  This article aims to investigate sufficient conditions for the stability of
stochastic differential equations with a random structure, particularly in
contexts involving the presence of concentration points. The proof of
asymptotic stability leverages the use of Lyapunov functions, supplemented by
additional constraints on the magnitudes of jumps and jump times, as well as
the Markov property of the system solutions. The findings are elucidated with
an example, demonstrating both stable and unstable conditions of the system.
