Authors: Johannes Zirngibl, Patrick Sattler, Georg Carle

Authors: Benedikt Jaeger, Johannes Zirngibl, Marcel Kempf, Kevin Ploch, Georg Carle

Authors: Henning Stubbe, Sebastian Gallenmüller, Manuel Simon, Eric Hauser, Dominik Scholz, Georg Carle

Authors: Manuel Simon, Sebastian Gallenmüller, Georg Carle

Authors: Jonas Andre, Johannes Naab, Benedikt Jaeger, Georg Carle, Leander Seidlitz, Stephan Günther

Authors: Simon Bauer, Janluka Janelidze, Benedikt Jaeger, Patrick Sattler, Patrick Brzoza, Georg Carle

Authors: Sebastian Gallenmüller, Serge Fdida, Georg Carle

Authors: Kilian Holzinger, Henning Stubbe, Manuel Simon, Sebastian Gallenmüller, Georg Carle

Collecting metadata from Transport Layer Security (TLS) servers on a large scale allows to draw conclusions about their capabilities and configuration. This provides not only insights into the Internet but it enables use cases like detecting malicious Command and Control (C &C) servers. However, active scanners can only observe and interpret the behavior of TLS servers, the underlying configuration and implementation causing the behavior remains hidden. Existing approaches struggle between resource intensive scans that can reconstruct this data and light-weight fingerprinting approaches that aim to differentiate servers without making any assumptions about their inner working. With this work we propose DissecTLS, an active TLS scanner that is both light-weight enough to be used for Internet measurements and able to reconstruct the configuration and capabilities of the TLS stack. This was achieved by modeling the parameters of the TLS stack and derive an active scan that dynamically creates scanning probes based on the model and the previous responses from the server. We provide a comparison of five active TLS scanning and fingerprinting approaches in a local testbed and on toplist targets. We conducted a measurement study over nine weeks to fingerprint C &C servers and analyzed popular and deprecated TLS parameter usage. Similar to related work, the fingerprinting achieved a maximum precision of 99 % for a conservative detection threshold of 100 %; and at the same time, we improved the recall by a factor of 2.8.

Authors: Markus Sosnowski, Johannes Zirngibl, Patrick Sattler, Georg Carle

Authors: Filip Rezabek*, Marcin Bosk*, Georg Carle, Jörg Ott