  We present a study of galaxies showing mid-infrared variability in data taken
in the deepest Spitzer/MIPS 24 $\mu$m surveys in the GOODS-South field. We
divide the dataset in epochs and subepochs to study the long-term
(months-years) and the short-term (days) variability. We use a
$\chi^2$-statistics method to select AGN candidates with a probability $\leq$
1% that the observed variability is due to statistical errors alone. We find 39
(1.7% of the parent sample) sources that show long-term variability and 55
(2.2% of the parent sample) showing short-term variability. That is, 0.03
sources $\times$ arcmin$^{-2}$ for both, long-term and short-term variable
sources. After removing the expected number of false positives inherent to the
method, the estimated percentages are 1.0% and 1.4% of the parent sample for
the long-term and short-term respectively. We compare our candidates with AGN
selected in the X-ray and radio bands, and AGN candidates selected by their IR
emission. Approximately, 50% of the MIPS 24 $\mu$m variable sources would be
identified as AGN with these other methods. Therefore, MIPS 24 $\mu$m
variability is a new method to identify AGN candidates, possibly dust obscured
and low luminosity AGN, that might be missed by other methods. However, the
contribution of the MIPS 24 $\mu$m variable identified AGN to the general AGN
population is small ($\leq$ 13%) in GOODS-South.
