The vast amount of data crossing the net with terrorism-related content, including voice, is so immense that the use of powerful filtering/detection tools with great discriminative capacities becomes essential. Although the analysis of this content often ends with some manual inspection, a first filtering process becomes basic. In this direction, we propose a speaker clustering solution based on a speaker identification system. We show that both the speaker clustering and the speaker recognition solution can be used individually to efficiently solve searching tasks in several terrorism-related scenarios.