We study leaky adaptive algorithms that employ a general scalar or matrix data nonlinearity. We perform mean-square analysis of this class of algorithms without imposing restrictions on the distribution of the input signal. In particular, we derive conditions on the step-size for stability, and provide closed form expressions for the steady-state performance.