The mechanisms underlying chemifriction (the contribution of interfacial bonding to friction) in defected twisted graphene interfaces are revealed using fully atomistic molecular dynamics simulations based on machine-learning potentials. This involves stochastic events of consecutive bond formation and rupture between single vacancy defects that may enhance friction. A unique shear-induced interlayer atomic transfer healing mechanism is discovered that can be harnessed to design a run-in procedure to restore superlubric sliding. This mechanism should be manifested as negative differential friction coefficients that are expected to emerge under moderate normal loads. A physically motivated phenomenological model is developed to predict the chemifriction effects in experimentally relevant sliding velocity regimes. This allows us to identify a distinct transition between logarithmic increase and logarithmic decrease of the friction force with increasing sliding velocity. While demonstrated for homogeneous graphitic contacts, a similar mechanism is expected to occur in other homogeneous or heterogeneous defected two-dimensional material interfaces.