Firmware-level malware represents one of the most persistent and stealthy threats in modern computing systems. Unlike conventional malware that operates within an operating system, firmware implants reside deeper in the hardware stack, allowing them to survive operating system reinstallation and evade traditional security tools. This talk presents a practical approach to firmware security that combines bare-metal data collection with Python-based forensic analysis. A custom bootable tool is used to collect raw firmware data directly from the system before the operating system loads, ensuring that potentially compromised OS-level components cannot interfere with the investigation. Once the firmware data is collected, Python scripts are used to analyze it using techniques commonly applied in security research. These include integrity verification through hashing, signature scanning for known firmware implants, and entropy analysis to detect suspicious or encrypted payloads. The talk will demonstrate how Python can automate firmware analysis workflows and help security researchers build tools for investigating low-level threats. By the end of the session, attendees will understand how firmware-based attacks operate, why they are difficult to detect, and how Python can be used to build practical analysis pipelines for identifying hidden threats at the firmware level.