  Cosmic rays interacting with the atmosphere allow for the probing of
fundamental interactions at ultra-high energies. We thus obtain limits on
strongly coupled new physics models via their imprints on cosmic-ray air
showers. Using the Monte Carlo event generators Herwig and HERBVI, and the air
shower simulator CORSIKA, to simulate such processes, we apply machine learning
algorithms to the simulated observables to discriminate the events arising via
new physics from the QCD background. We then use the signal and background
discrimination performance to set potential limits on the cross sections of the
new physics models.
