  The ongoing modernization of the power system, involving new equipment
installations and upgrades, exposes the power system to the introduction of
malware into its operation through supply chain attacks. Supply chain attacks
present a significant threat to power systems, allowing cybercriminals to
bypass network defenses and execute deliberate attacks at the physical layer.
Given the exponential advancements in machine intelligence, cybercriminals will
leverage this technology to create sophisticated and adaptable attacks that can
be incorporated into supply chain attacks. We demonstrate the use of
reinforcement learning for developing intelligent attacks incorporated into
supply chain attacks against generation control devices. We simulate potential
disturbances impacting frequency and voltage regulation. The presented method
can provide valuable guidance for defending against supply chain attacks.
