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Proactive detection of network configuration bugs is important to ensure itsproper functioning and reduce cost of network administrator. In this research,we propose to build the control plane verification engine MAVERICK that detectsthe bugs in the network control plane i.e., network device configurations andcontrol plane states. MAVERICK automatically infers signatures for the controlplane configurations (e.g., ACLs, route-maps, route-policies and so on) andstates that allows administrators to automatically detect bugs with minimalhuman intervention. MAVERICK achieves this by effectively leveraging anystructural deviation i.e., outliers in the network configurations that isorganized as simple or complexly nested key-value pairs. The outliers that arecalculated using signature-based outlier detection mechanism are furthercharacterized for its severity and ranked or re-prioritized according to theircriticality. We consider a wide set of heuristics and domain expertise factorsfor effectively to reduce both false positives and false negatives.Ourevaluation on four medium to large-scale enterprise networks show that MAVERICKcan automatically detect the bugs present in the network with approximately 75%accuracy. Further-more, With minimal administrator input i.e., with a fewminutes of signature re-tuning, MAVERICK allows the administrators toeffectively detect approximately 94 - 100% of the bugs present in the network,thereby ranking down less severe bugs and removing false positives.

MAVERICK: Proactively detecting network control plane bugs using structural outlierness