True Random Number Generators (TRNGs) are becoming increasingly relevant in a world where communications, banking security, and cryptographic systems depend on robust and unpredictable sources of randomness. Unlike other types of random number generators, TRNGs rely on inherently stochastic physical phenomena whose unpredictability arises at the material level. This work proposes the use of memristors as a source of randomness for TRNG applications. These devices have attracted growing interest in fields such as unconventional computing and artificial intelligence-oriented architectures. Although the inherent variability of these devices represents a challenge for many of these applications, in this work their stochastic behavior is exploited as the main source of randomness. After demonstrating through simulations the fundamental behavior of this type of devices for TRNG applications, a true random number generator circuit is implemented and validated using, for the first time, a commercially available non-volatile memristor. The proposed system employs a compact topology and a portable experimental setup, demonstrating that this type of solution can be developed using accessible components. The generated sequence is then measured and its randomness is evaluated using widely accepted statistical tests, obtaining satisfactory results. Finally, the circuit is designed in X-FAB XT018 180 nm CMOS technology to interface with Knowm Inc.’s Self-Directed Channel memristors. This thesis was formulated and carried out in collaboration with professors from the University of Seville, as part of a broader effort to explore the potential of emerging hardware technologies for cryptographic applications.