
security audits has become a crucial element in securing these networks. The
first step in auditing a network is reconnaissance by mapping it to get a
comprehensive overview over its structure. The growing complexity, however,
makes this task increasingly effortful, even more as mapping (instead of plain
scanning), presently, still involves a lot of manual work. Therefore, the
concept proposed in this paper automates the scanning and mapping of unknown
and non-cooperative computer networks in order to find security weaknesses or
verify access controls. It further helps to conduct audits by allowing
comparing documented with actual networks and finding unauthorized network
devices, as well as evaluating access control methods by conducting delta
scans. It uses a novel approach of augmenting data from iteratively chained
existing scanning tools with context, using genuine analytics modules to allow
assessing a network's topology instead of just generating a list of scanned
devices. It further contains a visualization model that provides a clear, lucid
topology map and a special graph for comparative analysis. The goal is to
provide maximum insight with a minimum of a priori knowledge.
