Ravshan Rikhsiev
I am a security researcher specializing in low-level security, reverse engineering, vulnerability research including embedded devices and IoT. I have spoken at cybersecurity conferences including BSides Prague, KazHackStan, Positive Hack Talks, Cyberkent.
@arzedlab | not that active as like Ln or telegram
arzedlab
Session
Modern IoT firmware is a largely unexplored attack surface, and manual analysis doesn't scale. In this talk, we present a pipeline that combines core computer science fundamentals with large language models to automate vulnerability discovery in firmware binaries.
In this talk, we describe how we built a pipeline that combines computer science fundamentals with LLMs to find bugs in firmware. We use LLMs as an operator for detecting vulnerability patterns, a kind of "vuln smell", and walk through how we built the pipeline using control flow graphs, Ghidra internals to extract pseudo-C code, and build taint analyzes pipeline, and how crafting the right prompts with the right context lets even Gemini Flash detect bugs or at least give meaningful hints, and of course our pitfalls, and why LLMs better than fuzzing in case of firmware and MORE.
Attendees will leave with a practical understanding of how to build LLM-assisted binary analysis pipelines and how prompt engineering decisions directly impact bug-finding accuracy.