Jan Friebertshauser, Florian Kosterhon, Jiska Classen, Matthias Hollick (Secure Mobile Networking Lab, TU Darmstad)

Embedded systems, IoT devices, and systems on a chip such as wireless network cards often run raw firmware binaries. Raw binaries miss metadata such as the target architecture and an entry point. Thus, their analysis is challenging. Nonetheless, chip firmware analysis is vital to the security of modern devices. We find that state-of-the-art disassemblers fail to identify function starts and signatures in raw binaries. In our case, these issues originate from the dense, variable-length ARM Thumb2 instruction set. Binary differs such as BinDiff and Diaphora perform poor on raw ARM binaries, since they depend on correctly identified functions. Moreover, binary patchers like NexMon require function signatures to pass arguments. As a solution for fast diffing and function identification, we design and implement Polypyus. This firmware historian learns from binaries with known functions, generalizes this knowledge, and applies it to raw binaries. Polypyus is independent from architecture and disassembler. However, the results can be imported as disassembler entry points, thereby improving function identification and follow-up results by other binary differs. Additionally, we partially reconstruct function signatures and custom types from Eclipse PDOM files. Each Eclipse project contains a PDOM file, which caches selected project information for compiler optimization. We showcase the capabilities of Polypyus on a set of 20 firmware binaries.

View More Papers

coucouArray ( [post_type] => ndss-paper [post_status] => publish [posts_per_page] => 4 [orderby] => rand [tax_query] => Array ( [0] => Array ( [taxonomy] => category [field] => id [terms] => Array ( [0] => 37 [1] => 47 ) ) ) [post__not_in] => Array ( [0] => 7329 ) )

ROV++: Improved Deployable Defense against BGP Hijacking

Reynaldo Morillo (University of Connecticut), Justin Furuness (University of Connecticut), Cameron Morris (University of Connecticut), James Breslin (University of Connecticut), Amir Herzberg (University of Connecticut), Bing Wang (University of Connecticut)

Read More

Deceptive Deletions for Protecting Withdrawn Posts on Social Media...

Mohsen Minaei (Visa Research), S Chandra Mouli (Purdue University), Mainack Mondal (IIT Kharagpur), Bruno Ribeiro (Purdue University), Aniket Kate (Purdue University)

Read More

FitM: Binary-Only Coverage-GuidedFuzzing for Stateful Network Protocols

Dominik Maier, Otto Bittner, Marc Munier, Julian Beier (TU Berlin)

Read More

Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)