Manual firmware analysis for IoT devices is a bottleneck, delaying vulnerability detection and exposing operational technology to supply-chain attacks. A custom automated workflow emulates diverse CPU architectures (ARM, MIPS) and RTOS environments to detonate firmware, extracting behavioral telemetry like anomalous network calls or unauthorized binary modifications. This architecture directly reduces mean time to detection from weeks to hours, scaling security coverage across thousands of device models and firmware versions without proportional analyst headcount increase.




