University of Florida Research Foundation Inc

Grant Haydock Hernandez

Kevin R Butler

Farhaan Fowze

Tuba Yavuz

Jing Tian

Patrick G Traynor

Kevin Raymond Boyce Butler

Various examples are provided related to automated security analysis of baseband firmware. In one example, a system includes a wireless front end and processing circuitry communicatively coupled to the wireless front end and a target device. The processing circuitry can generate mutated packets based upon a device state of the target device; provide the mutated packets for transmission to the target device; receive feedback information from the target device in response to reception of the mutated packets; and identify a firmware flaw associated with the target device in response to the feedback information. In another example, a method includes generating mutated packets based upon a device state of a target device; transmitting the mutated packets to the target device; receiving feedback information from the target device in response to reception of the mutated packets; and identifying a firmware flaw associated with the target device using the feedback information.

Automated security analysis of baseband firmware

The present disclosure describes a firmware analysis system and method that can generate a collection of protocol constraints from known firmware and apply the collection of protocol constraints towards an unknown firm to recognize protocol relevant fields and detect functionality within the unknown firmware.

Protocol model learning and guided firmware analysis

Example embodiments provide methods, apparatuses, systems, computing devices, and/or the like for vetting USB device firmware via a USB-specific firmware analysis framework. In one example, a method is provided for analyzing firmware of a Universal Serial Bus (USB) device. The example method includes steps of receiving a firmware image extracted from the USB device, identifying signatures from the firmware image relating to USB operation, and building an expected model of operation of the USB device using the identified signatures and a database of operational information regarding USB devices. The example method further includes the steps of generating a recovered model of operation of the USB device based on the firmware image and the identified signatures, and comparing the recovered model of operation with the expected model of operation to identify unexpected or unknown behaviors. The example method may further include generating a report comprising the identified unexpected or unknown behaviors.

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Gainesville, FL, United States of America

Grant Haydock Hernandez